diff --git a/.gitignore b/.gitignore
index c259cb8f2d3ec492abbb672179f9125e235806b3..b79145f550b19b9c86992462e10e697b6b677c23 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1,12 +1,13 @@
-.idea
-data/
-data-collection/out/
-*.iml
-*.db
-*.zip
-.vector_cache/
-runs/
-*.csv
-embeddings/tag_embedding_models/*
-*.pt
-embeddings/wandb/*
\ No newline at end of file
+.idea
+data/
+data-collection/out/
+*.iml
+*.db
+*.zip
+.vector_cache/
+runs/
+*.csv
+embeddings/tag_embedding_models/*
+*.pt
+embeddings/wandb/*
+*.pkl
diff --git a/.vscode/settings.json b/.vscode/settings.json
new file mode 100644
index 0000000000000000000000000000000000000000..c54084c7c43e503dd776d3dde8cf61753755beb5
--- /dev/null
+++ b/.vscode/settings.json
@@ -0,0 +1,4 @@
+{
+ "python.pythonPath": "\\\\filestore.soton.ac.uk\\users\\lhb1g20\\.conda\\envs\\gpuservice\\python.exe",
+ "terminal.integrated.windowsEnableConpty": false
+}
\ No newline at end of file
diff --git a/archived/GAT.py b/archived/GAT.py
index e484e36da55c95e16dc5c63bddb13742e55a3ab2..9c974c7a54a602386c6e3caeb6b27fb77167c32b 100644
--- a/archived/GAT.py
+++ b/archived/GAT.py
@@ -1,85 +1,85 @@
-import torch
-from torch_geometric.loader import DataLoader
-from torch_geometric.nn import GATConv, Linear, MeanAggregation, to_hetero
-
-from dataset import UserGraphDataset
-
-
-class GAT(torch.nn.Module):
- def __init__(self, hidden_channels):
- super(GAT, self).__init__()
- torch.manual_seed(12345)
- self.conv1 = GATConv((-1, -1), hidden_channels, add_self_loops=False)
- self.conv2 = GATConv((-1, -1), hidden_channels, add_self_loops=False)
- self.conv3 = GATConv((-1, -1), hidden_channels, add_self_loops=False)
- self.lin = Linear(hidden_channels, 2)
- self.softmax = torch.nn.Softmax(dim=1)
- self.pool = MeanAggregation()
-
- def forward(self, x, edge_index, batch, post_emb):
- # 1. Obtain node embeddings
- x = self.conv1(x, edge_index)
- x = x.relu()
- x = self.conv2(x, edge_index)
- x = x.relu()
- x = self.conv3(x, edge_index)
-
- # 2. Readout layer
- x = self.pool(x, batch) # [batch_size, hidden_channels]
-
- # 3. Concatenate with post embedding
- #x = torch.cat((x, post_emb))
- # 4. Apply a final classifier.
- x = self.lin(x)
- x = self.softmax(x)
- return x
-
-
-def train(model, train_loader):
- model.train()
-
- for data in train_loader: # Iterate in batches over the training dataset.
- print(data)
-
- out = model(data.x_dict, data.edge_index_dict, data.batch_dict, torch.concat([data.question_emb, data.answer_emb])) # Perform a single forward pass.
- print(out, data.label)
- loss = criterion(out, data.label) # Compute the loss.
- loss.backward() # Derive gradients.
- optimizer.step() # Update parameters based on gradients.
- optimizer.zero_grad() # Clear gradients.
-
-
-def test(loader):
- model.eval()
-
- correct = 0
- for data in loader: # Iterate in batches over the training/test dataset.
- out = model(data.x, data.edge_index, data.batch)
- pred = out.argmax(dim=1) # Use the class with highest probability.
- correct += int((pred == data.y).sum()) # Check against ground-truth labels.
- return correct / len(loader.dataset) # Derive ratio of correct predictions.
-
-
-if __name__ == '__main__':
- dataset = UserGraphDataset(root="../data", skip_processing=True)
- train_dataset, val_dataset, test_dataset = torch.utils.data.random_split(dataset, [0.6, 0.1, 0.3])
-
- print(dataset.num_node_features)
-
- train_loader = DataLoader(train_dataset, batch_size=1)
- val_loader = DataLoader(val_dataset, batch_size=64)
- test_loader = DataLoader(test_dataset, batch_size=64)
-
- model = GAT(hidden_channels=64)
- sample = train_dataset[0]
- metadata = (['question', 'answer', 'comment', 'tag', 'module'], [('tag', 'describes', 'question'), ('tag', 'describes', 'answer'), ('tag', 'describes', 'comment'), ('module', 'imported_in', 'question'), ('module', 'imported_in', 'answer'), ('question', 'rev_describes', 'tag'), ('answer', 'rev_describes', 'tag'), ('comment', 'rev_describes', 'tag'), ('question', 'rev_imported_in', 'module'), ('answer', 'rev_imported_in', 'module')])
- model = to_hetero(model, metadata)
- #print(model(sample.x_dict, sample.edge_index_dict, sample.batch_dict))
-
- optimizer = torch.optim.Adam(model.parameters(), lr=0.01)
- criterion = torch.nn.CrossEntropyLoss()
-
- for epoch in range(1, 10):
- train(model, train_loader)
- #train_acc = test(train_loader)
- #print(f'Epoch: {epoch:03d}, Train Acc: {train_acc:.4f}, Test Acc: {test_acc:.4f}')
+import torch
+from torch_geometric.loader import DataLoader
+from torch_geometric.nn import GATConv, Linear, MeanAggregation, to_hetero
+
+from dataset import UserGraphDataset
+
+
+class GAT(torch.nn.Module):
+ def __init__(self, hidden_channels):
+ super(GAT, self).__init__()
+ torch.manual_seed(12345)
+ self.conv1 = GATConv((-1, -1), hidden_channels, add_self_loops=False)
+ self.conv2 = GATConv((-1, -1), hidden_channels, add_self_loops=False)
+ self.conv3 = GATConv((-1, -1), hidden_channels, add_self_loops=False)
+ self.lin = Linear(hidden_channels, 2)
+ self.softmax = torch.nn.Softmax(dim=1)
+ self.pool = MeanAggregation()
+
+ def forward(self, x, edge_index, batch, post_emb):
+ # 1. Obtain node embeddings
+ x = self.conv1(x, edge_index)
+ x = x.relu()
+ x = self.conv2(x, edge_index)
+ x = x.relu()
+ x = self.conv3(x, edge_index)
+
+ # 2. Readout layer
+ x = self.pool(x, batch) # [batch_size, hidden_channels]
+
+ # 3. Concatenate with post embedding
+ #x = torch.cat((x, post_emb))
+ # 4. Apply a final classifier.
+ x = self.lin(x)
+ x = self.softmax(x)
+ return x
+
+
+def train(model, train_loader):
+ model.train()
+
+ for data in train_loader: # Iterate in batches over the training dataset.
+ print(data)
+
+ out = model(data.x_dict, data.edge_index_dict, data.batch_dict, torch.concat([data.question_emb, data.answer_emb])) # Perform a single forward pass.
+ print(out, data.label)
+ loss = criterion(out, data.label) # Compute the loss.
+ loss.backward() # Derive gradients.
+ optimizer.step() # Update parameters based on gradients.
+ optimizer.zero_grad() # Clear gradients.
+
+
+def test(loader):
+ model.eval()
+
+ correct = 0
+ for data in loader: # Iterate in batches over the training/test dataset.
+ out = model(data.x, data.edge_index, data.batch)
+ pred = out.argmax(dim=1) # Use the class with highest probability.
+ correct += int((pred == data.y).sum()) # Check against ground-truth labels.
+ return correct / len(loader.dataset) # Derive ratio of correct predictions.
+
+
+if __name__ == '__main__':
+ dataset = UserGraphDataset(root="../data", skip_processing=True)
+ train_dataset, val_dataset, test_dataset = torch.utils.data.random_split(dataset, [0.6, 0.1, 0.3])
+
+ print(dataset.num_node_features)
+
+ train_loader = DataLoader(train_dataset, batch_size=1)
+ val_loader = DataLoader(val_dataset, batch_size=64)
+ test_loader = DataLoader(test_dataset, batch_size=64)
+
+ model = GAT(hidden_channels=64)
+ sample = train_dataset[0]
+ metadata = (['question', 'answer', 'comment', 'tag', 'module'], [('tag', 'describes', 'question'), ('tag', 'describes', 'answer'), ('tag', 'describes', 'comment'), ('module', 'imported_in', 'question'), ('module', 'imported_in', 'answer'), ('question', 'rev_describes', 'tag'), ('answer', 'rev_describes', 'tag'), ('comment', 'rev_describes', 'tag'), ('question', 'rev_imported_in', 'module'), ('answer', 'rev_imported_in', 'module')])
+ model = to_hetero(model, metadata)
+ #print(model(sample.x_dict, sample.edge_index_dict, sample.batch_dict))
+
+ optimizer = torch.optim.Adam(model.parameters(), lr=0.01)
+ criterion = torch.nn.CrossEntropyLoss()
+
+ for epoch in range(1, 10):
+ train(model, train_loader)
+ #train_acc = test(train_loader)
+ #print(f'Epoch: {epoch:03d}, Train Acc: {train_acc:.4f}, Test Acc: {test_acc:.4f}')
diff --git a/archived/db_handler.py b/archived/db_handler.py
index 89fd5a1d2fc89637144d219f085b26757b2a5cad..9f54e0a39181b0aa4c6fac5e13c9063ba6cd964c 100644
--- a/archived/db_handler.py
+++ b/archived/db_handler.py
@@ -1,50 +1,50 @@
-import sqlite3
-
-import pandas as pd
-
-
-class DBHandler:
- def __init__(self, file_name: str):
- self._db = sqlite3.connect(file_name)
-
- def fetch_questions_by_user_id(self, user_id: int):
- questions = pd.read_sql_query(f"""
- SELECT *
- FROM Post
- WHERE Tags LIKE '%python%' AND (PostTypeId = 1) AND ((LastEditorUserId = {user_id}) OR (OwnerUserId = {user_id}))
- """, self._db)
- questions.set_index('PostId', inplace=True)
-
- def fetch_answers_by_user_id(self, user_id: int):
- answers = pd.read_sql_query(f"""
- SELECT A.Tags, B.*
- FROM Post A
- INNER JOIN Post B ON (B.ParentId = A.PostId) AND (B.ParentId IS NOT NULL)
- WHERE A.Tags LIKE '%python%' AND (B.PostTypeId = 2) AND ((B.LastEditorUserId = {user_id}) OR (B.OwnerUserId = {user_id}))
- """, self._db)
- # Only use the first of the two 'Tags' columns
- answers = answers.loc[:, ~answers.columns.duplicated()].copy()
- answers.set_index('PostId', inplace=True)
- return answers
-
- def fetch_comments_on_questions_by_user_id(self, user_id: int):
- comments_on_questions = pd.read_sql_query(f"""
- SELECT A.Tags, B.*
- FROM Post A
- INNER JOIN Comment B ON (B.PostId = A.PostId)
- WHERE A.Tags LIKE '%python%' AND (B.UserId = {user_id}) AND (A.PostTypeId = 1)
- """, self._db)
- comments_on_questions.set_index('CommentId', inplace=True)
- return comments_on_questions
-
- def fetch_comments_on_answers_by_user_id(self, user_id: int):
- comments_on_answers = pd.read_sql_query(f"""
- SELECT A.Tags, C.*
- FROM Post A
- INNER JOIN Post B ON (B.ParentId = A.PostId) AND (B.ParentId IS NOT NULL)
- INNER JOIN Comment C ON (B.PostId = C.PostId)
- WHERE A.Tags LIKE '%python%' AND (C.UserId = {user_id}) AND (B.PostTypeId = 2)
- """, self._db)
- comments_on_answers.set_index('CommentId', inplace=True)
- return comments_on_answers
-
+import sqlite3
+
+import pandas as pd
+
+
+class DBHandler:
+ def __init__(self, file_name: str):
+ self._db = sqlite3.connect(file_name)
+
+ def fetch_questions_by_user_id(self, user_id: int):
+ questions = pd.read_sql_query(f"""
+ SELECT *
+ FROM Post
+ WHERE Tags LIKE '%python%' AND (PostTypeId = 1) AND ((LastEditorUserId = {user_id}) OR (OwnerUserId = {user_id}))
+ """, self._db)
+ questions.set_index('PostId', inplace=True)
+
+ def fetch_answers_by_user_id(self, user_id: int):
+ answers = pd.read_sql_query(f"""
+ SELECT A.Tags, B.*
+ FROM Post A
+ INNER JOIN Post B ON (B.ParentId = A.PostId) AND (B.ParentId IS NOT NULL)
+ WHERE A.Tags LIKE '%python%' AND (B.PostTypeId = 2) AND ((B.LastEditorUserId = {user_id}) OR (B.OwnerUserId = {user_id}))
+ """, self._db)
+ # Only use the first of the two 'Tags' columns
+ answers = answers.loc[:, ~answers.columns.duplicated()].copy()
+ answers.set_index('PostId', inplace=True)
+ return answers
+
+ def fetch_comments_on_questions_by_user_id(self, user_id: int):
+ comments_on_questions = pd.read_sql_query(f"""
+ SELECT A.Tags, B.*
+ FROM Post A
+ INNER JOIN Comment B ON (B.PostId = A.PostId)
+ WHERE A.Tags LIKE '%python%' AND (B.UserId = {user_id}) AND (A.PostTypeId = 1)
+ """, self._db)
+ comments_on_questions.set_index('CommentId', inplace=True)
+ return comments_on_questions
+
+ def fetch_comments_on_answers_by_user_id(self, user_id: int):
+ comments_on_answers = pd.read_sql_query(f"""
+ SELECT A.Tags, C.*
+ FROM Post A
+ INNER JOIN Post B ON (B.ParentId = A.PostId) AND (B.ParentId IS NOT NULL)
+ INNER JOIN Comment C ON (B.PostId = C.PostId)
+ WHERE A.Tags LIKE '%python%' AND (C.UserId = {user_id}) AND (B.PostTypeId = 2)
+ """, self._db)
+ comments_on_answers.set_index('CommentId', inplace=True)
+ return comments_on_answers
+
diff --git a/archived/embeddings.ipynb b/archived/embeddings.ipynb
index 787757ea05cc34836bb198837260d7f770e6125e..48b98e6f13847ac3d3f08c5fb7ae42239a93ce15 100644
--- a/archived/embeddings.ipynb
+++ b/archived/embeddings.ipynb
@@ -1,874 +1,874 @@
-{
- "cells": [
- {
- "cell_type": "markdown",
- "source": [
- "# Embeddings\n",
- "Exploration into how different embeddings can be used to represent posts."
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": 1,
- "outputs": [],
- "source": [
- "import itertools\n",
- "import sqlite3\n",
- "from typing import List\n",
- "import itertools\n",
- "import pandas as pd\n",
- "from typing import *"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": 2,
- "outputs": [],
- "source": [
- "# Create your connection.\n",
- "db = sqlite3.connect('../stackoverflow.db')"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": 3,
- "outputs": [
- {
- "data": {
- "text/plain": " TagName Count\nTagId \n1 .net 323469\n2 html 1146245\n3 javascript 2426650\n4 css 771867\n5 php 1445747\n... ... ...\n158156 lost-update 1\n158157 chai-subset 1\n158159 at-spi 1\n158160 oro 0\n158161 sigsci 1\n\n[63653 rows x 2 columns]",
- "text/html": "<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>TagName</th>\n <th>Count</th>\n </tr>\n <tr>\n <th>TagId</th>\n <th></th>\n <th></th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>1</th>\n <td>.net</td>\n <td>323469</td>\n </tr>\n <tr>\n <th>2</th>\n <td>html</td>\n <td>1146245</td>\n </tr>\n <tr>\n <th>3</th>\n <td>javascript</td>\n <td>2426650</td>\n </tr>\n <tr>\n <th>4</th>\n <td>css</td>\n <td>771867</td>\n </tr>\n <tr>\n <th>5</th>\n <td>php</td>\n <td>1445747</td>\n </tr>\n <tr>\n <th>...</th>\n <td>...</td>\n <td>...</td>\n </tr>\n <tr>\n <th>158156</th>\n <td>lost-update</td>\n <td>1</td>\n </tr>\n <tr>\n <th>158157</th>\n <td>chai-subset</td>\n <td>1</td>\n </tr>\n <tr>\n <th>158159</th>\n <td>at-spi</td>\n <td>1</td>\n </tr>\n <tr>\n <th>158160</th>\n <td>oro</td>\n <td>0</td>\n </tr>\n <tr>\n <th>158161</th>\n <td>sigsci</td>\n <td>1</td>\n </tr>\n </tbody>\n</table>\n<p>63653 rows × 2 columns</p>\n</div>"
- },
- "execution_count": 3,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "tag_df = pd.read_sql_query(\"SELECT * FROM Tag\", db)\n",
- "tag_df.set_index('TagId', inplace=True)\n",
- "tag_df"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": 4,
- "outputs": [
- {
- "data": {
- "text/plain": " PostTypeId AcceptedAnswerId CreationDate Score \\\nPostId \n1 1 7.0 2008-07-31T21:42:52.667 781 \n2 1 31.0 2008-07-31T22:08:08.620 318 \n3 2 NaN 2008-07-31T22:17:57.883 517 \n4 1 1404.0 2008-07-31T23:40:59.743 2161 \n5 1 1248.0 2008-07-31T23:55:37.967 1629 \n... ... ... ... ... \n499996 2 NaN 2009-04-03T02:10:35.270 2 \n499997 2 NaN 2009-04-03T02:10:49.060 1 \n499998 1 799526.0 2009-04-03T02:11:16.237 4 \n499999 2 NaN 2009-04-03T02:14:04.293 5 \n500000 2 NaN 2009-04-03T02:15:39.347 1 \n\n ViewCount Body \\\nPostId \n1 67914.0 <p>I want to assign the decimal variable "... \n2 23047.0 <p>I have an absolutely positioned <code>div</... \n3 NaN <p>An explicit cast to <code>double</code> lik... \n4 757897.0 <p>Given a <code>DateTime</code> representing ... \n5 193525.0 <p>Given a specific <code>DateTime</code> valu... \n... ... ... \n499996 NaN <p>If we can assume that:</p>\\n\\n<ul>\\n<li>the... \n499997 NaN <p>Change:</p>\\n\\n<pre><code>for ansSeries in ... \n499998 3611.0 <p>Here are the first few lines of my page:</p... \n499999 NaN <p>Since, in general, there is more than one p... \n500000 NaN <p>Ugh. Short of writing your own authenticati... \n\n OwnerUserId LastEditorUserId LastEditorDisplayName \\\nPostId \n1 8.0 16124033.0 Rich B \n2 9.0 9134576.0 user14723686 \n3 9.0 5496973.0 None \n4 1.0 3524942.0 Rich B \n5 1.0 16790137.0 user2370523 \n... ... ... ... \n499996 72990.0 NaN None \n499997 9940.0 NaN None \n499998 63887.0 NaN None \n499999 15168.0 NaN None \n500000 85863.0 NaN None \n\n LastEditDate \\\nPostId \n1 2022-09-08T05:07:26.033 \n2 2021-01-29T18:46:45.963 \n3 2019-10-21T14:03:54.607 \n4 2022-07-27T22:34:36.320 \n5 2022-07-10T00:19:55.237 \n... ... \n499996 None \n499997 None \n499998 None \n499999 None \n500000 None \n\n Title \\\nPostId \n1 How to convert Decimal to Double in C#? \n2 Why did the width collapse in the percentage w... \n3 None \n4 How do I calculate someone's age based on a Da... \n5 Calculate relative time in C# \n... ... \n499996 None \n499997 None \n499998 Why can't I use session_start() in my php scri... \n499999 None \n500000 None \n\n Tags AnswerCount \\\nPostId \n1 <c#><floating-point><type-conversion><double><... 14.0 \n2 <html><css><internet-explorer-7> 7.0 \n3 None NaN \n4 <c#><.net><datetime> 71.0 \n5 <c#><datetime><time><datediff><relative-time-s... 41.0 \n... ... ... \n499996 None NaN \n499997 None NaN \n499998 <php><session><cookies><header> 2.0 \n499999 None NaN \n500000 None NaN \n\n CommentCount FavoriteCount CommunityOwnedDate ContentLicense \\\nPostId \n1 6 60.0 2012-10-31T16:42:47.213 CC BY-SA 4.0 \n2 0 13.0 None CC BY-SA 4.0 \n3 1 NaN None CC BY-SA 4.0 \n4 10 492.0 2011-08-16T19:40:43.080 CC BY-SA 4.0 \n5 3 552.0 2009-09-04T13:15:59.820 CC BY-SA 4.0 \n... ... ... ... ... \n499996 0 NaN None CC BY-SA 2.5 \n499997 0 NaN None CC BY-SA 2.5 \n499998 2 NaN None CC BY-SA 2.5 \n499999 1 NaN None CC BY-SA 2.5 \n500000 1 NaN None CC BY-SA 2.5 \n\n ParentId \nPostId \n1 NaN \n2 NaN \n3 4.0 \n4 NaN \n5 NaN \n... ... \n499996 712186.0 \n499997 712225.0 \n499998 NaN \n499999 712322.0 \n500000 712023.0 \n\n[500000 rows x 18 columns]",
- "text/html": "<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>PostTypeId</th>\n <th>AcceptedAnswerId</th>\n <th>CreationDate</th>\n <th>Score</th>\n <th>ViewCount</th>\n <th>Body</th>\n <th>OwnerUserId</th>\n <th>LastEditorUserId</th>\n <th>LastEditorDisplayName</th>\n <th>LastEditDate</th>\n <th>Title</th>\n <th>Tags</th>\n <th>AnswerCount</th>\n <th>CommentCount</th>\n <th>FavoriteCount</th>\n <th>CommunityOwnedDate</th>\n <th>ContentLicense</th>\n <th>ParentId</th>\n </tr>\n <tr>\n <th>PostId</th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>1</th>\n <td>1</td>\n <td>7.0</td>\n <td>2008-07-31T21:42:52.667</td>\n <td>781</td>\n <td>67914.0</td>\n <td><p>I want to assign the decimal variable &quot...</td>\n <td>8.0</td>\n <td>16124033.0</td>\n <td>Rich B</td>\n <td>2022-09-08T05:07:26.033</td>\n <td>How to convert Decimal to Double in C#?</td>\n <td><c#><floating-point><type-conversion><double><...</td>\n <td>14.0</td>\n <td>6</td>\n <td>60.0</td>\n <td>2012-10-31T16:42:47.213</td>\n <td>CC BY-SA 4.0</td>\n <td>NaN</td>\n </tr>\n <tr>\n <th>2</th>\n <td>1</td>\n <td>31.0</td>\n <td>2008-07-31T22:08:08.620</td>\n <td>318</td>\n <td>23047.0</td>\n <td><p>I have an absolutely positioned <code>div</...</td>\n <td>9.0</td>\n <td>9134576.0</td>\n <td>user14723686</td>\n <td>2021-01-29T18:46:45.963</td>\n <td>Why did the width collapse in the percentage w...</td>\n <td><html><css><internet-explorer-7></td>\n <td>7.0</td>\n <td>0</td>\n <td>13.0</td>\n <td>None</td>\n <td>CC BY-SA 4.0</td>\n <td>NaN</td>\n </tr>\n <tr>\n <th>3</th>\n <td>2</td>\n <td>NaN</td>\n <td>2008-07-31T22:17:57.883</td>\n <td>517</td>\n <td>NaN</td>\n <td><p>An explicit cast to <code>double</code> lik...</td>\n <td>9.0</td>\n <td>5496973.0</td>\n <td>None</td>\n <td>2019-10-21T14:03:54.607</td>\n <td>None</td>\n <td>None</td>\n <td>NaN</td>\n <td>1</td>\n <td>NaN</td>\n <td>None</td>\n <td>CC BY-SA 4.0</td>\n <td>4.0</td>\n </tr>\n <tr>\n <th>4</th>\n <td>1</td>\n <td>1404.0</td>\n <td>2008-07-31T23:40:59.743</td>\n <td>2161</td>\n <td>757897.0</td>\n <td><p>Given a <code>DateTime</code> representing ...</td>\n <td>1.0</td>\n <td>3524942.0</td>\n <td>Rich B</td>\n <td>2022-07-27T22:34:36.320</td>\n <td>How do I calculate someone's age based on a Da...</td>\n <td><c#><.net><datetime></td>\n <td>71.0</td>\n <td>10</td>\n <td>492.0</td>\n <td>2011-08-16T19:40:43.080</td>\n <td>CC BY-SA 4.0</td>\n <td>NaN</td>\n </tr>\n <tr>\n <th>5</th>\n <td>1</td>\n <td>1248.0</td>\n <td>2008-07-31T23:55:37.967</td>\n <td>1629</td>\n <td>193525.0</td>\n <td><p>Given a specific <code>DateTime</code> valu...</td>\n <td>1.0</td>\n <td>16790137.0</td>\n <td>user2370523</td>\n <td>2022-07-10T00:19:55.237</td>\n <td>Calculate relative time in C#</td>\n <td><c#><datetime><time><datediff><relative-time-s...</td>\n <td>41.0</td>\n <td>3</td>\n <td>552.0</td>\n <td>2009-09-04T13:15:59.820</td>\n <td>CC BY-SA 4.0</td>\n <td>NaN</td>\n </tr>\n <tr>\n <th>...</th>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n </tr>\n <tr>\n <th>499996</th>\n <td>2</td>\n <td>NaN</td>\n <td>2009-04-03T02:10:35.270</td>\n <td>2</td>\n <td>NaN</td>\n <td><p>If we can assume that:</p>\\n\\n<ul>\\n<li>the...</td>\n <td>72990.0</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>NaN</td>\n <td>0</td>\n <td>NaN</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>712186.0</td>\n </tr>\n <tr>\n <th>499997</th>\n <td>2</td>\n <td>NaN</td>\n <td>2009-04-03T02:10:49.060</td>\n <td>1</td>\n <td>NaN</td>\n <td><p>Change:</p>\\n\\n<pre><code>for ansSeries in ...</td>\n <td>9940.0</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>NaN</td>\n <td>0</td>\n <td>NaN</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>712225.0</td>\n </tr>\n <tr>\n <th>499998</th>\n <td>1</td>\n <td>799526.0</td>\n <td>2009-04-03T02:11:16.237</td>\n <td>4</td>\n <td>3611.0</td>\n <td><p>Here are the first few lines of my page:</p...</td>\n <td>63887.0</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>Why can't I use session_start() in my php scri...</td>\n <td><php><session><cookies><header></td>\n <td>2.0</td>\n <td>2</td>\n <td>NaN</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>NaN</td>\n </tr>\n <tr>\n <th>499999</th>\n <td>2</td>\n <td>NaN</td>\n <td>2009-04-03T02:14:04.293</td>\n <td>5</td>\n <td>NaN</td>\n <td><p>Since, in general, there is more than one p...</td>\n <td>15168.0</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>NaN</td>\n <td>1</td>\n <td>NaN</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>712322.0</td>\n </tr>\n <tr>\n <th>500000</th>\n <td>2</td>\n <td>NaN</td>\n <td>2009-04-03T02:15:39.347</td>\n <td>1</td>\n <td>NaN</td>\n <td><p>Ugh. Short of writing your own authenticati...</td>\n <td>85863.0</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>NaN</td>\n <td>1</td>\n <td>NaN</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>712023.0</td>\n </tr>\n </tbody>\n</table>\n<p>500000 rows × 18 columns</p>\n</div>"
- },
- "execution_count": 4,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "POST_LIMIT = 500000\n",
- "post_df = pd.read_sql_query(f\"SELECT * FROM Post LIMIT {POST_LIMIT}\", db)\n",
- "post_df.set_index('PostId', inplace=True)\n",
- "post_df"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": 5,
- "outputs": [
- {
- "data": {
- "text/plain": " UserId Name CreationDate Class TagBased\nBadgeId \n1 3718 Teacher 2008-09-15T08:55:03.923 3 False\n2 994 Teacher 2008-09-15T08:55:03.957 3 False\n3 3893 Teacher 2008-09-15T08:55:03.957 3 False\n4 4591 Teacher 2008-09-15T08:55:03.957 3 False\n5 5196 Teacher 2008-09-15T08:55:03.957 3 False\n... ... ... ... ... ...\n499996 51452 Good Answer 2010-02-15T12:27:33.500 2 False\n499997 250648 Critic 2010-02-15T12:32:31.950 3 False\n499998 162569 Commentator 2010-02-15T12:32:32.713 3 False\n499999 116388 Popular Question 2010-02-15T12:32:32.930 3 False\n500000 267503 Tumbleweed 2010-02-15T12:32:35.007 3 False\n\n[500000 rows x 5 columns]",
- "text/html": "<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>UserId</th>\n <th>Name</th>\n <th>CreationDate</th>\n <th>Class</th>\n <th>TagBased</th>\n </tr>\n <tr>\n <th>BadgeId</th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>1</th>\n <td>3718</td>\n <td>Teacher</td>\n <td>2008-09-15T08:55:03.923</td>\n <td>3</td>\n <td>False</td>\n </tr>\n <tr>\n <th>2</th>\n <td>994</td>\n <td>Teacher</td>\n <td>2008-09-15T08:55:03.957</td>\n <td>3</td>\n <td>False</td>\n </tr>\n <tr>\n <th>3</th>\n <td>3893</td>\n <td>Teacher</td>\n <td>2008-09-15T08:55:03.957</td>\n <td>3</td>\n <td>False</td>\n </tr>\n <tr>\n <th>4</th>\n <td>4591</td>\n <td>Teacher</td>\n <td>2008-09-15T08:55:03.957</td>\n <td>3</td>\n <td>False</td>\n </tr>\n <tr>\n <th>5</th>\n <td>5196</td>\n <td>Teacher</td>\n <td>2008-09-15T08:55:03.957</td>\n <td>3</td>\n <td>False</td>\n </tr>\n <tr>\n <th>...</th>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n </tr>\n <tr>\n <th>499996</th>\n <td>51452</td>\n <td>Good Answer</td>\n <td>2010-02-15T12:27:33.500</td>\n <td>2</td>\n <td>False</td>\n </tr>\n <tr>\n <th>499997</th>\n <td>250648</td>\n <td>Critic</td>\n <td>2010-02-15T12:32:31.950</td>\n <td>3</td>\n <td>False</td>\n </tr>\n <tr>\n <th>499998</th>\n <td>162569</td>\n <td>Commentator</td>\n <td>2010-02-15T12:32:32.713</td>\n <td>3</td>\n <td>False</td>\n </tr>\n <tr>\n <th>499999</th>\n <td>116388</td>\n <td>Popular Question</td>\n <td>2010-02-15T12:32:32.930</td>\n <td>3</td>\n <td>False</td>\n </tr>\n <tr>\n <th>500000</th>\n <td>267503</td>\n <td>Tumbleweed</td>\n <td>2010-02-15T12:32:35.007</td>\n <td>3</td>\n <td>False</td>\n </tr>\n </tbody>\n</table>\n<p>500000 rows × 5 columns</p>\n</div>"
- },
- "execution_count": 5,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "BADGE_LIMIT = 500000\n",
- "badge_df = pd.read_sql_query(f\"SELECT * FROM badge LIMIT {BADGE_LIMIT}\", db)\n",
- "badge_df.set_index('BadgeId', inplace=True)\n",
- "badge_df"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": 6,
- "outputs": [
- {
- "data": {
- "text/plain": " Reputation CreationDate DisplayName \\\nUserId \n-1009 1 2022-05-17T15:06:54.890 WSO2 \n-1008 1 2022-01-31T19:45:27.477 Twilio \n-1007 1 2021-09-30T18:39:12.143 AudioBubble2 \n-1006 1 2021-09-27T19:40:44.437 Intel \n-1005 1 2021-07-29T14:07:57.580 GitLab \n... ... ... ... \n 884592 31 2011-08-08T18:18:02.387 Ann \n 884593 335 2011-08-08T18:19:27.857 ymliu \n 884595 123 2011-08-08T18:20:03.193 Neil Woods \n 884597 21 2011-08-08T18:21:27.077 Nathan B \n 884599 31 2011-08-08T18:22:16.987 Quaitex \n\n LastAccessDate WebsiteUrl Location \\\nUserId \n-1009 2022-05-17T15:06:54.890 None None \n-1008 2022-01-31T19:45:27.477 None None \n-1007 2021-09-30T18:39:12.143 None None \n-1006 2021-09-27T19:40:44.437 None None \n-1005 2021-07-29T14:07:57.580 None None \n... ... ... ... \n 884592 2011-08-08T18:18:02.387 None None \n 884593 2020-04-23T00:04:46.763 None \n 884595 2021-09-08T11:14:32.143 None \n 884597 2022-09-22T20:23:45.923 None \n 884599 2011-09-01T14:16:54.883 None None \n\n AboutMe Views UpVotes \\\nUserId \n-1009 <p>WSO2 solutions give enterprises the flexibi... 0 0 \n-1008 <p>Twilio has democratized channels like voice... 0 0 \n-1007 <p>Official Q&A support for AudioBubble2</... 0 0 \n-1006 <p>A space for developers to collaborate on In... 0 0 \n-1005 <p>GitLab is the open DevOps platform, deliver... 0 0 \n... ... ... ... \n 884592 None 0 0 \n 884593 33 8 \n 884595 6 3 \n 884597 14 28 \n 884599 None 5 0 \n\n DownVotes ProfileImageUrl AccountId \nUserId \n-1009 0 None NaN \n-1008 0 None NaN \n-1007 0 None NaN \n-1006 0 None NaN \n-1005 0 None NaN \n... ... ... ... \n 884592 0 None 802774.0 \n 884593 0 https://i.stack.imgur.com/jMCNj.jpg 474725.0 \n 884595 0 None 802775.0 \n 884597 0 https://i.stack.imgur.com/CMmBO.jpg 474727.0 \n 884599 0 None 796823.0 \n\n[500000 rows x 12 columns]",
- "text/html": "<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>Reputation</th>\n <th>CreationDate</th>\n <th>DisplayName</th>\n <th>LastAccessDate</th>\n <th>WebsiteUrl</th>\n <th>Location</th>\n <th>AboutMe</th>\n <th>Views</th>\n <th>UpVotes</th>\n <th>DownVotes</th>\n <th>ProfileImageUrl</th>\n <th>AccountId</th>\n </tr>\n <tr>\n <th>UserId</th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>-1009</th>\n <td>1</td>\n <td>2022-05-17T15:06:54.890</td>\n <td>WSO2</td>\n <td>2022-05-17T15:06:54.890</td>\n <td>None</td>\n <td>None</td>\n <td><p>WSO2 solutions give enterprises the flexibi...</td>\n <td>0</td>\n <td>0</td>\n <td>0</td>\n <td>None</td>\n <td>NaN</td>\n </tr>\n <tr>\n <th>-1008</th>\n <td>1</td>\n <td>2022-01-31T19:45:27.477</td>\n <td>Twilio</td>\n <td>2022-01-31T19:45:27.477</td>\n <td>None</td>\n <td>None</td>\n <td><p>Twilio has democratized channels like voice...</td>\n <td>0</td>\n <td>0</td>\n <td>0</td>\n <td>None</td>\n <td>NaN</td>\n </tr>\n <tr>\n <th>-1007</th>\n <td>1</td>\n <td>2021-09-30T18:39:12.143</td>\n <td>AudioBubble2</td>\n <td>2021-09-30T18:39:12.143</td>\n <td>None</td>\n <td>None</td>\n <td><p>Official Q&amp;A support for AudioBubble2</...</td>\n <td>0</td>\n <td>0</td>\n <td>0</td>\n <td>None</td>\n <td>NaN</td>\n </tr>\n <tr>\n <th>-1006</th>\n <td>1</td>\n <td>2021-09-27T19:40:44.437</td>\n <td>Intel</td>\n <td>2021-09-27T19:40:44.437</td>\n <td>None</td>\n <td>None</td>\n <td><p>A space for developers to collaborate on In...</td>\n <td>0</td>\n <td>0</td>\n <td>0</td>\n <td>None</td>\n <td>NaN</td>\n </tr>\n <tr>\n <th>-1005</th>\n <td>1</td>\n <td>2021-07-29T14:07:57.580</td>\n <td>GitLab</td>\n <td>2021-07-29T14:07:57.580</td>\n <td>None</td>\n <td>None</td>\n <td><p>GitLab is the open DevOps platform, deliver...</td>\n <td>0</td>\n <td>0</td>\n <td>0</td>\n <td>None</td>\n <td>NaN</td>\n </tr>\n <tr>\n <th>...</th>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n </tr>\n <tr>\n <th>884592</th>\n <td>31</td>\n <td>2011-08-08T18:18:02.387</td>\n <td>Ann</td>\n <td>2011-08-08T18:18:02.387</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>0</td>\n <td>0</td>\n <td>0</td>\n <td>None</td>\n <td>802774.0</td>\n </tr>\n <tr>\n <th>884593</th>\n <td>335</td>\n <td>2011-08-08T18:19:27.857</td>\n <td>ymliu</td>\n <td>2020-04-23T00:04:46.763</td>\n <td></td>\n <td>None</td>\n <td></td>\n <td>33</td>\n <td>8</td>\n <td>0</td>\n <td>https://i.stack.imgur.com/jMCNj.jpg</td>\n <td>474725.0</td>\n </tr>\n <tr>\n <th>884595</th>\n <td>123</td>\n <td>2011-08-08T18:20:03.193</td>\n <td>Neil Woods</td>\n <td>2021-09-08T11:14:32.143</td>\n <td></td>\n <td>None</td>\n <td></td>\n <td>6</td>\n <td>3</td>\n <td>0</td>\n <td>None</td>\n <td>802775.0</td>\n </tr>\n <tr>\n <th>884597</th>\n <td>21</td>\n <td>2011-08-08T18:21:27.077</td>\n <td>Nathan B</td>\n <td>2022-09-22T20:23:45.923</td>\n <td></td>\n <td>None</td>\n <td></td>\n <td>14</td>\n <td>28</td>\n <td>0</td>\n <td>https://i.stack.imgur.com/CMmBO.jpg</td>\n <td>474727.0</td>\n </tr>\n <tr>\n <th>884599</th>\n <td>31</td>\n <td>2011-08-08T18:22:16.987</td>\n <td>Quaitex</td>\n <td>2011-09-01T14:16:54.883</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>5</td>\n <td>0</td>\n <td>0</td>\n <td>None</td>\n <td>796823.0</td>\n </tr>\n </tbody>\n</table>\n<p>500000 rows × 12 columns</p>\n</div>"
- },
- "execution_count": 6,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "user_LIMIT = 500000\n",
- "user_df = pd.read_sql_query(f\"SELECT * FROM user LIMIT {user_LIMIT}\", db)\n",
- "user_df.set_index('UserId', inplace=True)\n",
- "user_df"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": 7,
- "outputs": [
- {
- "data": {
- "text/plain": " PostId Score Body \\\nCommentId \n1 45651 6 It will help if you give some details of which... \n2 47428 3 One of the things that make a url user-friendl... \n3 47481 0 I agree, both CodeRush and RefactorPro are vis... \n4 47373 0 Just wanted to mention that this is an excelle... \n5 47497 1 Indeed, the only way to do this is get the ser... \n... ... ... ... \n499996 1044179 0 The index is there already. How can I force or... \n499997 1047464 0 are you sure you can rewrite to a URL on anoth... \n499998 1045341 0 Not sure if I understood correctly. \\nWhere's ... \n499999 1047471 0 Is there a way to remove that selected class f... \n500000 1043743 0 I've added some XSLT that does the necessary c... \n\n CreationDate UserId ContentLicense \nCommentId \n1 2008-09-06T13:38:23.647 242.0 CC BY-SA 2.5 \n2 2008-09-06T13:51:47.843 4642.0 CC BY-SA 2.5 \n3 2008-09-06T14:15:46.897 4642.0 CC BY-SA 2.5 \n4 2008-09-06T14:30:40.217 2495.0 CC BY-SA 2.5 \n5 2008-09-06T14:42:35.303 4642.0 CC BY-SA 2.5 \n... ... ... ... \n499996 2009-06-26T05:43:11.223 87248.0 CC BY-SA 2.5 \n499997 2009-06-26T05:43:42.253 109102.0 CC BY-SA 2.5 \n499998 2009-06-26T05:46:21.890 73715.0 CC BY-SA 2.5 \n499999 2009-06-26T05:46:23.497 86038.0 CC BY-SA 2.5 \n500000 2009-06-26T05:48:48.330 18771.0 CC BY-SA 2.5 \n\n[500000 rows x 6 columns]",
- "text/html": "<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>PostId</th>\n <th>Score</th>\n <th>Body</th>\n <th>CreationDate</th>\n <th>UserId</th>\n <th>ContentLicense</th>\n </tr>\n <tr>\n <th>CommentId</th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>1</th>\n <td>45651</td>\n <td>6</td>\n <td>It will help if you give some details of which...</td>\n <td>2008-09-06T13:38:23.647</td>\n <td>242.0</td>\n <td>CC BY-SA 2.5</td>\n </tr>\n <tr>\n <th>2</th>\n <td>47428</td>\n <td>3</td>\n <td>One of the things that make a url user-friendl...</td>\n <td>2008-09-06T13:51:47.843</td>\n <td>4642.0</td>\n <td>CC BY-SA 2.5</td>\n </tr>\n <tr>\n <th>3</th>\n <td>47481</td>\n <td>0</td>\n <td>I agree, both CodeRush and RefactorPro are vis...</td>\n <td>2008-09-06T14:15:46.897</td>\n <td>4642.0</td>\n <td>CC BY-SA 2.5</td>\n </tr>\n <tr>\n <th>4</th>\n <td>47373</td>\n <td>0</td>\n <td>Just wanted to mention that this is an excelle...</td>\n <td>2008-09-06T14:30:40.217</td>\n <td>2495.0</td>\n <td>CC BY-SA 2.5</td>\n </tr>\n <tr>\n <th>5</th>\n <td>47497</td>\n <td>1</td>\n <td>Indeed, the only way to do this is get the ser...</td>\n <td>2008-09-06T14:42:35.303</td>\n <td>4642.0</td>\n <td>CC BY-SA 2.5</td>\n </tr>\n <tr>\n <th>...</th>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n </tr>\n <tr>\n <th>499996</th>\n <td>1044179</td>\n <td>0</td>\n <td>The index is there already. How can I force or...</td>\n <td>2009-06-26T05:43:11.223</td>\n <td>87248.0</td>\n <td>CC BY-SA 2.5</td>\n </tr>\n <tr>\n <th>499997</th>\n <td>1047464</td>\n <td>0</td>\n <td>are you sure you can rewrite to a URL on anoth...</td>\n <td>2009-06-26T05:43:42.253</td>\n <td>109102.0</td>\n <td>CC BY-SA 2.5</td>\n </tr>\n <tr>\n <th>499998</th>\n <td>1045341</td>\n <td>0</td>\n <td>Not sure if I understood correctly. \\nWhere's ...</td>\n <td>2009-06-26T05:46:21.890</td>\n <td>73715.0</td>\n <td>CC BY-SA 2.5</td>\n </tr>\n <tr>\n <th>499999</th>\n <td>1047471</td>\n <td>0</td>\n <td>Is there a way to remove that selected class f...</td>\n <td>2009-06-26T05:46:23.497</td>\n <td>86038.0</td>\n <td>CC BY-SA 2.5</td>\n </tr>\n <tr>\n <th>500000</th>\n <td>1043743</td>\n <td>0</td>\n <td>I've added some XSLT that does the necessary c...</td>\n <td>2009-06-26T05:48:48.330</td>\n <td>18771.0</td>\n <td>CC BY-SA 2.5</td>\n </tr>\n </tbody>\n</table>\n<p>500000 rows × 6 columns</p>\n</div>"
- },
- "execution_count": 7,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "comment_LIMIT = 500000\n",
- "comment_df = pd.read_sql_query(f\"SELECT * FROM comment LIMIT {comment_LIMIT}\", db)\n",
- "comment_df.set_index('CommentId', inplace=True)\n",
- "comment_df"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": 8,
- "outputs": [
- {
- "data": {
- "text/plain": " PostId VoteTypeId CreationDate\nVoteId \n1 1 2 2008-07-31T00:00:00.000\n2 3 2 2008-07-31T00:00:00.000\n3 2 2 2008-07-31T00:00:00.000\n4 4 2 2008-07-31T00:00:00.000\n5 6 2 2008-07-31T00:00:00.000\n... ... ... ...\n499996 231200 2 2008-10-23T00:00:00.000\n499997 231274 2 2008-10-23T00:00:00.000\n499998 230845 5 2008-10-23T00:00:00.000\n499999 231245 2 2008-10-23T00:00:00.000\n500000 149397 2 2008-10-23T00:00:00.000\n\n[500000 rows x 3 columns]",
- "text/html": "<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>PostId</th>\n <th>VoteTypeId</th>\n <th>CreationDate</th>\n </tr>\n <tr>\n <th>VoteId</th>\n <th></th>\n <th></th>\n <th></th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>1</th>\n <td>1</td>\n <td>2</td>\n <td>2008-07-31T00:00:00.000</td>\n </tr>\n <tr>\n <th>2</th>\n <td>3</td>\n <td>2</td>\n <td>2008-07-31T00:00:00.000</td>\n </tr>\n <tr>\n <th>3</th>\n <td>2</td>\n <td>2</td>\n <td>2008-07-31T00:00:00.000</td>\n </tr>\n <tr>\n <th>4</th>\n <td>4</td>\n <td>2</td>\n <td>2008-07-31T00:00:00.000</td>\n </tr>\n <tr>\n <th>5</th>\n <td>6</td>\n <td>2</td>\n <td>2008-07-31T00:00:00.000</td>\n </tr>\n <tr>\n <th>...</th>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n </tr>\n <tr>\n <th>499996</th>\n <td>231200</td>\n <td>2</td>\n <td>2008-10-23T00:00:00.000</td>\n </tr>\n <tr>\n <th>499997</th>\n <td>231274</td>\n <td>2</td>\n <td>2008-10-23T00:00:00.000</td>\n </tr>\n <tr>\n <th>499998</th>\n <td>230845</td>\n <td>5</td>\n <td>2008-10-23T00:00:00.000</td>\n </tr>\n <tr>\n <th>499999</th>\n <td>231245</td>\n <td>2</td>\n <td>2008-10-23T00:00:00.000</td>\n </tr>\n <tr>\n <th>500000</th>\n <td>149397</td>\n <td>2</td>\n <td>2008-10-23T00:00:00.000</td>\n </tr>\n </tbody>\n</table>\n<p>500000 rows × 3 columns</p>\n</div>"
- },
- "execution_count": 8,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "vote_LIMIT = 500000\n",
- "vote_df = pd.read_sql_query(f\"SELECT * FROM vote LIMIT {vote_LIMIT}\", db)\n",
- "vote_df.set_index('VoteId', inplace=True)\n",
- "vote_df"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "markdown",
- "source": [
- "So, we want to build an embedding for the body of posts.\n",
- "The body of posts are stored as HTML, we need to split up the text and the code snippets so we can process them separately."
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": 9,
- "outputs": [
- {
- "data": {
- "text/plain": " PostTypeId AcceptedAnswerId CreationDate Score \\\nPostId \n1 1 7.0 2008-07-31T21:42:52.667 781 \n\n ViewCount Body \\\nPostId \n1 67914.0 <p>I want to assign the decimal variable "... \n\n OwnerUserId LastEditorUserId LastEditorDisplayName \\\nPostId \n1 8.0 16124033.0 Rich B \n\n LastEditDate Title \\\nPostId \n1 2022-09-08T05:07:26.033 How to convert Decimal to Double in C#? \n\n Tags AnswerCount \\\nPostId \n1 <c#><floating-point><type-conversion><double><... 14.0 \n\n CommentCount FavoriteCount CommunityOwnedDate ContentLicense \\\nPostId \n1 6 60.0 2012-10-31T16:42:47.213 CC BY-SA 4.0 \n\n ParentId \nPostId \n1 NaN ",
- "text/html": "<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>PostTypeId</th>\n <th>AcceptedAnswerId</th>\n <th>CreationDate</th>\n <th>Score</th>\n <th>ViewCount</th>\n <th>Body</th>\n <th>OwnerUserId</th>\n <th>LastEditorUserId</th>\n <th>LastEditorDisplayName</th>\n <th>LastEditDate</th>\n <th>Title</th>\n <th>Tags</th>\n <th>AnswerCount</th>\n <th>CommentCount</th>\n <th>FavoriteCount</th>\n <th>CommunityOwnedDate</th>\n <th>ContentLicense</th>\n <th>ParentId</th>\n </tr>\n <tr>\n <th>PostId</th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>1</th>\n <td>1</td>\n <td>7.0</td>\n <td>2008-07-31T21:42:52.667</td>\n <td>781</td>\n <td>67914.0</td>\n <td><p>I want to assign the decimal variable &quot...</td>\n <td>8.0</td>\n <td>16124033.0</td>\n <td>Rich B</td>\n <td>2022-09-08T05:07:26.033</td>\n <td>How to convert Decimal to Double in C#?</td>\n <td><c#><floating-point><type-conversion><double><...</td>\n <td>14.0</td>\n <td>6</td>\n <td>60.0</td>\n <td>2012-10-31T16:42:47.213</td>\n <td>CC BY-SA 4.0</td>\n <td>NaN</td>\n </tr>\n </tbody>\n</table>\n</div>"
- },
- "execution_count": 9,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "sample_post = post_df.head(1)\n",
- "sample_post"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "markdown",
- "source": [
- "Let's process the Body first"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": 10,
- "outputs": [],
- "source": [
- "from bs4 import BeautifulSoup\n",
- "import spacy\n",
- "import torch\n",
- "import torch.nn as nn\n",
- "import torch.nn.functional as F\n",
- "import torch.optim as optim\n",
- "from torchtext.vocab import GloVe\n",
- "\n",
- "en = spacy.load('en_core_web_sm')\n",
- "stopwords = en.Defaults.stop_words"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": 11,
- "outputs": [
- {
- "data": {
- "text/plain": "tensor([-3.6374e-02, 1.1305e-01, -2.9251e-01, 4.6058e-03, 1.1432e-01,\n 1.3817e-01, 1.8094e-01, -1.4077e-01, -2.9465e-02, 8.6996e-01,\n -2.4227e-01, 1.7903e-03, -9.0644e-02, -2.6434e-02, -1.1753e-02,\n -1.5881e-01, -3.0371e-01, 1.7912e+00, -2.6080e-01, 6.3705e-02,\n 3.3689e-02, -6.7376e-02, -1.3606e-01, 5.8075e-02, 2.3817e-01,\n -2.1051e-01, -2.0274e-01, -1.2007e-01, 1.9419e-01, 4.3345e-02,\n -1.2157e-01, -2.8792e-02, 2.0707e-01, 5.3248e-02, 1.3090e-01,\n -7.3865e-02, 8.7552e-02, -5.2587e-02, -2.5966e-01, -1.7451e-01,\n 9.2528e-02, -2.5121e-01, 1.5754e-02, 9.7943e-03, -2.0923e-01,\n -6.1129e-03, 4.2967e-03, 1.8417e-01, -4.4229e-02, 1.0786e-01,\n -7.7416e-02, 2.1915e-01, 9.1229e-02, -4.5503e-02, 6.1583e-02,\n -6.6497e-02, 4.0271e-02, -8.5584e-02, 9.0862e-02, -3.6905e-02,\n -3.1869e-02, 1.5599e-01, -1.6684e-01, 9.5459e-02, 8.6566e-03,\n 6.3764e-02, 1.6507e-01, -5.7868e-02, 1.2635e-01, 3.5084e-02,\n -1.8181e-02, 2.0929e-01, 6.1381e-03, -2.1185e-01, 2.0875e-01,\n -5.7877e-03, -1.6763e-01, -1.6657e-03, 1.3546e-01, -1.2922e-03,\n 2.5813e-02, 1.4587e-01, -6.0748e-02, 2.7971e-01, -1.3223e-01,\n 1.3441e-02, 5.1517e-01, -4.5957e-01, 7.1570e-02, 6.0031e-03,\n -1.2266e-01, 5.8546e-02, 2.6375e-02, -2.4059e-01, 1.6735e-01,\n 1.4737e-01, 3.9753e-02, 1.4721e-02, 4.8923e-03, 5.5796e-02,\n -4.4108e-02, 9.2886e-02, -4.7641e-02, 4.8820e-02, -5.5781e-02,\n -4.1948e-01, 2.4288e-01, -3.7417e-02, -1.4816e-01, 1.0308e-01,\n -6.9336e-02, -1.0844e-01, -3.7208e-02, -6.5000e-02, -4.8448e-02,\n 1.1080e-01, -7.3346e-02, -3.0539e-02, -8.7169e-02, 4.4503e-02,\n 2.0317e-01, -9.4962e-02, -3.5851e-02, 2.5206e-02, -2.0442e-01,\n 1.0963e-01, 2.9626e-01, 3.5071e-02, 1.8693e-02, -1.6769e-01,\n -2.1641e-02, 4.6062e-01, -3.1421e-02, 4.2701e-02, 1.0721e-01,\n 9.8857e-02, -4.1678e-02, -2.0927e-01, -1.5136e-01, -1.9112e-01,\n -1.0427e+00, -1.0529e-01, 1.0680e-01, -6.5143e-02, 2.9127e-02,\n -1.4307e-01, 5.1208e-02, 2.0857e-01, -2.7466e-01, -1.9018e-01,\n 1.1354e-01, -6.2476e-03, 1.4769e-01, -4.5229e-03, 3.1324e-02,\n -1.8422e-01, -1.8878e-01, 8.4901e-02, 2.4357e-01, 1.4580e-03,\n 1.5736e-01, 6.7952e-02, -2.9599e-02, -6.6300e-02, -1.1379e-01,\n -3.6832e-02, -1.5733e-01, -2.2460e-02, -1.2680e-03, 1.7554e-01,\n -9.7585e-02, 6.3587e-02, -1.9106e-01, -2.6922e-01, 1.4811e-01,\n -8.2532e-02, 3.1161e-02, 1.0939e-01, -1.3534e-01, 1.1171e-02,\n 1.3951e-01, 1.9110e-02, 1.8764e-02, -1.1597e-01, -2.3729e-01,\n 1.9230e-01, -3.1623e-01, 6.5513e-02, 1.3013e-01, 1.4497e-02,\n -3.7088e-02, 9.2073e-02, -2.3112e-01, -1.1719e-01, 2.6579e-01,\n -1.1962e-01, -2.8811e-02, -4.5259e-01, -1.5807e-01, 1.2421e-03,\n 1.0005e-01, -6.1528e-02, 9.2894e-02, 2.4100e-01, -6.6927e-02,\n -1.3903e-01, -6.5851e-02, 2.1972e-03, -9.3033e-02, 5.3871e-02,\n -3.8980e-02, 1.3120e-01, -4.9600e-02, -3.3595e-02, -6.8743e-02,\n 5.2723e-02, -1.5917e-01, 1.4971e-01, -2.5889e-01, 1.3380e-01,\n 1.1774e-01, 1.4271e-01, 2.0470e-02, 9.0111e-02, -8.0654e-02,\n 2.9188e-01, -1.5516e-01, -1.0624e-01, 1.2108e-01, -1.9307e-02,\n -1.8038e-01, -2.6928e-01, 1.1441e-01, 6.6768e-02, -2.8219e-01,\n -1.0843e-01, -1.0348e-01, 1.0993e-01, -4.2919e-01, 2.3482e-01,\n 2.0702e-01, 1.3197e-01, 2.0704e-01, 1.7429e-01, 1.2611e-01,\n -1.0745e-01, 2.4112e-01, 3.3692e-02, -2.5452e-01, -6.9537e-02,\n 1.7775e-01, -3.3938e-02, -2.2522e-02, -6.8234e-02, -1.1130e-01,\n 2.4902e-01, -1.0053e-01, -2.7356e-02, 7.4078e-02, -4.5249e-02,\n -7.9914e-02, 1.1117e-01, 2.0239e-02, 8.5573e-02, 2.5660e-02,\n -1.8129e-01, 7.2276e-02, 9.7285e-02, 4.3870e-01, -2.6918e-01,\n 1.7922e-02, -7.1145e-02, 2.9965e-02, 6.9102e-02, -8.5326e-02,\n -8.6552e-02, 1.1103e-02, 1.2541e-03, -6.9890e-02, 1.5100e-01,\n 2.1181e-02, 1.4036e-01, 1.0159e-01, 1.2323e-01, -7.2754e-02,\n -2.5326e-01, 2.0318e-01, 6.6203e-03, 1.9592e-01, -9.0636e-03,\n 2.0394e-01, -1.5663e-01, -3.1973e-01, -6.1289e-02, 3.1670e-01,\n -1.1282e-01, -1.6557e-01, -1.2395e-01, 5.8688e-02, 6.2929e-02])"
- },
- "execution_count": 11,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "class PostEmbedding(nn.Module):\n",
- "\n",
- " def __init__(self):\n",
- " super().__init__()\n",
- " self._global_vectors = GloVe(name='840B', dim=300)\n",
- "\n",
- " def forward(self, html: str, title: str, flatten=True) -> torch.tensor:\n",
- " soup = BeautifulSoup(html)\n",
- " ps = self.get_paragraphs(soup, title)\n",
- " if flatten:\n",
- " # Treat all paragraphs the same\n",
- " ps = [token for para in ps for token in para]\n",
- "\n",
- " para_emb = self.to_paragraph_embedding(ps)\n",
- "\n",
- " code = self.get_code(soup)\n",
- " return para_emb\n",
- "\n",
- " def preprocess(self, text: str) -> List[str]:\n",
- " doc = en(text.lower())\n",
- " tokens = [word.text for word in doc if not (word.is_stop or word.is_punct or word.like_num)]\n",
- " return tokens\n",
- "\n",
- " def get_paragraphs(self, soup: BeautifulSoup, title: str=None) -> List[List[str]]:\n",
- " paras = [self.preprocess(x.get_text()) for x in soup.find_all('p')]\n",
- " # If title is available add it to the paragraphs\n",
- " if title is not None:\n",
- " paras += self.preprocess(title)\n",
- " return paras\n",
- "\n",
- " def to_paragraph_embedding(self, tokens: List[str]):\n",
- " word_embeddings = self._global_vectors.get_vecs_by_tokens(tokens)\n",
- " return torch.sum(word_embeddings, dim=0) / len(tokens)\n",
- "\n",
- "\n",
- " def get_code(self, soup: BeautifulSoup) -> str:\n",
- " return \"\\n\".join([x.get_text() for x in soup.find_all('code')])\n",
- "\n",
- "\n",
- "html = sample_post['Body'].item()\n",
- "\n",
- "embedding = PostEmbedding()\n",
- "embedding(html, sample_post['Title'].item())"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "markdown",
- "source": [
- "## Extracting features from code snippets\n",
- "Since supervisor meeting on 7th November, we decided to constrain it to Python.\n",
- "This means that the `ast` library can be used, rather than RegEx for all languages."
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": 14,
- "outputs": [
- {
- "data": {
- "text/plain": " PostTypeId AcceptedAnswerId CreationDate Score \\\nPostId \n1 1 7.0 2008-07-31T21:42:52.667 781 \n2 1 31.0 2008-07-31T22:08:08.620 318 \n3 2 NaN 2008-07-31T22:17:57.883 517 \n4 1 1404.0 2008-07-31T23:40:59.743 2161 \n5 1 1248.0 2008-07-31T23:55:37.967 1629 \n... ... ... ... ... \n499996 2 NaN 2009-04-03T02:10:35.270 2 \n499997 2 NaN 2009-04-03T02:10:49.060 1 \n499998 1 799526.0 2009-04-03T02:11:16.237 4 \n499999 2 NaN 2009-04-03T02:14:04.293 5 \n500000 2 NaN 2009-04-03T02:15:39.347 1 \n\n ViewCount Body \\\nPostId \n1 67914.0 <p>I want to assign the decimal variable "... \n2 23047.0 <p>I have an absolutely positioned <code>div</... \n3 NaN <p>An explicit cast to <code>double</code> lik... \n4 757897.0 <p>Given a <code>DateTime</code> representing ... \n5 193525.0 <p>Given a specific <code>DateTime</code> valu... \n... ... ... \n499996 NaN <p>If we can assume that:</p>\\n\\n<ul>\\n<li>the... \n499997 NaN <p>Change:</p>\\n\\n<pre><code>for ansSeries in ... \n499998 3611.0 <p>Here are the first few lines of my page:</p... \n499999 NaN <p>Since, in general, there is more than one p... \n500000 NaN <p>Ugh. Short of writing your own authenticati... \n\n OwnerUserId LastEditorUserId LastEditorDisplayName \\\nPostId \n1 8.0 16124033.0 Rich B \n2 9.0 9134576.0 user14723686 \n3 9.0 5496973.0 None \n4 1.0 3524942.0 Rich B \n5 1.0 16790137.0 user2370523 \n... ... ... ... \n499996 72990.0 NaN None \n499997 9940.0 NaN None \n499998 63887.0 NaN None \n499999 15168.0 NaN None \n500000 85863.0 NaN None \n\n LastEditDate \\\nPostId \n1 2022-09-08T05:07:26.033 \n2 2021-01-29T18:46:45.963 \n3 2019-10-21T14:03:54.607 \n4 2022-07-27T22:34:36.320 \n5 2022-07-10T00:19:55.237 \n... ... \n499996 None \n499997 None \n499998 None \n499999 None \n500000 None \n\n Title \\\nPostId \n1 How to convert Decimal to Double in C#? \n2 Why did the width collapse in the percentage w... \n3 None \n4 How do I calculate someone's age based on a Da... \n5 Calculate relative time in C# \n... ... \n499996 None \n499997 None \n499998 Why can't I use session_start() in my php scri... \n499999 None \n500000 None \n\n Tags AnswerCount \\\nPostId \n1 <c#><floating-point><type-conversion><double><... 14.0 \n2 <html><css><internet-explorer-7> 7.0 \n3 None NaN \n4 <c#><.net><datetime> 71.0 \n5 <c#><datetime><time><datediff><relative-time-s... 41.0 \n... ... ... \n499996 None NaN \n499997 None NaN \n499998 <php><session><cookies><header> 2.0 \n499999 None NaN \n500000 None NaN \n\n CommentCount FavoriteCount CommunityOwnedDate ContentLicense \\\nPostId \n1 6 60.0 2012-10-31T16:42:47.213 CC BY-SA 4.0 \n2 0 13.0 None CC BY-SA 4.0 \n3 1 NaN None CC BY-SA 4.0 \n4 10 492.0 2011-08-16T19:40:43.080 CC BY-SA 4.0 \n5 3 552.0 2009-09-04T13:15:59.820 CC BY-SA 4.0 \n... ... ... ... ... \n499996 0 NaN None CC BY-SA 2.5 \n499997 0 NaN None CC BY-SA 2.5 \n499998 2 NaN None CC BY-SA 2.5 \n499999 1 NaN None CC BY-SA 2.5 \n500000 1 NaN None CC BY-SA 2.5 \n\n ParentId code_snippets \nPostId \n1 NaN decimal trans = trackBar1.Value / 5000;\\nthis.... \n2 NaN div\\ndiv\\npercentage-based width\\ndiv\\n0 width... \n3 4.0 double\\ndouble trans = (double) trackBar1.Valu... \n4 NaN DateTime \n5 NaN DateTime\\n2 hours ago\\n3 days ago\\na month ago \n... ... ... \n499996 712186.0 $round_count = 0;\\n$header_printed = false;\\n$... \n499997 712225.0 for ansSeries in notmatched:\\n\\nfor ansSeries ... \n499998 NaN <!DOCTYPE html PUBLIC \"-//W3C//DTD HTML 4.01 T... \n499999 712322.0 \n500000 712023.0 X-LIGHTTPD-send-file\\nX-sendfile\\nmod proxy scgi \n\n[500000 rows x 19 columns]",
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<th></th>\n <th></th>\n <th></th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>1</th>\n <td>1</td>\n <td>7.0</td>\n <td>2008-07-31T21:42:52.667</td>\n <td>781</td>\n <td>67914.0</td>\n <td><p>I want to assign the decimal variable &quot...</td>\n <td>8.0</td>\n <td>16124033.0</td>\n <td>Rich B</td>\n <td>2022-09-08T05:07:26.033</td>\n <td>How to convert Decimal to Double in C#?</td>\n <td><c#><floating-point><type-conversion><double><...</td>\n <td>14.0</td>\n <td>6</td>\n <td>60.0</td>\n <td>2012-10-31T16:42:47.213</td>\n <td>CC BY-SA 4.0</td>\n <td>NaN</td>\n <td>decimal trans = trackBar1.Value / 5000;\\nthis....</td>\n </tr>\n <tr>\n <th>2</th>\n <td>1</td>\n <td>31.0</td>\n <td>2008-07-31T22:08:08.620</td>\n <td>318</td>\n <td>23047.0</td>\n <td><p>I have an absolutely positioned <code>div</...</td>\n <td>9.0</td>\n <td>9134576.0</td>\n <td>user14723686</td>\n <td>2021-01-29T18:46:45.963</td>\n <td>Why did the width collapse in the percentage w...</td>\n <td><html><css><internet-explorer-7></td>\n <td>7.0</td>\n <td>0</td>\n <td>13.0</td>\n <td>None</td>\n <td>CC BY-SA 4.0</td>\n <td>NaN</td>\n <td>div\\ndiv\\npercentage-based width\\ndiv\\n0 width...</td>\n </tr>\n <tr>\n <th>3</th>\n <td>2</td>\n <td>NaN</td>\n <td>2008-07-31T22:17:57.883</td>\n <td>517</td>\n <td>NaN</td>\n <td><p>An explicit cast to <code>double</code> lik...</td>\n <td>9.0</td>\n <td>5496973.0</td>\n <td>None</td>\n <td>2019-10-21T14:03:54.607</td>\n <td>None</td>\n <td>None</td>\n <td>NaN</td>\n <td>1</td>\n <td>NaN</td>\n <td>None</td>\n <td>CC BY-SA 4.0</td>\n <td>4.0</td>\n <td>double\\ndouble trans = (double) trackBar1.Valu...</td>\n </tr>\n <tr>\n <th>4</th>\n <td>1</td>\n <td>1404.0</td>\n <td>2008-07-31T23:40:59.743</td>\n <td>2161</td>\n <td>757897.0</td>\n <td><p>Given a <code>DateTime</code> representing ...</td>\n <td>1.0</td>\n <td>3524942.0</td>\n <td>Rich B</td>\n <td>2022-07-27T22:34:36.320</td>\n <td>How do I calculate someone's age based on a Da...</td>\n <td><c#><.net><datetime></td>\n <td>71.0</td>\n <td>10</td>\n <td>492.0</td>\n <td>2011-08-16T19:40:43.080</td>\n <td>CC BY-SA 4.0</td>\n <td>NaN</td>\n <td>DateTime</td>\n </tr>\n <tr>\n <th>5</th>\n <td>1</td>\n <td>1248.0</td>\n <td>2008-07-31T23:55:37.967</td>\n <td>1629</td>\n <td>193525.0</td>\n <td><p>Given a specific <code>DateTime</code> valu...</td>\n <td>1.0</td>\n <td>16790137.0</td>\n <td>user2370523</td>\n <td>2022-07-10T00:19:55.237</td>\n <td>Calculate relative time in C#</td>\n <td><c#><datetime><time><datediff><relative-time-s...</td>\n <td>41.0</td>\n <td>3</td>\n <td>552.0</td>\n <td>2009-09-04T13:15:59.820</td>\n <td>CC BY-SA 4.0</td>\n <td>NaN</td>\n <td>DateTime\\n2 hours ago\\n3 days ago\\na month ago</td>\n </tr>\n <tr>\n <th>...</th>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n </tr>\n <tr>\n <th>499996</th>\n <td>2</td>\n <td>NaN</td>\n <td>2009-04-03T02:10:35.270</td>\n <td>2</td>\n <td>NaN</td>\n <td><p>If we can assume that:</p>\\n\\n<ul>\\n<li>the...</td>\n <td>72990.0</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>NaN</td>\n <td>0</td>\n <td>NaN</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>712186.0</td>\n <td>$round_count = 0;\\n$header_printed = false;\\n$...</td>\n </tr>\n <tr>\n <th>499997</th>\n <td>2</td>\n <td>NaN</td>\n <td>2009-04-03T02:10:49.060</td>\n <td>1</td>\n <td>NaN</td>\n <td><p>Change:</p>\\n\\n<pre><code>for ansSeries in ...</td>\n <td>9940.0</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>NaN</td>\n <td>0</td>\n <td>NaN</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>712225.0</td>\n <td>for ansSeries in notmatched:\\n\\nfor ansSeries ...</td>\n </tr>\n <tr>\n <th>499998</th>\n <td>1</td>\n <td>799526.0</td>\n <td>2009-04-03T02:11:16.237</td>\n <td>4</td>\n <td>3611.0</td>\n <td><p>Here are the first few lines of my page:</p...</td>\n <td>63887.0</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>Why can't I use session_start() in my php scri...</td>\n <td><php><session><cookies><header></td>\n <td>2.0</td>\n <td>2</td>\n <td>NaN</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>NaN</td>\n <td><!DOCTYPE html PUBLIC \"-//W3C//DTD HTML 4.01 T...</td>\n </tr>\n <tr>\n <th>499999</th>\n <td>2</td>\n <td>NaN</td>\n <td>2009-04-03T02:14:04.293</td>\n <td>5</td>\n <td>NaN</td>\n <td><p>Since, in general, there is more than one p...</td>\n <td>15168.0</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>NaN</td>\n <td>1</td>\n <td>NaN</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>712322.0</td>\n <td></td>\n </tr>\n <tr>\n <th>500000</th>\n <td>2</td>\n <td>NaN</td>\n <td>2009-04-03T02:15:39.347</td>\n <td>1</td>\n <td>NaN</td>\n <td><p>Ugh. Short of writing your own authenticati...</td>\n <td>85863.0</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>NaN</td>\n <td>1</td>\n <td>NaN</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>712023.0</td>\n <td>X-LIGHTTPD-send-file\\nX-sendfile\\nmod proxy scgi</td>\n </tr>\n </tbody>\n</table>\n<p>500000 rows × 19 columns</p>\n</div>"
- },
- "execution_count": 14,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "pe = PostEmbedding()\n",
- "post_df['code_snippets'] = post_df['Body'].apply(lambda html: pe.get_code(BeautifulSoup(html)))\n",
- "post_df"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": 15,
- "outputs": [],
- "source": [
- "import re\n",
- "\n",
- "python_class_name_pattern = r\"class ([a-zA-Z_$][a-zA-Z_$0-9]*)[:(]\"\n",
- "py_func_name_pattern = r\"def ([a-zA-Z_$][a-zA-Z_$0-9]*)\\(\"\n",
- "py_import_pattern = r\"(?m)^(?:from[ ]+(\\S+)[ ]+)?import[ ]+(\\S+)(?:[ ]+as[ ]+\\S+)?[ ]*$\"\n",
- "py_variable_names = r\"([a-zA-Z_$0-9]+)[ ]=\""
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": 16,
- "outputs": [],
- "source": [
- "def find_code_features(code_snippet: str):\n",
- " class_names = re.findall(python_class_name_pattern, code_snippet)\n",
- " func_names = re.findall(py_func_name_pattern, code_snippet)\n",
- " import_names = list(sum(re.findall(py_import_pattern, code_snippet), ()))\n",
- " var_names = re.findall(py_variable_names, code_snippet)\n",
- " # return {\n",
- " # 'class_names' : class_names,\n",
- " # 'func_names' : func_names,\n",
- " # 'import_names' : import_names,\n",
- " # 'var_names' : var_names\n",
- " # }\n",
- " return import_names\n",
- "\n",
- "post_df['import_names'] = post_df['code_snippets'].apply(find_code_features)"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": 19,
- "outputs": [
- {
- "data": {
- "text/plain": " code_snippets \\\nPostId \n326 Premature end of script headers\\n\\nimport cgi\\... \n392 from SomeOtherProduct.SomeModule import SomeCl... \n710 raw_input()\\nraw_input\\nimport sys\\nprint \"\"\"M... \n716 import msvcrt\\nanswer=msvcrt.getch()\\n \n720 #!C:\\python25\\python.exe\\nimport msvcrt\\nprint... \n... ... \n499774 import java.io.File;\\n\\npublic class Main\\n{\\n... \n499834 s=\"hello\"\\ntype(s) == type(\"\")\\n\\ndef firstEle... \n499929 for (final String code : Locale.getISOCoun... \n499948 import java.util.*;\\n\\npublic class LocaleTest... \n499949 import java.util.*;\\nimport java.util.Locale;\\... \n\n import_names \nPostId \n326 [, cgi, , MySQLdb, , MySQLdb, , cgi] \n392 [SomeOtherProduct.SomeModule, SomeClass] \n710 [, sys] \n716 [, msvcrt] \n720 [, msvcrt] \n... ... \n499774 [, java.io.File;] \n499834 [, types] \n499929 [, java.util.Locale;, , java.util.*;] \n499948 [, java.util.*;] \n499949 [, java.util.*;, , java.util.Locale;] \n\n[3287 rows x 2 columns]",
- "text/html": "<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>code_snippets</th>\n <th>import_names</th>\n </tr>\n <tr>\n <th>PostId</th>\n <th></th>\n <th></th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>326</th>\n <td>Premature end of script headers\\n\\nimport cgi\\...</td>\n <td>[, cgi, , MySQLdb, , MySQLdb, , cgi]</td>\n </tr>\n <tr>\n <th>392</th>\n <td>from SomeOtherProduct.SomeModule import SomeCl...</td>\n <td>[SomeOtherProduct.SomeModule, SomeClass]</td>\n </tr>\n <tr>\n <th>710</th>\n <td>raw_input()\\nraw_input\\nimport sys\\nprint \"\"\"M...</td>\n <td>[, sys]</td>\n </tr>\n <tr>\n <th>716</th>\n <td>import msvcrt\\nanswer=msvcrt.getch()\\n</td>\n <td>[, msvcrt]</td>\n </tr>\n <tr>\n <th>720</th>\n <td>#!C:\\python25\\python.exe\\nimport msvcrt\\nprint...</td>\n <td>[, msvcrt]</td>\n </tr>\n <tr>\n <th>...</th>\n <td>...</td>\n <td>...</td>\n </tr>\n <tr>\n <th>499774</th>\n <td>import java.io.File;\\n\\npublic class Main\\n{\\n...</td>\n <td>[, java.io.File;]</td>\n </tr>\n <tr>\n <th>499834</th>\n <td>s=\"hello\"\\ntype(s) == type(\"\")\\n\\ndef firstEle...</td>\n <td>[, types]</td>\n </tr>\n <tr>\n <th>499929</th>\n <td>for (final String code : Locale.getISOCoun...</td>\n <td>[, java.util.Locale;, , java.util.*;]</td>\n </tr>\n <tr>\n <th>499948</th>\n <td>import java.util.*;\\n\\npublic class LocaleTest...</td>\n <td>[, java.util.*;]</td>\n </tr>\n <tr>\n <th>499949</th>\n <td>import java.util.*;\\nimport java.util.Locale;\\...</td>\n <td>[, java.util.*;, , java.util.Locale;]</td>\n </tr>\n </tbody>\n</table>\n<p>3287 rows × 2 columns</p>\n</div>"
- },
- "execution_count": 19,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "post_df[['code_snippets', 'import_names']].loc[post_df['import_names'].astype(str) != '[]']"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": 18,
- "outputs": [
- {
- "data": {
- "text/plain": "code_snippets object\nimport_names object\ndtype: object"
- },
- "execution_count": 18,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "a = post_df[['code_snippets', 'import_names']]\n",
- "a.dtypes"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "markdown",
- "source": [
- "## Building the graph\n",
- "We want to build a user-expertise graph"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "outputs": [],
- "source": [
- "USER_ID = 653\n",
- "user_df.loc[USER_ID]"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "outputs": [],
- "source": [
- "questions_by_user = pd.read_sql_query(f\"SELECT * FROM Post WHERE OwnerUserId={USER_ID} AND PostTypeId=1\", db)\n",
- "questions_by_user.set_index('PostId', inplace=True)\n",
- "questions_by_user"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "outputs": [],
- "source": [
- "answers_by_user = pd.read_sql_query(f\"SELECT * FROM Post WHERE OwnerUserId={USER_ID} AND PostTypeId=2\", db)\n",
- "answers_by_user.set_index('PostId', inplace=True)\n",
- "answers_by_user"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "outputs": [],
- "source": [
- "comments_by_user = pd.read_sql_query(f\"SELECT * FROM Comment WHERE UserId={USER_ID}\", db)\n",
- "comments_by_user.set_index('CommentId', inplace=True)\n",
- "comments_by_user"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "markdown",
- "source": [
- "## Tag Embeddings"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "outputs": [],
- "source": [
- "def parse_tag_list(tag_list: str) -> List[str]:\n",
- " return tag_list[1:-1].split(\"><\")\n",
- "\n",
- "def get_parent_tags(post_id: int) -> str:\n",
- " tags = pd.read_sql_query(f\"SELECT Tags FROM Post WHERE PostId={post_id}\", db)\n",
- " return tags['Tags'].item()"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "outputs": [],
- "source": [
- "tag_frequency = {}\n",
- "\n",
- "for i, row in questions_by_user.iterrows():\n",
- " tags = parse_tag_list(row.Tags)\n",
- " for t in tags:\n",
- " if t in tag_frequency:\n",
- " tag_frequency[t] += 1\n",
- " else:\n",
- " tag_frequency[t] = 1\n",
- "\n",
- "for i, row in answers_by_user.iterrows():\n",
- " tag_list = get_parent_tags(row.ParentId)\n",
- " if tag_list is None:\n",
- " continue\n",
- " for t in parse_tag_list(tag_list):\n",
- " if t in tag_frequency:\n",
- " tag_frequency[t] += 1\n",
- " else:\n",
- " tag_frequency[t] = 1\n",
- "\n",
- "{k: v for k, v in sorted(tag_frequency.items(), key=lambda item: item[1], reverse=True)}"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "markdown",
- "source": [
- "So we can see there are many categories and for a single user; but there is a lot of variance.\n",
- "Can we create an embedding for tags which reflect similar categories?"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "markdown",
- "source": [
- "Step 1. Build list of Tag vocabulary"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "outputs": [],
- "source": [
- "tag_df.head()"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "outputs": [],
- "source": [
- "tag_df[\"TagName\"].to_csv(\"tag_vocab.csv\", index=False)"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "outputs": [],
- "source": [
- "tag_vocab = list(set(tag_df[\"TagName\"]))"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "outputs": [],
- "source": [
- "post_tags = pd.read_sql_query(f\"SELECT Tags FROM Post WHERE PostTypeId=1\", db)\n",
- "post_tags.to_csv(\"all_tags.csv\", index=False)"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "outputs": [],
- "source": [
- "post_tags = pd.read_csv(\"all_tags.csv\")"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "outputs": [],
- "source": [
- "tag_list_df = post_tags['Tags'].apply(lambda row: parse_tag_list(row))"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "outputs": [],
- "source": [
- "combinations = tag_list_df.apply(lambda row: list(itertools.combinations(row, 2)))"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "outputs": [],
- "source": [
- "combinations = combinations[combinations.astype(str) != '[]']"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "outputs": [],
- "source": [
- "tag_pairs = []\n",
- "for i in combinations:\n",
- " tag_pairs += i"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "outputs": [],
- "source": [
- "device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n",
- "device"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "outputs": [],
- "source": [
- "import random\n",
- "\n",
- "TRAIN_SIZE = 10000\n",
- "tag_pairs = random.sample(tag_pairs, TRAIN_SIZE)\n",
- "tag_pairs"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "outputs": [],
- "source": [
- "len(tag_pairs), len(tag_vocab)"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "outputs": [],
- "source": [
- "tag_to_ix = {tag: i for i, tag in enumerate(tag_vocab)}"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "outputs": [],
- "source": [
- "class TagEmbedding(nn.Module):\n",
- "\n",
- " def __init__(self, vocab_size, embedding_dim):\n",
- " super(TagEmbedding, self).__init__()\n",
- " self.embedding = nn.Embedding(vocab_size, embedding_dim)\n",
- " self.linear1 = nn.Linear(embedding_dim, 128)\n",
- " self.linear2 = nn.Linear(128, vocab_size)\n",
- "\n",
- " def forward(self, inputs):\n",
- " embeds = self.embedding(inputs).view((1, -1))\n",
- " out = F.relu(self.linear1(embeds))\n",
- " out = self.linear2(out)\n",
- " log_probs = F.log_softmax(out, dim=1)\n",
- " return log_probs"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "outputs": [],
- "source": [
- "losses = []\n",
- "loss_function = nn.NLLLoss()\n",
- "model = TagEmbedding(vocab_size=len(tag_vocab), embedding_dim=20).to(device)\n",
- "optimizer = optim.SGD(model.parameters(), lr=0.001)"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "outputs": [],
- "source": [
- "from tqdm import tqdm\n",
- "\n",
- "for epoch in range(1):\n",
- " total_loss = 0\n",
- " for tag_a, tag_b in tqdm(tag_pairs):\n",
- " tag_a_id = torch.tensor(tag_to_ix[tag_a], dtype=torch.long).to(device)\n",
- " model.zero_grad()\n",
- " log_probs = model(tag_a_id)\n",
- " loss = loss_function(log_probs.flatten(), torch.tensor(tag_to_ix[tag_b], dtype=torch.long).to(device))\n",
- " loss.backward()\n",
- " optimizer.step()\n",
- " total_loss += loss.item()\n",
- " losses.append(total_loss)\n"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "outputs": [],
- "source": [
- "embd_a = model.embedding.weight[tag_to_ix[\"python\"]]\n",
- "embd_b = model.embedding.weight[tag_to_ix[\"java\"]]"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "outputs": [],
- "source": [
- "sim = torch.nn.CosineSimilarity(dim=0)\n",
- "sim(embd_a, embd_b)"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "outputs": [],
- "source": [
- "from torch.utils.tensorboard import SummaryWriter\n",
- "writer = SummaryWriter('runs/visualisation2')"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "outputs": [],
- "source": [
- "tag_vocab"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "outputs": [],
- "source": [
- "loaded_model = torch.load(\"10mil.pt\", map_location=torch.device('cpu'))\n",
- "writer.add_embedding(loaded_model.embedding.weight,\n",
- " metadata = tag_vocab,\n",
- " tag = f'Tag embedding')"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "outputs": [],
- "source": [
- "writer.close()"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "outputs": [],
- "source": [],
- "metadata": {
- "collapsed": false
- }
- }
- ],
- "metadata": {
- "kernelspec": {
- "display_name": "Python 3",
- "language": "python",
- "name": "python3"
- },
- "language_info": {
- "codemirror_mode": {
- "name": "ipython",
- "version": 2
- },
- "file_extension": ".py",
- "mimetype": "text/x-python",
- "name": "python",
- "nbconvert_exporter": "python",
- "pygments_lexer": "ipython2",
- "version": "2.7.6"
- }
- },
- "nbformat": 4,
- "nbformat_minor": 0
-}
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "source": [
+ "# Embeddings\n",
+ "Exploration into how different embeddings can be used to represent posts."
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "outputs": [],
+ "source": [
+ "import itertools\n",
+ "import sqlite3\n",
+ "from typing import List\n",
+ "import itertools\n",
+ "import pandas as pd\n",
+ "from typing import *"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "outputs": [],
+ "source": [
+ "# Create your connection.\n",
+ "db = sqlite3.connect('../stackoverflow.db')"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "outputs": [
+ {
+ "data": {
+ "text/plain": " TagName Count\nTagId \n1 .net 323469\n2 html 1146245\n3 javascript 2426650\n4 css 771867\n5 php 1445747\n... ... ...\n158156 lost-update 1\n158157 chai-subset 1\n158159 at-spi 1\n158160 oro 0\n158161 sigsci 1\n\n[63653 rows x 2 columns]",
+ "text/html": "<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>TagName</th>\n <th>Count</th>\n </tr>\n <tr>\n <th>TagId</th>\n <th></th>\n <th></th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>1</th>\n <td>.net</td>\n <td>323469</td>\n </tr>\n <tr>\n <th>2</th>\n <td>html</td>\n <td>1146245</td>\n </tr>\n <tr>\n <th>3</th>\n <td>javascript</td>\n <td>2426650</td>\n </tr>\n <tr>\n <th>4</th>\n <td>css</td>\n <td>771867</td>\n </tr>\n <tr>\n <th>5</th>\n <td>php</td>\n <td>1445747</td>\n </tr>\n <tr>\n <th>...</th>\n <td>...</td>\n <td>...</td>\n </tr>\n <tr>\n <th>158156</th>\n <td>lost-update</td>\n <td>1</td>\n </tr>\n <tr>\n <th>158157</th>\n <td>chai-subset</td>\n <td>1</td>\n </tr>\n <tr>\n <th>158159</th>\n <td>at-spi</td>\n <td>1</td>\n </tr>\n <tr>\n <th>158160</th>\n <td>oro</td>\n <td>0</td>\n </tr>\n <tr>\n <th>158161</th>\n <td>sigsci</td>\n <td>1</td>\n </tr>\n </tbody>\n</table>\n<p>63653 rows × 2 columns</p>\n</div>"
+ },
+ "execution_count": 3,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "tag_df = pd.read_sql_query(\"SELECT * FROM Tag\", db)\n",
+ "tag_df.set_index('TagId', inplace=True)\n",
+ "tag_df"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "outputs": [
+ {
+ "data": {
+ "text/plain": " PostTypeId AcceptedAnswerId CreationDate Score \\\nPostId \n1 1 7.0 2008-07-31T21:42:52.667 781 \n2 1 31.0 2008-07-31T22:08:08.620 318 \n3 2 NaN 2008-07-31T22:17:57.883 517 \n4 1 1404.0 2008-07-31T23:40:59.743 2161 \n5 1 1248.0 2008-07-31T23:55:37.967 1629 \n... ... ... ... ... \n499996 2 NaN 2009-04-03T02:10:35.270 2 \n499997 2 NaN 2009-04-03T02:10:49.060 1 \n499998 1 799526.0 2009-04-03T02:11:16.237 4 \n499999 2 NaN 2009-04-03T02:14:04.293 5 \n500000 2 NaN 2009-04-03T02:15:39.347 1 \n\n ViewCount Body \\\nPostId \n1 67914.0 <p>I want to assign the decimal variable "... \n2 23047.0 <p>I have an absolutely positioned <code>div</... \n3 NaN <p>An explicit cast to <code>double</code> lik... \n4 757897.0 <p>Given a <code>DateTime</code> representing ... \n5 193525.0 <p>Given a specific <code>DateTime</code> valu... \n... ... ... \n499996 NaN <p>If we can assume that:</p>\\n\\n<ul>\\n<li>the... \n499997 NaN <p>Change:</p>\\n\\n<pre><code>for ansSeries in ... \n499998 3611.0 <p>Here are the first few lines of my page:</p... \n499999 NaN <p>Since, in general, there is more than one p... \n500000 NaN <p>Ugh. Short of writing your own authenticati... \n\n OwnerUserId LastEditorUserId LastEditorDisplayName \\\nPostId \n1 8.0 16124033.0 Rich B \n2 9.0 9134576.0 user14723686 \n3 9.0 5496973.0 None \n4 1.0 3524942.0 Rich B \n5 1.0 16790137.0 user2370523 \n... ... ... ... \n499996 72990.0 NaN None \n499997 9940.0 NaN None \n499998 63887.0 NaN None \n499999 15168.0 NaN None \n500000 85863.0 NaN None \n\n LastEditDate \\\nPostId \n1 2022-09-08T05:07:26.033 \n2 2021-01-29T18:46:45.963 \n3 2019-10-21T14:03:54.607 \n4 2022-07-27T22:34:36.320 \n5 2022-07-10T00:19:55.237 \n... ... \n499996 None \n499997 None \n499998 None \n499999 None \n500000 None \n\n Title \\\nPostId \n1 How to convert Decimal to Double in C#? \n2 Why did the width collapse in the percentage w... \n3 None \n4 How do I calculate someone's age based on a Da... \n5 Calculate relative time in C# \n... ... \n499996 None \n499997 None \n499998 Why can't I use session_start() in my php scri... \n499999 None \n500000 None \n\n Tags AnswerCount \\\nPostId \n1 <c#><floating-point><type-conversion><double><... 14.0 \n2 <html><css><internet-explorer-7> 7.0 \n3 None NaN \n4 <c#><.net><datetime> 71.0 \n5 <c#><datetime><time><datediff><relative-time-s... 41.0 \n... ... ... \n499996 None NaN \n499997 None NaN \n499998 <php><session><cookies><header> 2.0 \n499999 None NaN \n500000 None NaN \n\n CommentCount FavoriteCount CommunityOwnedDate ContentLicense \\\nPostId \n1 6 60.0 2012-10-31T16:42:47.213 CC BY-SA 4.0 \n2 0 13.0 None CC BY-SA 4.0 \n3 1 NaN None CC BY-SA 4.0 \n4 10 492.0 2011-08-16T19:40:43.080 CC BY-SA 4.0 \n5 3 552.0 2009-09-04T13:15:59.820 CC BY-SA 4.0 \n... ... ... ... ... \n499996 0 NaN None CC BY-SA 2.5 \n499997 0 NaN None CC BY-SA 2.5 \n499998 2 NaN None CC BY-SA 2.5 \n499999 1 NaN None CC BY-SA 2.5 \n500000 1 NaN None CC BY-SA 2.5 \n\n ParentId \nPostId \n1 NaN \n2 NaN \n3 4.0 \n4 NaN \n5 NaN \n... ... \n499996 712186.0 \n499997 712225.0 \n499998 NaN \n499999 712322.0 \n500000 712023.0 \n\n[500000 rows x 18 columns]",
+ "text/html": "<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>PostTypeId</th>\n <th>AcceptedAnswerId</th>\n <th>CreationDate</th>\n <th>Score</th>\n <th>ViewCount</th>\n <th>Body</th>\n <th>OwnerUserId</th>\n <th>LastEditorUserId</th>\n <th>LastEditorDisplayName</th>\n <th>LastEditDate</th>\n <th>Title</th>\n <th>Tags</th>\n <th>AnswerCount</th>\n <th>CommentCount</th>\n <th>FavoriteCount</th>\n <th>CommunityOwnedDate</th>\n <th>ContentLicense</th>\n <th>ParentId</th>\n </tr>\n <tr>\n <th>PostId</th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>1</th>\n <td>1</td>\n <td>7.0</td>\n <td>2008-07-31T21:42:52.667</td>\n <td>781</td>\n <td>67914.0</td>\n <td><p>I want to assign the decimal variable &quot...</td>\n <td>8.0</td>\n <td>16124033.0</td>\n <td>Rich B</td>\n <td>2022-09-08T05:07:26.033</td>\n <td>How to convert Decimal to Double in C#?</td>\n <td><c#><floating-point><type-conversion><double><...</td>\n <td>14.0</td>\n <td>6</td>\n <td>60.0</td>\n <td>2012-10-31T16:42:47.213</td>\n <td>CC BY-SA 4.0</td>\n <td>NaN</td>\n </tr>\n <tr>\n <th>2</th>\n <td>1</td>\n <td>31.0</td>\n <td>2008-07-31T22:08:08.620</td>\n <td>318</td>\n <td>23047.0</td>\n <td><p>I have an absolutely positioned <code>div</...</td>\n <td>9.0</td>\n <td>9134576.0</td>\n <td>user14723686</td>\n <td>2021-01-29T18:46:45.963</td>\n <td>Why did the width collapse in the percentage w...</td>\n <td><html><css><internet-explorer-7></td>\n <td>7.0</td>\n <td>0</td>\n <td>13.0</td>\n <td>None</td>\n <td>CC BY-SA 4.0</td>\n <td>NaN</td>\n </tr>\n <tr>\n <th>3</th>\n <td>2</td>\n <td>NaN</td>\n <td>2008-07-31T22:17:57.883</td>\n <td>517</td>\n <td>NaN</td>\n <td><p>An explicit cast to <code>double</code> lik...</td>\n <td>9.0</td>\n <td>5496973.0</td>\n <td>None</td>\n <td>2019-10-21T14:03:54.607</td>\n <td>None</td>\n <td>None</td>\n <td>NaN</td>\n <td>1</td>\n <td>NaN</td>\n <td>None</td>\n <td>CC BY-SA 4.0</td>\n <td>4.0</td>\n </tr>\n <tr>\n <th>4</th>\n <td>1</td>\n <td>1404.0</td>\n <td>2008-07-31T23:40:59.743</td>\n <td>2161</td>\n <td>757897.0</td>\n <td><p>Given a <code>DateTime</code> representing ...</td>\n <td>1.0</td>\n <td>3524942.0</td>\n <td>Rich B</td>\n <td>2022-07-27T22:34:36.320</td>\n <td>How do I calculate someone's age based on a Da...</td>\n <td><c#><.net><datetime></td>\n <td>71.0</td>\n <td>10</td>\n <td>492.0</td>\n <td>2011-08-16T19:40:43.080</td>\n <td>CC BY-SA 4.0</td>\n <td>NaN</td>\n </tr>\n <tr>\n <th>5</th>\n <td>1</td>\n <td>1248.0</td>\n <td>2008-07-31T23:55:37.967</td>\n <td>1629</td>\n <td>193525.0</td>\n <td><p>Given a specific <code>DateTime</code> valu...</td>\n <td>1.0</td>\n <td>16790137.0</td>\n <td>user2370523</td>\n <td>2022-07-10T00:19:55.237</td>\n <td>Calculate relative time in C#</td>\n <td><c#><datetime><time><datediff><relative-time-s...</td>\n <td>41.0</td>\n <td>3</td>\n <td>552.0</td>\n <td>2009-09-04T13:15:59.820</td>\n <td>CC BY-SA 4.0</td>\n <td>NaN</td>\n </tr>\n <tr>\n <th>...</th>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n </tr>\n <tr>\n <th>499996</th>\n <td>2</td>\n <td>NaN</td>\n <td>2009-04-03T02:10:35.270</td>\n <td>2</td>\n <td>NaN</td>\n <td><p>If we can assume that:</p>\\n\\n<ul>\\n<li>the...</td>\n <td>72990.0</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>NaN</td>\n <td>0</td>\n <td>NaN</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>712186.0</td>\n </tr>\n <tr>\n <th>499997</th>\n <td>2</td>\n <td>NaN</td>\n <td>2009-04-03T02:10:49.060</td>\n <td>1</td>\n <td>NaN</td>\n <td><p>Change:</p>\\n\\n<pre><code>for ansSeries in ...</td>\n <td>9940.0</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>NaN</td>\n <td>0</td>\n <td>NaN</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>712225.0</td>\n </tr>\n <tr>\n <th>499998</th>\n <td>1</td>\n <td>799526.0</td>\n <td>2009-04-03T02:11:16.237</td>\n <td>4</td>\n <td>3611.0</td>\n <td><p>Here are the first few lines of my page:</p...</td>\n <td>63887.0</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>Why can't I use session_start() in my php scri...</td>\n <td><php><session><cookies><header></td>\n <td>2.0</td>\n <td>2</td>\n <td>NaN</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>NaN</td>\n </tr>\n <tr>\n <th>499999</th>\n <td>2</td>\n <td>NaN</td>\n <td>2009-04-03T02:14:04.293</td>\n <td>5</td>\n <td>NaN</td>\n <td><p>Since, in general, there is more than one p...</td>\n <td>15168.0</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>NaN</td>\n <td>1</td>\n <td>NaN</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>712322.0</td>\n </tr>\n <tr>\n <th>500000</th>\n <td>2</td>\n <td>NaN</td>\n <td>2009-04-03T02:15:39.347</td>\n <td>1</td>\n <td>NaN</td>\n <td><p>Ugh. Short of writing your own authenticati...</td>\n <td>85863.0</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>NaN</td>\n <td>1</td>\n <td>NaN</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>712023.0</td>\n </tr>\n </tbody>\n</table>\n<p>500000 rows × 18 columns</p>\n</div>"
+ },
+ "execution_count": 4,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "POST_LIMIT = 500000\n",
+ "post_df = pd.read_sql_query(f\"SELECT * FROM Post LIMIT {POST_LIMIT}\", db)\n",
+ "post_df.set_index('PostId', inplace=True)\n",
+ "post_df"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "outputs": [
+ {
+ "data": {
+ "text/plain": " UserId Name CreationDate Class TagBased\nBadgeId \n1 3718 Teacher 2008-09-15T08:55:03.923 3 False\n2 994 Teacher 2008-09-15T08:55:03.957 3 False\n3 3893 Teacher 2008-09-15T08:55:03.957 3 False\n4 4591 Teacher 2008-09-15T08:55:03.957 3 False\n5 5196 Teacher 2008-09-15T08:55:03.957 3 False\n... ... ... ... ... ...\n499996 51452 Good Answer 2010-02-15T12:27:33.500 2 False\n499997 250648 Critic 2010-02-15T12:32:31.950 3 False\n499998 162569 Commentator 2010-02-15T12:32:32.713 3 False\n499999 116388 Popular Question 2010-02-15T12:32:32.930 3 False\n500000 267503 Tumbleweed 2010-02-15T12:32:35.007 3 False\n\n[500000 rows x 5 columns]",
+ "text/html": "<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>UserId</th>\n <th>Name</th>\n <th>CreationDate</th>\n <th>Class</th>\n <th>TagBased</th>\n </tr>\n <tr>\n <th>BadgeId</th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>1</th>\n <td>3718</td>\n <td>Teacher</td>\n <td>2008-09-15T08:55:03.923</td>\n <td>3</td>\n <td>False</td>\n </tr>\n <tr>\n <th>2</th>\n <td>994</td>\n <td>Teacher</td>\n <td>2008-09-15T08:55:03.957</td>\n <td>3</td>\n <td>False</td>\n </tr>\n <tr>\n <th>3</th>\n <td>3893</td>\n <td>Teacher</td>\n <td>2008-09-15T08:55:03.957</td>\n <td>3</td>\n <td>False</td>\n </tr>\n <tr>\n <th>4</th>\n <td>4591</td>\n <td>Teacher</td>\n <td>2008-09-15T08:55:03.957</td>\n <td>3</td>\n <td>False</td>\n </tr>\n <tr>\n <th>5</th>\n <td>5196</td>\n <td>Teacher</td>\n <td>2008-09-15T08:55:03.957</td>\n <td>3</td>\n <td>False</td>\n </tr>\n <tr>\n <th>...</th>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n </tr>\n <tr>\n <th>499996</th>\n <td>51452</td>\n <td>Good Answer</td>\n <td>2010-02-15T12:27:33.500</td>\n <td>2</td>\n <td>False</td>\n </tr>\n <tr>\n <th>499997</th>\n <td>250648</td>\n <td>Critic</td>\n <td>2010-02-15T12:32:31.950</td>\n <td>3</td>\n <td>False</td>\n </tr>\n <tr>\n <th>499998</th>\n <td>162569</td>\n <td>Commentator</td>\n <td>2010-02-15T12:32:32.713</td>\n <td>3</td>\n <td>False</td>\n </tr>\n <tr>\n <th>499999</th>\n <td>116388</td>\n <td>Popular Question</td>\n <td>2010-02-15T12:32:32.930</td>\n <td>3</td>\n <td>False</td>\n </tr>\n <tr>\n <th>500000</th>\n <td>267503</td>\n <td>Tumbleweed</td>\n <td>2010-02-15T12:32:35.007</td>\n <td>3</td>\n <td>False</td>\n </tr>\n </tbody>\n</table>\n<p>500000 rows × 5 columns</p>\n</div>"
+ },
+ "execution_count": 5,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "BADGE_LIMIT = 500000\n",
+ "badge_df = pd.read_sql_query(f\"SELECT * FROM badge LIMIT {BADGE_LIMIT}\", db)\n",
+ "badge_df.set_index('BadgeId', inplace=True)\n",
+ "badge_df"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "outputs": [
+ {
+ "data": {
+ "text/plain": " Reputation CreationDate DisplayName \\\nUserId \n-1009 1 2022-05-17T15:06:54.890 WSO2 \n-1008 1 2022-01-31T19:45:27.477 Twilio \n-1007 1 2021-09-30T18:39:12.143 AudioBubble2 \n-1006 1 2021-09-27T19:40:44.437 Intel \n-1005 1 2021-07-29T14:07:57.580 GitLab \n... ... ... ... \n 884592 31 2011-08-08T18:18:02.387 Ann \n 884593 335 2011-08-08T18:19:27.857 ymliu \n 884595 123 2011-08-08T18:20:03.193 Neil Woods \n 884597 21 2011-08-08T18:21:27.077 Nathan B \n 884599 31 2011-08-08T18:22:16.987 Quaitex \n\n LastAccessDate WebsiteUrl Location \\\nUserId \n-1009 2022-05-17T15:06:54.890 None None \n-1008 2022-01-31T19:45:27.477 None None \n-1007 2021-09-30T18:39:12.143 None None \n-1006 2021-09-27T19:40:44.437 None None \n-1005 2021-07-29T14:07:57.580 None None \n... ... ... ... \n 884592 2011-08-08T18:18:02.387 None None \n 884593 2020-04-23T00:04:46.763 None \n 884595 2021-09-08T11:14:32.143 None \n 884597 2022-09-22T20:23:45.923 None \n 884599 2011-09-01T14:16:54.883 None None \n\n AboutMe Views UpVotes \\\nUserId \n-1009 <p>WSO2 solutions give enterprises the flexibi... 0 0 \n-1008 <p>Twilio has democratized channels like voice... 0 0 \n-1007 <p>Official Q&A support for AudioBubble2</... 0 0 \n-1006 <p>A space for developers to collaborate on In... 0 0 \n-1005 <p>GitLab is the open DevOps platform, deliver... 0 0 \n... ... ... ... \n 884592 None 0 0 \n 884593 33 8 \n 884595 6 3 \n 884597 14 28 \n 884599 None 5 0 \n\n DownVotes ProfileImageUrl AccountId \nUserId \n-1009 0 None NaN \n-1008 0 None NaN \n-1007 0 None NaN \n-1006 0 None NaN \n-1005 0 None NaN \n... ... ... ... \n 884592 0 None 802774.0 \n 884593 0 https://i.stack.imgur.com/jMCNj.jpg 474725.0 \n 884595 0 None 802775.0 \n 884597 0 https://i.stack.imgur.com/CMmBO.jpg 474727.0 \n 884599 0 None 796823.0 \n\n[500000 rows x 12 columns]",
+ "text/html": "<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>Reputation</th>\n <th>CreationDate</th>\n <th>DisplayName</th>\n <th>LastAccessDate</th>\n <th>WebsiteUrl</th>\n <th>Location</th>\n <th>AboutMe</th>\n <th>Views</th>\n <th>UpVotes</th>\n <th>DownVotes</th>\n <th>ProfileImageUrl</th>\n <th>AccountId</th>\n </tr>\n <tr>\n <th>UserId</th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>-1009</th>\n <td>1</td>\n <td>2022-05-17T15:06:54.890</td>\n <td>WSO2</td>\n <td>2022-05-17T15:06:54.890</td>\n <td>None</td>\n <td>None</td>\n <td><p>WSO2 solutions give enterprises the flexibi...</td>\n <td>0</td>\n <td>0</td>\n <td>0</td>\n <td>None</td>\n <td>NaN</td>\n </tr>\n <tr>\n <th>-1008</th>\n <td>1</td>\n <td>2022-01-31T19:45:27.477</td>\n <td>Twilio</td>\n <td>2022-01-31T19:45:27.477</td>\n <td>None</td>\n <td>None</td>\n <td><p>Twilio has democratized channels like voice...</td>\n <td>0</td>\n <td>0</td>\n <td>0</td>\n <td>None</td>\n <td>NaN</td>\n </tr>\n <tr>\n <th>-1007</th>\n <td>1</td>\n <td>2021-09-30T18:39:12.143</td>\n <td>AudioBubble2</td>\n <td>2021-09-30T18:39:12.143</td>\n <td>None</td>\n <td>None</td>\n <td><p>Official Q&amp;A support for AudioBubble2</...</td>\n <td>0</td>\n <td>0</td>\n <td>0</td>\n <td>None</td>\n <td>NaN</td>\n </tr>\n <tr>\n <th>-1006</th>\n <td>1</td>\n <td>2021-09-27T19:40:44.437</td>\n <td>Intel</td>\n <td>2021-09-27T19:40:44.437</td>\n <td>None</td>\n <td>None</td>\n <td><p>A space for developers to collaborate on In...</td>\n <td>0</td>\n <td>0</td>\n <td>0</td>\n <td>None</td>\n <td>NaN</td>\n </tr>\n <tr>\n <th>-1005</th>\n <td>1</td>\n <td>2021-07-29T14:07:57.580</td>\n <td>GitLab</td>\n <td>2021-07-29T14:07:57.580</td>\n <td>None</td>\n <td>None</td>\n <td><p>GitLab is the open DevOps platform, deliver...</td>\n <td>0</td>\n <td>0</td>\n <td>0</td>\n <td>None</td>\n <td>NaN</td>\n </tr>\n <tr>\n <th>...</th>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n </tr>\n <tr>\n <th>884592</th>\n <td>31</td>\n <td>2011-08-08T18:18:02.387</td>\n <td>Ann</td>\n <td>2011-08-08T18:18:02.387</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>0</td>\n <td>0</td>\n <td>0</td>\n <td>None</td>\n <td>802774.0</td>\n </tr>\n <tr>\n <th>884593</th>\n <td>335</td>\n <td>2011-08-08T18:19:27.857</td>\n <td>ymliu</td>\n <td>2020-04-23T00:04:46.763</td>\n <td></td>\n <td>None</td>\n <td></td>\n <td>33</td>\n <td>8</td>\n <td>0</td>\n <td>https://i.stack.imgur.com/jMCNj.jpg</td>\n <td>474725.0</td>\n </tr>\n <tr>\n <th>884595</th>\n <td>123</td>\n <td>2011-08-08T18:20:03.193</td>\n <td>Neil Woods</td>\n <td>2021-09-08T11:14:32.143</td>\n <td></td>\n <td>None</td>\n <td></td>\n <td>6</td>\n <td>3</td>\n <td>0</td>\n <td>None</td>\n <td>802775.0</td>\n </tr>\n <tr>\n <th>884597</th>\n <td>21</td>\n <td>2011-08-08T18:21:27.077</td>\n <td>Nathan B</td>\n <td>2022-09-22T20:23:45.923</td>\n <td></td>\n <td>None</td>\n <td></td>\n <td>14</td>\n <td>28</td>\n <td>0</td>\n <td>https://i.stack.imgur.com/CMmBO.jpg</td>\n <td>474727.0</td>\n </tr>\n <tr>\n <th>884599</th>\n <td>31</td>\n <td>2011-08-08T18:22:16.987</td>\n <td>Quaitex</td>\n <td>2011-09-01T14:16:54.883</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>5</td>\n <td>0</td>\n <td>0</td>\n <td>None</td>\n <td>796823.0</td>\n </tr>\n </tbody>\n</table>\n<p>500000 rows × 12 columns</p>\n</div>"
+ },
+ "execution_count": 6,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "user_LIMIT = 500000\n",
+ "user_df = pd.read_sql_query(f\"SELECT * FROM user LIMIT {user_LIMIT}\", db)\n",
+ "user_df.set_index('UserId', inplace=True)\n",
+ "user_df"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "outputs": [
+ {
+ "data": {
+ "text/plain": " PostId Score Body \\\nCommentId \n1 45651 6 It will help if you give some details of which... \n2 47428 3 One of the things that make a url user-friendl... \n3 47481 0 I agree, both CodeRush and RefactorPro are vis... \n4 47373 0 Just wanted to mention that this is an excelle... \n5 47497 1 Indeed, the only way to do this is get the ser... \n... ... ... ... \n499996 1044179 0 The index is there already. How can I force or... \n499997 1047464 0 are you sure you can rewrite to a URL on anoth... \n499998 1045341 0 Not sure if I understood correctly. \\nWhere's ... \n499999 1047471 0 Is there a way to remove that selected class f... \n500000 1043743 0 I've added some XSLT that does the necessary c... \n\n CreationDate UserId ContentLicense \nCommentId \n1 2008-09-06T13:38:23.647 242.0 CC BY-SA 2.5 \n2 2008-09-06T13:51:47.843 4642.0 CC BY-SA 2.5 \n3 2008-09-06T14:15:46.897 4642.0 CC BY-SA 2.5 \n4 2008-09-06T14:30:40.217 2495.0 CC BY-SA 2.5 \n5 2008-09-06T14:42:35.303 4642.0 CC BY-SA 2.5 \n... ... ... ... \n499996 2009-06-26T05:43:11.223 87248.0 CC BY-SA 2.5 \n499997 2009-06-26T05:43:42.253 109102.0 CC BY-SA 2.5 \n499998 2009-06-26T05:46:21.890 73715.0 CC BY-SA 2.5 \n499999 2009-06-26T05:46:23.497 86038.0 CC BY-SA 2.5 \n500000 2009-06-26T05:48:48.330 18771.0 CC BY-SA 2.5 \n\n[500000 rows x 6 columns]",
+ "text/html": "<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>PostId</th>\n <th>Score</th>\n <th>Body</th>\n <th>CreationDate</th>\n <th>UserId</th>\n <th>ContentLicense</th>\n </tr>\n <tr>\n <th>CommentId</th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>1</th>\n <td>45651</td>\n <td>6</td>\n <td>It will help if you give some details of which...</td>\n <td>2008-09-06T13:38:23.647</td>\n <td>242.0</td>\n <td>CC BY-SA 2.5</td>\n </tr>\n <tr>\n <th>2</th>\n <td>47428</td>\n <td>3</td>\n <td>One of the things that make a url user-friendl...</td>\n <td>2008-09-06T13:51:47.843</td>\n <td>4642.0</td>\n <td>CC BY-SA 2.5</td>\n </tr>\n <tr>\n <th>3</th>\n <td>47481</td>\n <td>0</td>\n <td>I agree, both CodeRush and RefactorPro are vis...</td>\n <td>2008-09-06T14:15:46.897</td>\n <td>4642.0</td>\n <td>CC BY-SA 2.5</td>\n </tr>\n <tr>\n <th>4</th>\n <td>47373</td>\n <td>0</td>\n <td>Just wanted to mention that this is an excelle...</td>\n <td>2008-09-06T14:30:40.217</td>\n <td>2495.0</td>\n <td>CC BY-SA 2.5</td>\n </tr>\n <tr>\n <th>5</th>\n <td>47497</td>\n <td>1</td>\n <td>Indeed, the only way to do this is get the ser...</td>\n <td>2008-09-06T14:42:35.303</td>\n <td>4642.0</td>\n <td>CC BY-SA 2.5</td>\n </tr>\n <tr>\n <th>...</th>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n </tr>\n <tr>\n <th>499996</th>\n <td>1044179</td>\n <td>0</td>\n <td>The index is there already. How can I force or...</td>\n <td>2009-06-26T05:43:11.223</td>\n <td>87248.0</td>\n <td>CC BY-SA 2.5</td>\n </tr>\n <tr>\n <th>499997</th>\n <td>1047464</td>\n <td>0</td>\n <td>are you sure you can rewrite to a URL on anoth...</td>\n <td>2009-06-26T05:43:42.253</td>\n <td>109102.0</td>\n <td>CC BY-SA 2.5</td>\n </tr>\n <tr>\n <th>499998</th>\n <td>1045341</td>\n <td>0</td>\n <td>Not sure if I understood correctly. \\nWhere's ...</td>\n <td>2009-06-26T05:46:21.890</td>\n <td>73715.0</td>\n <td>CC BY-SA 2.5</td>\n </tr>\n <tr>\n <th>499999</th>\n <td>1047471</td>\n <td>0</td>\n <td>Is there a way to remove that selected class f...</td>\n <td>2009-06-26T05:46:23.497</td>\n <td>86038.0</td>\n <td>CC BY-SA 2.5</td>\n </tr>\n <tr>\n <th>500000</th>\n <td>1043743</td>\n <td>0</td>\n <td>I've added some XSLT that does the necessary c...</td>\n <td>2009-06-26T05:48:48.330</td>\n <td>18771.0</td>\n <td>CC BY-SA 2.5</td>\n </tr>\n </tbody>\n</table>\n<p>500000 rows × 6 columns</p>\n</div>"
+ },
+ "execution_count": 7,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "comment_LIMIT = 500000\n",
+ "comment_df = pd.read_sql_query(f\"SELECT * FROM comment LIMIT {comment_LIMIT}\", db)\n",
+ "comment_df.set_index('CommentId', inplace=True)\n",
+ "comment_df"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 8,
+ "outputs": [
+ {
+ "data": {
+ "text/plain": " PostId VoteTypeId CreationDate\nVoteId \n1 1 2 2008-07-31T00:00:00.000\n2 3 2 2008-07-31T00:00:00.000\n3 2 2 2008-07-31T00:00:00.000\n4 4 2 2008-07-31T00:00:00.000\n5 6 2 2008-07-31T00:00:00.000\n... ... ... ...\n499996 231200 2 2008-10-23T00:00:00.000\n499997 231274 2 2008-10-23T00:00:00.000\n499998 230845 5 2008-10-23T00:00:00.000\n499999 231245 2 2008-10-23T00:00:00.000\n500000 149397 2 2008-10-23T00:00:00.000\n\n[500000 rows x 3 columns]",
+ "text/html": "<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>PostId</th>\n <th>VoteTypeId</th>\n <th>CreationDate</th>\n </tr>\n <tr>\n <th>VoteId</th>\n <th></th>\n <th></th>\n <th></th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>1</th>\n <td>1</td>\n <td>2</td>\n <td>2008-07-31T00:00:00.000</td>\n </tr>\n <tr>\n <th>2</th>\n <td>3</td>\n <td>2</td>\n <td>2008-07-31T00:00:00.000</td>\n </tr>\n <tr>\n <th>3</th>\n <td>2</td>\n <td>2</td>\n <td>2008-07-31T00:00:00.000</td>\n </tr>\n <tr>\n <th>4</th>\n <td>4</td>\n <td>2</td>\n <td>2008-07-31T00:00:00.000</td>\n </tr>\n <tr>\n <th>5</th>\n <td>6</td>\n <td>2</td>\n <td>2008-07-31T00:00:00.000</td>\n </tr>\n <tr>\n <th>...</th>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n </tr>\n <tr>\n <th>499996</th>\n <td>231200</td>\n <td>2</td>\n <td>2008-10-23T00:00:00.000</td>\n </tr>\n <tr>\n <th>499997</th>\n <td>231274</td>\n <td>2</td>\n <td>2008-10-23T00:00:00.000</td>\n </tr>\n <tr>\n <th>499998</th>\n <td>230845</td>\n <td>5</td>\n <td>2008-10-23T00:00:00.000</td>\n </tr>\n <tr>\n <th>499999</th>\n <td>231245</td>\n <td>2</td>\n <td>2008-10-23T00:00:00.000</td>\n </tr>\n <tr>\n <th>500000</th>\n <td>149397</td>\n <td>2</td>\n <td>2008-10-23T00:00:00.000</td>\n </tr>\n </tbody>\n</table>\n<p>500000 rows × 3 columns</p>\n</div>"
+ },
+ "execution_count": 8,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "vote_LIMIT = 500000\n",
+ "vote_df = pd.read_sql_query(f\"SELECT * FROM vote LIMIT {vote_LIMIT}\", db)\n",
+ "vote_df.set_index('VoteId', inplace=True)\n",
+ "vote_df"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "markdown",
+ "source": [
+ "So, we want to build an embedding for the body of posts.\n",
+ "The body of posts are stored as HTML, we need to split up the text and the code snippets so we can process them separately."
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 9,
+ "outputs": [
+ {
+ "data": {
+ "text/plain": " PostTypeId AcceptedAnswerId CreationDate Score \\\nPostId \n1 1 7.0 2008-07-31T21:42:52.667 781 \n\n ViewCount Body \\\nPostId \n1 67914.0 <p>I want to assign the decimal variable "... \n\n OwnerUserId LastEditorUserId LastEditorDisplayName \\\nPostId \n1 8.0 16124033.0 Rich B \n\n LastEditDate Title \\\nPostId \n1 2022-09-08T05:07:26.033 How to convert Decimal to Double in C#? \n\n Tags AnswerCount \\\nPostId \n1 <c#><floating-point><type-conversion><double><... 14.0 \n\n CommentCount FavoriteCount CommunityOwnedDate ContentLicense \\\nPostId \n1 6 60.0 2012-10-31T16:42:47.213 CC BY-SA 4.0 \n\n ParentId \nPostId \n1 NaN ",
+ "text/html": "<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>PostTypeId</th>\n <th>AcceptedAnswerId</th>\n <th>CreationDate</th>\n <th>Score</th>\n <th>ViewCount</th>\n <th>Body</th>\n <th>OwnerUserId</th>\n <th>LastEditorUserId</th>\n <th>LastEditorDisplayName</th>\n <th>LastEditDate</th>\n <th>Title</th>\n <th>Tags</th>\n <th>AnswerCount</th>\n <th>CommentCount</th>\n <th>FavoriteCount</th>\n <th>CommunityOwnedDate</th>\n <th>ContentLicense</th>\n <th>ParentId</th>\n </tr>\n <tr>\n <th>PostId</th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>1</th>\n <td>1</td>\n <td>7.0</td>\n <td>2008-07-31T21:42:52.667</td>\n <td>781</td>\n <td>67914.0</td>\n <td><p>I want to assign the decimal variable &quot...</td>\n <td>8.0</td>\n <td>16124033.0</td>\n <td>Rich B</td>\n <td>2022-09-08T05:07:26.033</td>\n <td>How to convert Decimal to Double in C#?</td>\n <td><c#><floating-point><type-conversion><double><...</td>\n <td>14.0</td>\n <td>6</td>\n <td>60.0</td>\n <td>2012-10-31T16:42:47.213</td>\n <td>CC BY-SA 4.0</td>\n <td>NaN</td>\n </tr>\n </tbody>\n</table>\n</div>"
+ },
+ "execution_count": 9,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "sample_post = post_df.head(1)\n",
+ "sample_post"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "markdown",
+ "source": [
+ "Let's process the Body first"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 10,
+ "outputs": [],
+ "source": [
+ "from bs4 import BeautifulSoup\n",
+ "import spacy\n",
+ "import torch\n",
+ "import torch.nn as nn\n",
+ "import torch.nn.functional as F\n",
+ "import torch.optim as optim\n",
+ "from torchtext.vocab import GloVe\n",
+ "\n",
+ "en = spacy.load('en_core_web_sm')\n",
+ "stopwords = en.Defaults.stop_words"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 11,
+ "outputs": [
+ {
+ "data": {
+ "text/plain": "tensor([-3.6374e-02, 1.1305e-01, -2.9251e-01, 4.6058e-03, 1.1432e-01,\n 1.3817e-01, 1.8094e-01, -1.4077e-01, -2.9465e-02, 8.6996e-01,\n -2.4227e-01, 1.7903e-03, -9.0644e-02, -2.6434e-02, -1.1753e-02,\n -1.5881e-01, -3.0371e-01, 1.7912e+00, -2.6080e-01, 6.3705e-02,\n 3.3689e-02, -6.7376e-02, -1.3606e-01, 5.8075e-02, 2.3817e-01,\n -2.1051e-01, -2.0274e-01, -1.2007e-01, 1.9419e-01, 4.3345e-02,\n -1.2157e-01, -2.8792e-02, 2.0707e-01, 5.3248e-02, 1.3090e-01,\n -7.3865e-02, 8.7552e-02, -5.2587e-02, -2.5966e-01, -1.7451e-01,\n 9.2528e-02, -2.5121e-01, 1.5754e-02, 9.7943e-03, -2.0923e-01,\n -6.1129e-03, 4.2967e-03, 1.8417e-01, -4.4229e-02, 1.0786e-01,\n -7.7416e-02, 2.1915e-01, 9.1229e-02, -4.5503e-02, 6.1583e-02,\n -6.6497e-02, 4.0271e-02, -8.5584e-02, 9.0862e-02, -3.6905e-02,\n -3.1869e-02, 1.5599e-01, -1.6684e-01, 9.5459e-02, 8.6566e-03,\n 6.3764e-02, 1.6507e-01, -5.7868e-02, 1.2635e-01, 3.5084e-02,\n -1.8181e-02, 2.0929e-01, 6.1381e-03, -2.1185e-01, 2.0875e-01,\n -5.7877e-03, -1.6763e-01, -1.6657e-03, 1.3546e-01, -1.2922e-03,\n 2.5813e-02, 1.4587e-01, -6.0748e-02, 2.7971e-01, -1.3223e-01,\n 1.3441e-02, 5.1517e-01, -4.5957e-01, 7.1570e-02, 6.0031e-03,\n -1.2266e-01, 5.8546e-02, 2.6375e-02, -2.4059e-01, 1.6735e-01,\n 1.4737e-01, 3.9753e-02, 1.4721e-02, 4.8923e-03, 5.5796e-02,\n -4.4108e-02, 9.2886e-02, -4.7641e-02, 4.8820e-02, -5.5781e-02,\n -4.1948e-01, 2.4288e-01, -3.7417e-02, -1.4816e-01, 1.0308e-01,\n -6.9336e-02, -1.0844e-01, -3.7208e-02, -6.5000e-02, -4.8448e-02,\n 1.1080e-01, -7.3346e-02, -3.0539e-02, -8.7169e-02, 4.4503e-02,\n 2.0317e-01, -9.4962e-02, -3.5851e-02, 2.5206e-02, -2.0442e-01,\n 1.0963e-01, 2.9626e-01, 3.5071e-02, 1.8693e-02, -1.6769e-01,\n -2.1641e-02, 4.6062e-01, -3.1421e-02, 4.2701e-02, 1.0721e-01,\n 9.8857e-02, -4.1678e-02, -2.0927e-01, -1.5136e-01, -1.9112e-01,\n -1.0427e+00, -1.0529e-01, 1.0680e-01, -6.5143e-02, 2.9127e-02,\n -1.4307e-01, 5.1208e-02, 2.0857e-01, -2.7466e-01, -1.9018e-01,\n 1.1354e-01, -6.2476e-03, 1.4769e-01, -4.5229e-03, 3.1324e-02,\n -1.8422e-01, -1.8878e-01, 8.4901e-02, 2.4357e-01, 1.4580e-03,\n 1.5736e-01, 6.7952e-02, -2.9599e-02, -6.6300e-02, -1.1379e-01,\n -3.6832e-02, -1.5733e-01, -2.2460e-02, -1.2680e-03, 1.7554e-01,\n -9.7585e-02, 6.3587e-02, -1.9106e-01, -2.6922e-01, 1.4811e-01,\n -8.2532e-02, 3.1161e-02, 1.0939e-01, -1.3534e-01, 1.1171e-02,\n 1.3951e-01, 1.9110e-02, 1.8764e-02, -1.1597e-01, -2.3729e-01,\n 1.9230e-01, -3.1623e-01, 6.5513e-02, 1.3013e-01, 1.4497e-02,\n -3.7088e-02, 9.2073e-02, -2.3112e-01, -1.1719e-01, 2.6579e-01,\n -1.1962e-01, -2.8811e-02, -4.5259e-01, -1.5807e-01, 1.2421e-03,\n 1.0005e-01, -6.1528e-02, 9.2894e-02, 2.4100e-01, -6.6927e-02,\n -1.3903e-01, -6.5851e-02, 2.1972e-03, -9.3033e-02, 5.3871e-02,\n -3.8980e-02, 1.3120e-01, -4.9600e-02, -3.3595e-02, -6.8743e-02,\n 5.2723e-02, -1.5917e-01, 1.4971e-01, -2.5889e-01, 1.3380e-01,\n 1.1774e-01, 1.4271e-01, 2.0470e-02, 9.0111e-02, -8.0654e-02,\n 2.9188e-01, -1.5516e-01, -1.0624e-01, 1.2108e-01, -1.9307e-02,\n -1.8038e-01, -2.6928e-01, 1.1441e-01, 6.6768e-02, -2.8219e-01,\n -1.0843e-01, -1.0348e-01, 1.0993e-01, -4.2919e-01, 2.3482e-01,\n 2.0702e-01, 1.3197e-01, 2.0704e-01, 1.7429e-01, 1.2611e-01,\n -1.0745e-01, 2.4112e-01, 3.3692e-02, -2.5452e-01, -6.9537e-02,\n 1.7775e-01, -3.3938e-02, -2.2522e-02, -6.8234e-02, -1.1130e-01,\n 2.4902e-01, -1.0053e-01, -2.7356e-02, 7.4078e-02, -4.5249e-02,\n -7.9914e-02, 1.1117e-01, 2.0239e-02, 8.5573e-02, 2.5660e-02,\n -1.8129e-01, 7.2276e-02, 9.7285e-02, 4.3870e-01, -2.6918e-01,\n 1.7922e-02, -7.1145e-02, 2.9965e-02, 6.9102e-02, -8.5326e-02,\n -8.6552e-02, 1.1103e-02, 1.2541e-03, -6.9890e-02, 1.5100e-01,\n 2.1181e-02, 1.4036e-01, 1.0159e-01, 1.2323e-01, -7.2754e-02,\n -2.5326e-01, 2.0318e-01, 6.6203e-03, 1.9592e-01, -9.0636e-03,\n 2.0394e-01, -1.5663e-01, -3.1973e-01, -6.1289e-02, 3.1670e-01,\n -1.1282e-01, -1.6557e-01, -1.2395e-01, 5.8688e-02, 6.2929e-02])"
+ },
+ "execution_count": 11,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "class PostEmbedding(nn.Module):\n",
+ "\n",
+ " def __init__(self):\n",
+ " super().__init__()\n",
+ " self._global_vectors = GloVe(name='840B', dim=300)\n",
+ "\n",
+ " def forward(self, html: str, title: str, flatten=True) -> torch.tensor:\n",
+ " soup = BeautifulSoup(html)\n",
+ " ps = self.get_paragraphs(soup, title)\n",
+ " if flatten:\n",
+ " # Treat all paragraphs the same\n",
+ " ps = [token for para in ps for token in para]\n",
+ "\n",
+ " para_emb = self.to_paragraph_embedding(ps)\n",
+ "\n",
+ " code = self.get_code(soup)\n",
+ " return para_emb\n",
+ "\n",
+ " def preprocess(self, text: str) -> List[str]:\n",
+ " doc = en(text.lower())\n",
+ " tokens = [word.text for word in doc if not (word.is_stop or word.is_punct or word.like_num)]\n",
+ " return tokens\n",
+ "\n",
+ " def get_paragraphs(self, soup: BeautifulSoup, title: str=None) -> List[List[str]]:\n",
+ " paras = [self.preprocess(x.get_text()) for x in soup.find_all('p')]\n",
+ " # If title is available add it to the paragraphs\n",
+ " if title is not None:\n",
+ " paras += self.preprocess(title)\n",
+ " return paras\n",
+ "\n",
+ " def to_paragraph_embedding(self, tokens: List[str]):\n",
+ " word_embeddings = self._global_vectors.get_vecs_by_tokens(tokens)\n",
+ " return torch.sum(word_embeddings, dim=0) / len(tokens)\n",
+ "\n",
+ "\n",
+ " def get_code(self, soup: BeautifulSoup) -> str:\n",
+ " return \"\\n\".join([x.get_text() for x in soup.find_all('code')])\n",
+ "\n",
+ "\n",
+ "html = sample_post['Body'].item()\n",
+ "\n",
+ "embedding = PostEmbedding()\n",
+ "embedding(html, sample_post['Title'].item())"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "markdown",
+ "source": [
+ "## Extracting features from code snippets\n",
+ "Since supervisor meeting on 7th November, we decided to constrain it to Python.\n",
+ "This means that the `ast` library can be used, rather than RegEx for all languages."
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 14,
+ "outputs": [
+ {
+ "data": {
+ "text/plain": " PostTypeId AcceptedAnswerId CreationDate Score \\\nPostId \n1 1 7.0 2008-07-31T21:42:52.667 781 \n2 1 31.0 2008-07-31T22:08:08.620 318 \n3 2 NaN 2008-07-31T22:17:57.883 517 \n4 1 1404.0 2008-07-31T23:40:59.743 2161 \n5 1 1248.0 2008-07-31T23:55:37.967 1629 \n... ... ... ... ... \n499996 2 NaN 2009-04-03T02:10:35.270 2 \n499997 2 NaN 2009-04-03T02:10:49.060 1 \n499998 1 799526.0 2009-04-03T02:11:16.237 4 \n499999 2 NaN 2009-04-03T02:14:04.293 5 \n500000 2 NaN 2009-04-03T02:15:39.347 1 \n\n ViewCount Body \\\nPostId \n1 67914.0 <p>I want to assign the decimal variable "... \n2 23047.0 <p>I have an absolutely positioned <code>div</... \n3 NaN <p>An explicit cast to <code>double</code> lik... \n4 757897.0 <p>Given a <code>DateTime</code> representing ... \n5 193525.0 <p>Given a specific <code>DateTime</code> valu... \n... ... ... \n499996 NaN <p>If we can assume that:</p>\\n\\n<ul>\\n<li>the... \n499997 NaN <p>Change:</p>\\n\\n<pre><code>for ansSeries in ... \n499998 3611.0 <p>Here are the first few lines of my page:</p... \n499999 NaN <p>Since, in general, there is more than one p... \n500000 NaN <p>Ugh. Short of writing your own authenticati... \n\n OwnerUserId LastEditorUserId LastEditorDisplayName \\\nPostId \n1 8.0 16124033.0 Rich B \n2 9.0 9134576.0 user14723686 \n3 9.0 5496973.0 None \n4 1.0 3524942.0 Rich B \n5 1.0 16790137.0 user2370523 \n... ... ... ... \n499996 72990.0 NaN None \n499997 9940.0 NaN None \n499998 63887.0 NaN None \n499999 15168.0 NaN None \n500000 85863.0 NaN None \n\n LastEditDate \\\nPostId \n1 2022-09-08T05:07:26.033 \n2 2021-01-29T18:46:45.963 \n3 2019-10-21T14:03:54.607 \n4 2022-07-27T22:34:36.320 \n5 2022-07-10T00:19:55.237 \n... ... \n499996 None \n499997 None \n499998 None \n499999 None \n500000 None \n\n Title \\\nPostId \n1 How to convert Decimal to Double in C#? \n2 Why did the width collapse in the percentage w... \n3 None \n4 How do I calculate someone's age based on a Da... \n5 Calculate relative time in C# \n... ... \n499996 None \n499997 None \n499998 Why can't I use session_start() in my php scri... \n499999 None \n500000 None \n\n Tags AnswerCount \\\nPostId \n1 <c#><floating-point><type-conversion><double><... 14.0 \n2 <html><css><internet-explorer-7> 7.0 \n3 None NaN \n4 <c#><.net><datetime> 71.0 \n5 <c#><datetime><time><datediff><relative-time-s... 41.0 \n... ... ... \n499996 None NaN \n499997 None NaN \n499998 <php><session><cookies><header> 2.0 \n499999 None NaN \n500000 None NaN \n\n CommentCount FavoriteCount CommunityOwnedDate ContentLicense \\\nPostId \n1 6 60.0 2012-10-31T16:42:47.213 CC BY-SA 4.0 \n2 0 13.0 None CC BY-SA 4.0 \n3 1 NaN None CC BY-SA 4.0 \n4 10 492.0 2011-08-16T19:40:43.080 CC BY-SA 4.0 \n5 3 552.0 2009-09-04T13:15:59.820 CC BY-SA 4.0 \n... ... ... ... ... \n499996 0 NaN None CC BY-SA 2.5 \n499997 0 NaN None CC BY-SA 2.5 \n499998 2 NaN None CC BY-SA 2.5 \n499999 1 NaN None CC BY-SA 2.5 \n500000 1 NaN None CC BY-SA 2.5 \n\n ParentId code_snippets \nPostId \n1 NaN decimal trans = trackBar1.Value / 5000;\\nthis.... \n2 NaN div\\ndiv\\npercentage-based width\\ndiv\\n0 width... \n3 4.0 double\\ndouble trans = (double) trackBar1.Valu... \n4 NaN DateTime \n5 NaN DateTime\\n2 hours ago\\n3 days ago\\na month ago \n... ... ... \n499996 712186.0 $round_count = 0;\\n$header_printed = false;\\n$... \n499997 712225.0 for ansSeries in notmatched:\\n\\nfor ansSeries ... \n499998 NaN <!DOCTYPE html PUBLIC \"-//W3C//DTD HTML 4.01 T... \n499999 712322.0 \n500000 712023.0 X-LIGHTTPD-send-file\\nX-sendfile\\nmod proxy scgi \n\n[500000 rows x 19 columns]",
+ "text/html": "<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>PostTypeId</th>\n <th>AcceptedAnswerId</th>\n <th>CreationDate</th>\n <th>Score</th>\n <th>ViewCount</th>\n <th>Body</th>\n <th>OwnerUserId</th>\n <th>LastEditorUserId</th>\n <th>LastEditorDisplayName</th>\n <th>LastEditDate</th>\n <th>Title</th>\n <th>Tags</th>\n <th>AnswerCount</th>\n <th>CommentCount</th>\n <th>FavoriteCount</th>\n <th>CommunityOwnedDate</th>\n <th>ContentLicense</th>\n <th>ParentId</th>\n <th>code_snippets</th>\n </tr>\n <tr>\n <th>PostId</th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>1</th>\n <td>1</td>\n <td>7.0</td>\n <td>2008-07-31T21:42:52.667</td>\n <td>781</td>\n <td>67914.0</td>\n <td><p>I want to assign the decimal variable &quot...</td>\n <td>8.0</td>\n <td>16124033.0</td>\n <td>Rich B</td>\n <td>2022-09-08T05:07:26.033</td>\n <td>How to convert Decimal to Double in C#?</td>\n <td><c#><floating-point><type-conversion><double><...</td>\n <td>14.0</td>\n <td>6</td>\n <td>60.0</td>\n <td>2012-10-31T16:42:47.213</td>\n <td>CC BY-SA 4.0</td>\n <td>NaN</td>\n <td>decimal trans = trackBar1.Value / 5000;\\nthis....</td>\n </tr>\n <tr>\n <th>2</th>\n <td>1</td>\n <td>31.0</td>\n <td>2008-07-31T22:08:08.620</td>\n <td>318</td>\n <td>23047.0</td>\n <td><p>I have an absolutely positioned <code>div</...</td>\n <td>9.0</td>\n <td>9134576.0</td>\n <td>user14723686</td>\n <td>2021-01-29T18:46:45.963</td>\n <td>Why did the width collapse in the percentage w...</td>\n <td><html><css><internet-explorer-7></td>\n <td>7.0</td>\n <td>0</td>\n <td>13.0</td>\n <td>None</td>\n <td>CC BY-SA 4.0</td>\n <td>NaN</td>\n <td>div\\ndiv\\npercentage-based width\\ndiv\\n0 width...</td>\n </tr>\n <tr>\n <th>3</th>\n <td>2</td>\n <td>NaN</td>\n <td>2008-07-31T22:17:57.883</td>\n <td>517</td>\n <td>NaN</td>\n <td><p>An explicit cast to <code>double</code> lik...</td>\n <td>9.0</td>\n <td>5496973.0</td>\n <td>None</td>\n <td>2019-10-21T14:03:54.607</td>\n <td>None</td>\n <td>None</td>\n <td>NaN</td>\n <td>1</td>\n <td>NaN</td>\n <td>None</td>\n <td>CC BY-SA 4.0</td>\n <td>4.0</td>\n <td>double\\ndouble trans = (double) trackBar1.Valu...</td>\n </tr>\n <tr>\n <th>4</th>\n <td>1</td>\n <td>1404.0</td>\n <td>2008-07-31T23:40:59.743</td>\n <td>2161</td>\n <td>757897.0</td>\n <td><p>Given a <code>DateTime</code> representing ...</td>\n <td>1.0</td>\n <td>3524942.0</td>\n <td>Rich B</td>\n <td>2022-07-27T22:34:36.320</td>\n <td>How do I calculate someone's age based on a Da...</td>\n <td><c#><.net><datetime></td>\n <td>71.0</td>\n <td>10</td>\n <td>492.0</td>\n <td>2011-08-16T19:40:43.080</td>\n <td>CC BY-SA 4.0</td>\n <td>NaN</td>\n <td>DateTime</td>\n </tr>\n <tr>\n <th>5</th>\n <td>1</td>\n <td>1248.0</td>\n <td>2008-07-31T23:55:37.967</td>\n <td>1629</td>\n <td>193525.0</td>\n <td><p>Given a specific <code>DateTime</code> valu...</td>\n <td>1.0</td>\n <td>16790137.0</td>\n <td>user2370523</td>\n <td>2022-07-10T00:19:55.237</td>\n <td>Calculate relative time in C#</td>\n <td><c#><datetime><time><datediff><relative-time-s...</td>\n <td>41.0</td>\n <td>3</td>\n <td>552.0</td>\n <td>2009-09-04T13:15:59.820</td>\n <td>CC BY-SA 4.0</td>\n <td>NaN</td>\n <td>DateTime\\n2 hours ago\\n3 days ago\\na month ago</td>\n </tr>\n <tr>\n <th>...</th>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n </tr>\n <tr>\n <th>499996</th>\n <td>2</td>\n <td>NaN</td>\n <td>2009-04-03T02:10:35.270</td>\n <td>2</td>\n <td>NaN</td>\n <td><p>If we can assume that:</p>\\n\\n<ul>\\n<li>the...</td>\n <td>72990.0</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>NaN</td>\n <td>0</td>\n <td>NaN</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>712186.0</td>\n <td>$round_count = 0;\\n$header_printed = false;\\n$...</td>\n </tr>\n <tr>\n <th>499997</th>\n <td>2</td>\n <td>NaN</td>\n <td>2009-04-03T02:10:49.060</td>\n <td>1</td>\n <td>NaN</td>\n <td><p>Change:</p>\\n\\n<pre><code>for ansSeries in ...</td>\n <td>9940.0</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>NaN</td>\n <td>0</td>\n <td>NaN</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>712225.0</td>\n <td>for ansSeries in notmatched:\\n\\nfor ansSeries ...</td>\n </tr>\n <tr>\n <th>499998</th>\n <td>1</td>\n <td>799526.0</td>\n <td>2009-04-03T02:11:16.237</td>\n <td>4</td>\n <td>3611.0</td>\n <td><p>Here are the first few lines of my page:</p...</td>\n <td>63887.0</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>Why can't I use session_start() in my php scri...</td>\n <td><php><session><cookies><header></td>\n <td>2.0</td>\n <td>2</td>\n <td>NaN</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>NaN</td>\n <td><!DOCTYPE html PUBLIC \"-//W3C//DTD HTML 4.01 T...</td>\n </tr>\n <tr>\n <th>499999</th>\n <td>2</td>\n <td>NaN</td>\n <td>2009-04-03T02:14:04.293</td>\n <td>5</td>\n <td>NaN</td>\n <td><p>Since, in general, there is more than one p...</td>\n <td>15168.0</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>NaN</td>\n <td>1</td>\n <td>NaN</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>712322.0</td>\n <td></td>\n </tr>\n <tr>\n <th>500000</th>\n <td>2</td>\n <td>NaN</td>\n <td>2009-04-03T02:15:39.347</td>\n <td>1</td>\n <td>NaN</td>\n <td><p>Ugh. Short of writing your own authenticati...</td>\n <td>85863.0</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>NaN</td>\n <td>1</td>\n <td>NaN</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>712023.0</td>\n <td>X-LIGHTTPD-send-file\\nX-sendfile\\nmod proxy scgi</td>\n </tr>\n </tbody>\n</table>\n<p>500000 rows × 19 columns</p>\n</div>"
+ },
+ "execution_count": 14,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "pe = PostEmbedding()\n",
+ "post_df['code_snippets'] = post_df['Body'].apply(lambda html: pe.get_code(BeautifulSoup(html)))\n",
+ "post_df"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 15,
+ "outputs": [],
+ "source": [
+ "import re\n",
+ "\n",
+ "python_class_name_pattern = r\"class ([a-zA-Z_$][a-zA-Z_$0-9]*)[:(]\"\n",
+ "py_func_name_pattern = r\"def ([a-zA-Z_$][a-zA-Z_$0-9]*)\\(\"\n",
+ "py_import_pattern = r\"(?m)^(?:from[ ]+(\\S+)[ ]+)?import[ ]+(\\S+)(?:[ ]+as[ ]+\\S+)?[ ]*$\"\n",
+ "py_variable_names = r\"([a-zA-Z_$0-9]+)[ ]=\""
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 16,
+ "outputs": [],
+ "source": [
+ "def find_code_features(code_snippet: str):\n",
+ " class_names = re.findall(python_class_name_pattern, code_snippet)\n",
+ " func_names = re.findall(py_func_name_pattern, code_snippet)\n",
+ " import_names = list(sum(re.findall(py_import_pattern, code_snippet), ()))\n",
+ " var_names = re.findall(py_variable_names, code_snippet)\n",
+ " # return {\n",
+ " # 'class_names' : class_names,\n",
+ " # 'func_names' : func_names,\n",
+ " # 'import_names' : import_names,\n",
+ " # 'var_names' : var_names\n",
+ " # }\n",
+ " return import_names\n",
+ "\n",
+ "post_df['import_names'] = post_df['code_snippets'].apply(find_code_features)"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 19,
+ "outputs": [
+ {
+ "data": {
+ "text/plain": " code_snippets \\\nPostId \n326 Premature end of script headers\\n\\nimport cgi\\... \n392 from SomeOtherProduct.SomeModule import SomeCl... \n710 raw_input()\\nraw_input\\nimport sys\\nprint \"\"\"M... \n716 import msvcrt\\nanswer=msvcrt.getch()\\n \n720 #!C:\\python25\\python.exe\\nimport msvcrt\\nprint... \n... ... \n499774 import java.io.File;\\n\\npublic class Main\\n{\\n... \n499834 s=\"hello\"\\ntype(s) == type(\"\")\\n\\ndef firstEle... \n499929 for (final String code : Locale.getISOCoun... \n499948 import java.util.*;\\n\\npublic class LocaleTest... \n499949 import java.util.*;\\nimport java.util.Locale;\\... \n\n import_names \nPostId \n326 [, cgi, , MySQLdb, , MySQLdb, , cgi] \n392 [SomeOtherProduct.SomeModule, SomeClass] \n710 [, sys] \n716 [, msvcrt] \n720 [, msvcrt] \n... ... \n499774 [, java.io.File;] \n499834 [, types] \n499929 [, java.util.Locale;, , java.util.*;] \n499948 [, java.util.*;] \n499949 [, java.util.*;, , java.util.Locale;] \n\n[3287 rows x 2 columns]",
+ "text/html": "<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>code_snippets</th>\n <th>import_names</th>\n </tr>\n <tr>\n <th>PostId</th>\n <th></th>\n <th></th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>326</th>\n <td>Premature end of script headers\\n\\nimport cgi\\...</td>\n <td>[, cgi, , MySQLdb, , MySQLdb, , cgi]</td>\n </tr>\n <tr>\n <th>392</th>\n <td>from SomeOtherProduct.SomeModule import SomeCl...</td>\n <td>[SomeOtherProduct.SomeModule, SomeClass]</td>\n </tr>\n <tr>\n <th>710</th>\n <td>raw_input()\\nraw_input\\nimport sys\\nprint \"\"\"M...</td>\n <td>[, sys]</td>\n </tr>\n <tr>\n <th>716</th>\n <td>import msvcrt\\nanswer=msvcrt.getch()\\n</td>\n <td>[, msvcrt]</td>\n </tr>\n <tr>\n <th>720</th>\n <td>#!C:\\python25\\python.exe\\nimport msvcrt\\nprint...</td>\n <td>[, msvcrt]</td>\n </tr>\n <tr>\n <th>...</th>\n <td>...</td>\n <td>...</td>\n </tr>\n <tr>\n <th>499774</th>\n <td>import java.io.File;\\n\\npublic class Main\\n{\\n...</td>\n <td>[, java.io.File;]</td>\n </tr>\n <tr>\n <th>499834</th>\n <td>s=\"hello\"\\ntype(s) == type(\"\")\\n\\ndef firstEle...</td>\n <td>[, types]</td>\n </tr>\n <tr>\n <th>499929</th>\n <td>for (final String code : Locale.getISOCoun...</td>\n <td>[, java.util.Locale;, , java.util.*;]</td>\n </tr>\n <tr>\n <th>499948</th>\n <td>import java.util.*;\\n\\npublic class LocaleTest...</td>\n <td>[, java.util.*;]</td>\n </tr>\n <tr>\n <th>499949</th>\n <td>import java.util.*;\\nimport java.util.Locale;\\...</td>\n <td>[, java.util.*;, , java.util.Locale;]</td>\n </tr>\n </tbody>\n</table>\n<p>3287 rows × 2 columns</p>\n</div>"
+ },
+ "execution_count": 19,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "post_df[['code_snippets', 'import_names']].loc[post_df['import_names'].astype(str) != '[]']"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 18,
+ "outputs": [
+ {
+ "data": {
+ "text/plain": "code_snippets object\nimport_names object\ndtype: object"
+ },
+ "execution_count": 18,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "a = post_df[['code_snippets', 'import_names']]\n",
+ "a.dtypes"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "markdown",
+ "source": [
+ "## Building the graph\n",
+ "We want to build a user-expertise graph"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "outputs": [],
+ "source": [
+ "USER_ID = 653\n",
+ "user_df.loc[USER_ID]"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "outputs": [],
+ "source": [
+ "questions_by_user = pd.read_sql_query(f\"SELECT * FROM Post WHERE OwnerUserId={USER_ID} AND PostTypeId=1\", db)\n",
+ "questions_by_user.set_index('PostId', inplace=True)\n",
+ "questions_by_user"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "outputs": [],
+ "source": [
+ "answers_by_user = pd.read_sql_query(f\"SELECT * FROM Post WHERE OwnerUserId={USER_ID} AND PostTypeId=2\", db)\n",
+ "answers_by_user.set_index('PostId', inplace=True)\n",
+ "answers_by_user"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "outputs": [],
+ "source": [
+ "comments_by_user = pd.read_sql_query(f\"SELECT * FROM Comment WHERE UserId={USER_ID}\", db)\n",
+ "comments_by_user.set_index('CommentId', inplace=True)\n",
+ "comments_by_user"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "markdown",
+ "source": [
+ "## Tag Embeddings"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "outputs": [],
+ "source": [
+ "def parse_tag_list(tag_list: str) -> List[str]:\n",
+ " return tag_list[1:-1].split(\"><\")\n",
+ "\n",
+ "def get_parent_tags(post_id: int) -> str:\n",
+ " tags = pd.read_sql_query(f\"SELECT Tags FROM Post WHERE PostId={post_id}\", db)\n",
+ " return tags['Tags'].item()"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "outputs": [],
+ "source": [
+ "tag_frequency = {}\n",
+ "\n",
+ "for i, row in questions_by_user.iterrows():\n",
+ " tags = parse_tag_list(row.Tags)\n",
+ " for t in tags:\n",
+ " if t in tag_frequency:\n",
+ " tag_frequency[t] += 1\n",
+ " else:\n",
+ " tag_frequency[t] = 1\n",
+ "\n",
+ "for i, row in answers_by_user.iterrows():\n",
+ " tag_list = get_parent_tags(row.ParentId)\n",
+ " if tag_list is None:\n",
+ " continue\n",
+ " for t in parse_tag_list(tag_list):\n",
+ " if t in tag_frequency:\n",
+ " tag_frequency[t] += 1\n",
+ " else:\n",
+ " tag_frequency[t] = 1\n",
+ "\n",
+ "{k: v for k, v in sorted(tag_frequency.items(), key=lambda item: item[1], reverse=True)}"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "markdown",
+ "source": [
+ "So we can see there are many categories and for a single user; but there is a lot of variance.\n",
+ "Can we create an embedding for tags which reflect similar categories?"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "markdown",
+ "source": [
+ "Step 1. Build list of Tag vocabulary"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "outputs": [],
+ "source": [
+ "tag_df.head()"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "outputs": [],
+ "source": [
+ "tag_df[\"TagName\"].to_csv(\"tag_vocab.csv\", index=False)"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "outputs": [],
+ "source": [
+ "tag_vocab = list(set(tag_df[\"TagName\"]))"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "outputs": [],
+ "source": [
+ "post_tags = pd.read_sql_query(f\"SELECT Tags FROM Post WHERE PostTypeId=1\", db)\n",
+ "post_tags.to_csv(\"all_tags.csv\", index=False)"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "outputs": [],
+ "source": [
+ "post_tags = pd.read_csv(\"all_tags.csv\")"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "outputs": [],
+ "source": [
+ "tag_list_df = post_tags['Tags'].apply(lambda row: parse_tag_list(row))"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "outputs": [],
+ "source": [
+ "combinations = tag_list_df.apply(lambda row: list(itertools.combinations(row, 2)))"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "outputs": [],
+ "source": [
+ "combinations = combinations[combinations.astype(str) != '[]']"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "outputs": [],
+ "source": [
+ "tag_pairs = []\n",
+ "for i in combinations:\n",
+ " tag_pairs += i"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "outputs": [],
+ "source": [
+ "device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n",
+ "device"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "outputs": [],
+ "source": [
+ "import random\n",
+ "\n",
+ "TRAIN_SIZE = 10000\n",
+ "tag_pairs = random.sample(tag_pairs, TRAIN_SIZE)\n",
+ "tag_pairs"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "outputs": [],
+ "source": [
+ "len(tag_pairs), len(tag_vocab)"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "outputs": [],
+ "source": [
+ "tag_to_ix = {tag: i for i, tag in enumerate(tag_vocab)}"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "outputs": [],
+ "source": [
+ "class TagEmbedding(nn.Module):\n",
+ "\n",
+ " def __init__(self, vocab_size, embedding_dim):\n",
+ " super(TagEmbedding, self).__init__()\n",
+ " self.embedding = nn.Embedding(vocab_size, embedding_dim)\n",
+ " self.linear1 = nn.Linear(embedding_dim, 128)\n",
+ " self.linear2 = nn.Linear(128, vocab_size)\n",
+ "\n",
+ " def forward(self, inputs):\n",
+ " embeds = self.embedding(inputs).view((1, -1))\n",
+ " out = F.relu(self.linear1(embeds))\n",
+ " out = self.linear2(out)\n",
+ " log_probs = F.log_softmax(out, dim=1)\n",
+ " return log_probs"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "outputs": [],
+ "source": [
+ "losses = []\n",
+ "loss_function = nn.NLLLoss()\n",
+ "model = TagEmbedding(vocab_size=len(tag_vocab), embedding_dim=20).to(device)\n",
+ "optimizer = optim.SGD(model.parameters(), lr=0.001)"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "outputs": [],
+ "source": [
+ "from tqdm import tqdm\n",
+ "\n",
+ "for epoch in range(1):\n",
+ " total_loss = 0\n",
+ " for tag_a, tag_b in tqdm(tag_pairs):\n",
+ " tag_a_id = torch.tensor(tag_to_ix[tag_a], dtype=torch.long).to(device)\n",
+ " model.zero_grad()\n",
+ " log_probs = model(tag_a_id)\n",
+ " loss = loss_function(log_probs.flatten(), torch.tensor(tag_to_ix[tag_b], dtype=torch.long).to(device))\n",
+ " loss.backward()\n",
+ " optimizer.step()\n",
+ " total_loss += loss.item()\n",
+ " losses.append(total_loss)\n"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "outputs": [],
+ "source": [
+ "embd_a = model.embedding.weight[tag_to_ix[\"python\"]]\n",
+ "embd_b = model.embedding.weight[tag_to_ix[\"java\"]]"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "outputs": [],
+ "source": [
+ "sim = torch.nn.CosineSimilarity(dim=0)\n",
+ "sim(embd_a, embd_b)"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "outputs": [],
+ "source": [
+ "from torch.utils.tensorboard import SummaryWriter\n",
+ "writer = SummaryWriter('runs/visualisation2')"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "outputs": [],
+ "source": [
+ "tag_vocab"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "outputs": [],
+ "source": [
+ "loaded_model = torch.load(\"10mil.pt\", map_location=torch.device('cpu'))\n",
+ "writer.add_embedding(loaded_model.embedding.weight,\n",
+ " metadata = tag_vocab,\n",
+ " tag = f'Tag embedding')"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "outputs": [],
+ "source": [
+ "writer.close()"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "outputs": [],
+ "source": [],
+ "metadata": {
+ "collapsed": false
+ }
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.6"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
diff --git a/archived/pyg_construction_demo.ipynb b/archived/pyg_construction_demo.ipynb
index 5f354836bde65d42b808f37b26c64237a319513f..b0cdb2d521e223aeaf5e7fcece8f6a177acf6c19 100644
--- a/archived/pyg_construction_demo.ipynb
+++ b/archived/pyg_construction_demo.ipynb
@@ -1,487 +1,487 @@
-{
- "cells": [
- {
- "cell_type": "code",
- "execution_count": 15,
- "outputs": [],
- "source": [
- "import sqlite3\n",
- "\n",
- "import numpy as np\n",
- "import pandas as pd\n",
- "from typing import *\n",
- "import ast\n",
- "\n",
- "import torch\n",
- "from torch_geometric.data import HeteroData\n",
- "from bs4 import BeautifulSoup\n",
- "from post_embedding_builder import PostEmbedding\n",
- "import networkx as nx\n",
- "from matplotlib import pyplot as plt"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": 16,
- "outputs": [],
- "source": [
- "# Create your connection.\n",
- "db = sqlite3.connect('../stackoverflow.db')"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": 17,
- "outputs": [],
- "source": [
- "user_id = 13009"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": 18,
- "outputs": [
- {
- "data": {
- "text/plain": " PostTypeId AcceptedAnswerId CreationDate Score \\\nPostId \n269676 1 NaN 2008-11-06T18:06:13.213 10 \n1046474 1 1046522.0 2009-06-25T22:04:16.890 5 \n2970045 1 2974177.0 2010-06-03T21:52:14.793 6 \n3712445 1 3712645.0 2010-09-14T20:04:19.940 1 \n5538814 1 5539724.0 2011-04-04T13:00:53.620 0 \n... ... ... ... ... \n36922532 1 36922586.0 2016-04-28T18:18:49.007 6 \n40749339 1 40749648.0 2016-11-22T18:42:04.867 1 \n41616578 1 41623932.0 2017-01-12T15:10:45.340 2 \n44933724 1 44950763.0 2017-07-05T18:40:48.800 0 \n45238835 1 45239952.0 2017-07-21T13:23:56.527 4 \n\n ViewCount Body \\\nPostId \n269676 7250 <p>I want to make my Python library working wi... \n1046474 12418 <p>How do I run this command with subprocess?<... \n2970045 7850 <p>I have a python web application that needs ... \n3712445 405 <p>Say I have text 'C:\\somedir\\test.log' and I... \n5538814 631 <p>I have multiple Django apps, and I have som... \n... ... ... \n36922532 3284 <p>I know there must be a way to do this. But... \n40749339 1271 <p>Say I have a script like this:</p>\\n\\n<pre>... \n41616578 24094 <p>I'm trying to run code like this:</p>\\n\\n<p... \n44933724 388 <p>I've been running fine on Django 1.7. I'm ... \n45238835 1191 <p>I'm on Django 1.9, Python 3.6. I made this... \n\n OwnerUserId LastEditorUserId LastEditorDisplayName \\\nPostId \n269676 13009 13009.0 Greg \n1046474 13009 13009.0 None \n2970045 13009 13009.0 None \n3712445 13009 13009.0 None \n5538814 13009 13009.0 None \n... ... ... ... \n36922532 13009 NaN None \n40749339 13009 NaN None \n41616578 13009 NaN None \n44933724 13009 NaN None \n45238835 13009 NaN None \n\n LastEditDate \\\nPostId \n269676 2008-11-10T15:12:18.133 \n1046474 2009-06-25T22:21:41.520 \n2970045 2010-06-03T22:11:27.260 \n3712445 2010-09-14T20:18:32.083 \n5538814 2011-04-04T13:15:37.903 \n... ... \n36922532 None \n40749339 None \n41616578 None \n44933724 None \n45238835 None \n\n Title \\\nPostId \n269676 How can I Cause a Deadlock in MySQL for Testin... \n1046474 Python - Subprocess - How to call a Piped comm... \n2970045 Python - Launch a Long Running Process from a ... \n3712445 Python Regular Expression Question \n5538814 Django - non app specific models.py? \n... ... \n36922532 Python functools.partial - How to apply it to ... \n40749339 Python subprocess - check exit codes of forked... \n41616578 Psycopg copy_expert method - How to use properly \n44933724 Django 1.11 upgrade - object has no attribute ... \n45238835 Django failing migration - Cannot query \"peter... \n\n Tags AnswerCount \\\nPostId \n269676 <python><mysql><database><deadlock> 5 \n1046474 <python><subprocess><pipe><echo><popen> 2 \n2970045 <python><windows><winapi><popen><long-running-... 4 \n3712445 <python><regex> 4 \n5538814 <python><django><django-models> 3 \n... ... ... \n36922532 <python><static-methods><python-decorators><fu... 3 \n40749339 <python><subprocess><fork> 1 \n41616578 <python><postgresql><psycopg2><psycopg> 2 \n44933724 <python><django><django-models><django-authent... 1 \n45238835 <python><django><migration><django-migrations> 1 \n\n CommentCount FavoriteCount CommunityOwnedDate ContentLicense \\\nPostId \n269676 0 3.0 None CC BY-SA 2.5 \n1046474 2 3.0 None CC BY-SA 2.5 \n2970045 2 6.0 None CC BY-SA 2.5 \n3712445 0 1.0 None CC BY-SA 2.5 \n5538814 0 1.0 None CC BY-SA 2.5 \n... ... ... ... ... \n36922532 0 1.0 None CC BY-SA 3.0 \n40749339 0 NaN None CC BY-SA 3.0 \n41616578 2 NaN None CC BY-SA 3.0 \n44933724 2 0.0 None CC BY-SA 3.0 \n45238835 4 NaN None CC BY-SA 3.0 \n\n ParentId \nPostId \n269676 None \n1046474 None \n2970045 None \n3712445 None \n5538814 None \n... ... \n36922532 None \n40749339 None \n41616578 None \n44933724 None \n45238835 None \n\n[105 rows x 18 columns]",
- "text/html": "<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>PostTypeId</th>\n <th>AcceptedAnswerId</th>\n <th>CreationDate</th>\n <th>Score</th>\n <th>ViewCount</th>\n <th>Body</th>\n <th>OwnerUserId</th>\n <th>LastEditorUserId</th>\n <th>LastEditorDisplayName</th>\n <th>LastEditDate</th>\n <th>Title</th>\n <th>Tags</th>\n <th>AnswerCount</th>\n <th>CommentCount</th>\n <th>FavoriteCount</th>\n <th>CommunityOwnedDate</th>\n <th>ContentLicense</th>\n <th>ParentId</th>\n </tr>\n <tr>\n <th>PostId</th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>269676</th>\n <td>1</td>\n <td>NaN</td>\n <td>2008-11-06T18:06:13.213</td>\n <td>10</td>\n <td>7250</td>\n <td><p>I want to make my Python library working wi...</td>\n <td>13009</td>\n <td>13009.0</td>\n <td>Greg</td>\n <td>2008-11-10T15:12:18.133</td>\n <td>How can I Cause a Deadlock in MySQL for Testin...</td>\n <td><python><mysql><database><deadlock></td>\n <td>5</td>\n <td>0</td>\n <td>3.0</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>None</td>\n </tr>\n <tr>\n <th>1046474</th>\n <td>1</td>\n <td>1046522.0</td>\n <td>2009-06-25T22:04:16.890</td>\n <td>5</td>\n <td>12418</td>\n <td><p>How do I run this command with subprocess?<...</td>\n <td>13009</td>\n <td>13009.0</td>\n <td>None</td>\n <td>2009-06-25T22:21:41.520</td>\n <td>Python - Subprocess - How to call a Piped comm...</td>\n <td><python><subprocess><pipe><echo><popen></td>\n <td>2</td>\n <td>2</td>\n <td>3.0</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>None</td>\n </tr>\n <tr>\n <th>2970045</th>\n <td>1</td>\n <td>2974177.0</td>\n <td>2010-06-03T21:52:14.793</td>\n <td>6</td>\n <td>7850</td>\n <td><p>I have a python web application that needs ...</td>\n <td>13009</td>\n <td>13009.0</td>\n <td>None</td>\n <td>2010-06-03T22:11:27.260</td>\n <td>Python - Launch a Long Running Process from a ...</td>\n <td><python><windows><winapi><popen><long-running-...</td>\n <td>4</td>\n <td>2</td>\n <td>6.0</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>None</td>\n </tr>\n <tr>\n <th>3712445</th>\n <td>1</td>\n <td>3712645.0</td>\n <td>2010-09-14T20:04:19.940</td>\n <td>1</td>\n <td>405</td>\n <td><p>Say I have text 'C:\\somedir\\test.log' and I...</td>\n <td>13009</td>\n <td>13009.0</td>\n <td>None</td>\n <td>2010-09-14T20:18:32.083</td>\n <td>Python Regular Expression Question</td>\n <td><python><regex></td>\n <td>4</td>\n <td>0</td>\n <td>1.0</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>None</td>\n </tr>\n <tr>\n <th>5538814</th>\n <td>1</td>\n <td>5539724.0</td>\n <td>2011-04-04T13:00:53.620</td>\n <td>0</td>\n <td>631</td>\n <td><p>I have multiple Django apps, and I have som...</td>\n <td>13009</td>\n <td>13009.0</td>\n <td>None</td>\n <td>2011-04-04T13:15:37.903</td>\n <td>Django - non app specific models.py?</td>\n <td><python><django><django-models></td>\n <td>3</td>\n <td>0</td>\n <td>1.0</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>None</td>\n </tr>\n <tr>\n <th>...</th>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n </tr>\n <tr>\n <th>36922532</th>\n <td>1</td>\n <td>36922586.0</td>\n <td>2016-04-28T18:18:49.007</td>\n <td>6</td>\n <td>3284</td>\n <td><p>I know there must be a way to do this. But...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>Python functools.partial - How to apply it to ...</td>\n <td><python><static-methods><python-decorators><fu...</td>\n <td>3</td>\n <td>0</td>\n <td>1.0</td>\n <td>None</td>\n <td>CC BY-SA 3.0</td>\n <td>None</td>\n </tr>\n <tr>\n <th>40749339</th>\n <td>1</td>\n <td>40749648.0</td>\n <td>2016-11-22T18:42:04.867</td>\n <td>1</td>\n <td>1271</td>\n <td><p>Say I have a script like this:</p>\\n\\n<pre>...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>Python subprocess - check exit codes of forked...</td>\n <td><python><subprocess><fork></td>\n <td>1</td>\n <td>0</td>\n <td>NaN</td>\n <td>None</td>\n <td>CC BY-SA 3.0</td>\n <td>None</td>\n </tr>\n <tr>\n <th>41616578</th>\n <td>1</td>\n <td>41623932.0</td>\n <td>2017-01-12T15:10:45.340</td>\n <td>2</td>\n <td>24094</td>\n <td><p>I'm trying to run code like this:</p>\\n\\n<p...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>Psycopg copy_expert method - How to use properly</td>\n <td><python><postgresql><psycopg2><psycopg></td>\n <td>2</td>\n <td>2</td>\n <td>NaN</td>\n <td>None</td>\n <td>CC BY-SA 3.0</td>\n <td>None</td>\n </tr>\n <tr>\n <th>44933724</th>\n <td>1</td>\n <td>44950763.0</td>\n <td>2017-07-05T18:40:48.800</td>\n <td>0</td>\n <td>388</td>\n <td><p>I've been running fine on Django 1.7. I'm ...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>Django 1.11 upgrade - object has no attribute ...</td>\n <td><python><django><django-models><django-authent...</td>\n <td>1</td>\n <td>2</td>\n <td>0.0</td>\n <td>None</td>\n <td>CC BY-SA 3.0</td>\n <td>None</td>\n </tr>\n <tr>\n <th>45238835</th>\n <td>1</td>\n <td>45239952.0</td>\n <td>2017-07-21T13:23:56.527</td>\n <td>4</td>\n <td>1191</td>\n <td><p>I'm on Django 1.9, Python 3.6. I made this...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>Django failing migration - Cannot query \"peter...</td>\n <td><python><django><migration><django-migrations></td>\n <td>1</td>\n <td>4</td>\n <td>NaN</td>\n <td>None</td>\n <td>CC BY-SA 3.0</td>\n <td>None</td>\n </tr>\n </tbody>\n</table>\n<p>105 rows × 18 columns</p>\n</div>"
- },
- "execution_count": 18,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "questions_df = pd.read_sql_query(f\"\"\"\n",
- " SELECT *\n",
- " FROM Post\n",
- " WHERE Tags LIKE '%python%' AND (PostTypeId = 1) AND ((LastEditorUserId = {user_id}) OR (OwnerUserId = {user_id}))\n",
- "\"\"\", db)\n",
- "questions_df.set_index('PostId', inplace=True)\n",
- "questions_df"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": 19,
- "outputs": [
- {
- "data": {
- "text/plain": " Tags PostTypeId \\\nPostId \n6930808 <python><django><django-models><django-admin><... 2 \n45239952 <python><django><migration><django-migrations> 2 \n74335 <python><amazon> 2 \n94627 <python><user-interface><api> 2 \n109724 <python><excel><xlwt><pyexcelerator> 2 \n207065 <python><ajax><screen-scraping><beautifulsoup> 2 \n207074 <python><soap><soap-client> 2 \n224014 <python><ruby><perl><text-parsing> 2 \n273994 <python><programming-languages><python-3.x> 2 \n302681 <python><simplehttpserver><embeddedwebserver> 2 \n338929 <python><indentation> 2 \n350913 <python><django><django-forms> 2 \n368859 <python><unicode><ascii><encode> 2 \n562280 <python><excel-2007> 2 \n1166398 <python><newline><word-wrap> 2 \n1423207 <python><frameworks><cgi><nearlyfreespeech> 2 \n2726298 <python><xlwt><xlrd> 2 \n2883732 <python><sql-server><pyodbc><django-pyodbc> 2 \n2973884 <python><windows><winapi><popen><long-running-... 2 \n2974177 <python><windows><winapi><popen><long-running-... 2 \n3322769 <python><sqlalchemy><orm> 2 \n3364841 <python><session><timeout><sqlalchemy> 2 \n3740202 <python><dictionary> 2 \n5037673 <python><serialization><pickle><inverted-index> 2 \n5486539 <python><django><django-models><django-admin> 2 \n5501441 <python><xpath><elementtree> 2 \n5517355 <python><django><django-models> 2 \n5539724 <python><django><django-models> 2 \n5912867 <python><apache><mod-wsgi><redhat><setuptools> 2 \n5979034 <python><django><django-models><django-admin> 2 \n6507098 <python><django><django-models><django-admin><... 2 \n7097823 <python><django><django-models> 2 \n7323959 <python><popen><subprocess> 2 \n7999028 <python><linux><multithreading><threadpool> 2 \n10047815 <python><django> 2 \n21140430 <python><jdbc><jpype><jaydebeapi> 2 \n23349566 <python><rpy2> 2 \n29807514 <python><curl><python-requests> 2 \n31146549 <python><flask><uwsgi> 2 \n31164662 <python><mongodb><uwsgi><mlab><pymongo-3.x> 2 \n31482430 <python><nginx><flask><memcached><uwsgi> 2 \n31516660 <python><memcached><libmemcached><pylibmc> 2 \n32564909 <python><computer-vision><scikit-image><canny-... 2 \n33284974 <python><oracle><macos><cx-oracle><osx-elcapitan> 2 \n35611090 <python><django><celery><django-celery> 2 \n36922809 <python><static-methods><python-decorators><fu... 2 \n37288365 <python><python-2.7><unicode><subprocess> 2 \n41470962 <python><logging> 2 \n44950763 <python><django><django-models><django-authent... 2 \n\n AcceptedAnswerId CreationDate Score ViewCount \\\nPostId \n6930808 None 2011-08-03T17:45:24.243 1 None \n45239952 None 2017-07-21T14:15:08.280 6 None \n74335 None 2008-09-16T16:40:08.743 2 None \n94627 None 2008-09-18T17:21:42.810 3 None \n109724 None 2008-09-20T23:10:13.863 2 None \n207065 None 2008-10-16T00:58:10.813 0 None \n207074 None 2008-10-16T01:00:24.800 1 None \n224014 None 2008-10-22T00:03:23.323 5 None \n273994 None 2008-11-07T23:29:44.590 4 None \n302681 None 2008-11-19T17:21:06.677 0 None \n338929 None 2008-12-03T22:10:01.007 16 None \n350913 None 2008-12-08T21:12:56.517 40 None \n368859 None 2008-12-15T16:10:11.413 -3 None \n562280 None 2009-02-18T18:28:00.267 0 None \n1166398 None 2009-07-22T16:09:25.197 1 None \n1423207 None 2009-09-14T18:34:18.867 2 None \n2726298 None 2010-04-28T01:30:54.397 263 None \n2883732 None 2010-05-21T16:21:27.240 10 None \n2973884 None 2010-06-04T12:04:23.607 1 None \n2974177 None 2010-06-04T12:41:24.323 7 None \n3322769 None 2010-07-23T22:11:43.417 42 None \n3364841 None 2010-07-29T16:31:24.073 56 None \n3740202 None 2010-09-18T02:57:15.853 7 None \n5037673 None 2011-02-18T04:37:27.133 0 None \n5486539 None 2011-03-30T12:54:01.637 0 None \n5501441 None 2011-03-31T14:27:50.847 56 None \n5517355 None 2011-04-01T18:30:31.930 3 None \n5539724 None 2011-04-04T14:12:30.027 1 None \n5912867 None 2011-05-06T14:28:54.537 0 None \n5979034 None 2011-05-12T13:51:05.513 -2 None \n6507098 None 2011-06-28T13:20:49.480 0 None \n7097823 None 2011-08-17T18:45:06.860 3 None \n7323959 None 2011-09-06T17:45:14.537 8 None \n7999028 None 2011-11-03T17:09:51.260 0 None \n10047815 None 2012-04-06T18:46:30.720 1 None \n21140430 None 2014-01-15T14:44:21.213 5 None \n23349566 None 2014-04-28T19:26:54.797 0 None \n29807514 None 2015-04-22T19:53:07.763 0 None \n31146549 None 2015-06-30T19:13:43.577 7 None \n31164662 None 2015-07-01T14:47:11.400 14 None \n31482430 None 2015-07-17T18:30:07.053 0 None \n31516660 None 2015-07-20T12:34:33.923 0 None \n32564909 None 2015-09-14T12:31:51.097 1 None \n33284974 None 2015-10-22T15:36:24.507 0 None \n35611090 None 2016-02-24T19:18:36.617 0 None \n36922809 None 2016-04-28T18:32:49.863 2 None \n37288365 None 2016-05-18T00:36:59.467 1 None \n41470962 None 2017-01-04T18:37:01.457 1 None \n44950763 None 2017-07-06T13:45:42.037 2 None \n\n Body OwnerUserId \\\nPostId \n6930808 <p>Well, here's a work around since I can't fi... 13009 \n45239952 <p>Looks like I just needed to get User the sa... 13009 \n74335 <p>pyaws seems to be the best one out there. ... 13009 \n94627 <p><a href=\"http://pythoncard.sourceforge.net/... 13009 \n109724 <p>Found example here: <a href=\"http://www.ans... 13009 \n207065 <p>This seems like it's a pretty common proble... 13009 \n207074 <p>As I suggested <a href=\"https://stackoverfl... 13009 \n224014 <p><a href=\"http://pyparsing.wikispaces.com/\" ... 13009 \n273994 <p>Wouldn't VB6 to VB.net be the biggest examp... 13009 \n302681 <p>I made this one. <a href=\"http://www.blend... 13009 \n338929 <p>Python includes a script for the opposite (... 13009 \n350913 <p>I went ahead and answered my own question. ... 13009 \n368859 <p>This seems to work:</p>\\n\\n<pre><code>'add ... 13009 \n562280 <p>May I humbly suggest my site; <a href=\"http... 13009 \n1166398 <p>It looks like it doesn't support that. Thi... 13009 \n1423207 <p>I got web.py to work on nearly free speech ... 13009 \n2726298 <p>Here's some sample code I used recently to ... 13009 \n2883732 <p>Sorry, I asked too soon, <a href=\"http://co... 13009 \n2973884 <p>This almost works (<a href=\"http://docs.pyt... 13009 \n2974177 <p>Ok, I finally figured this out! This seems... 13009 \n3322769 <p>Ok I found it after further searching:</p>\\... 13009 \n3364841 <p>Whenever you create a new session in your c... 13009 \n3740202 <p>What you're describing in your edit is how ... 13009 \n5037673 <p>There's the other pickle library you could ... 13009 \n5486539 <p>What I did to fix this is I dropped every t... 13009 \n5501441 <p>Turns out I needed to say <code>target.find... 13009 \n5517355 <p>Ahh, found it in another SO answer. Weird ... 13009 \n5539724 <p><code>__init__.py</code> in my project's di... 13009 \n5912867 <p>Oh well, instead of fooling with that, I to... 13009 \n5979034 <p><a href=\"http://www.answermysearches.com/fi... 13009 \n6507098 <p>Ok, as a workaround I ended up defining a <... 13009 \n7097823 <p>get_or_create sounds busted to me. I'm jus... 13009 \n7323959 <p>Ok, I'm not sure why but this seems to work... 13009 \n7999028 <p>Actually this does seem to be working. I s... 13009 \n10047815 <p><a href=\"https://stackoverflow.com/question... 13009 \n21140430 <p>Ok, thanks to eltabo and Juan Mellado I fig... 13009 \n23349566 <p>So I was trying to install this on a networ... 13009 \n29807514 <p>Ok, changing to response.content fixed it. ... 13009 \n31146549 <p>Ok, @ipinak was on the right track. It loo... 13009 \n31164662 <p>I fixed it for myself by downgrading from p... 13009 \n31482430 <p>This isn't a great answer, but I ended up u... 13009 \n31516660 <p>As far as I can tell it seems to work fine ... 13009 \n32564909 <p>So the issue was with the canny function re... 13009 \n33284974 <p>I think I fixed it. Basically everything i... 13009 \n35611090 <p>After tooling around for a while and trying... 13009 \n36922809 <p>There's probably a smarter way to do it but... 13009 \n37288365 <p>Wow, this was the weirdest issue ever but I... 13009 \n41470962 <p>Here's what I ended up going with. But I'm... 13009 \n44950763 <p>As @adrien mentioned in the comment, that w... 13009 \n\n LastEditorUserId LastEditorDisplayName LastEditDate \\\nPostId \n6930808 13009.0 None 2011-08-04T11:44:00.257 \n45239952 13009.0 None 2017-07-21T19:13:22.417 \n74335 NaN None None \n94627 216356.0 None 2012-08-09T19:47:56.843 \n109724 NaN None None \n207065 NaN None None \n207074 -1.0 None 2017-05-23T12:34:59.060 \n224014 NaN None None \n273994 NaN None None \n302681 NaN None None \n338929 NaN None None \n350913 NaN None None \n368859 NaN None None \n562280 NaN None None \n1166398 NaN None None \n1423207 NaN None None \n2726298 3801587.0 None 2019-11-04T13:44:52.230 \n2883732 NaN None None \n2973884 NaN None None \n2974177 726378.0 None 2017-07-28T04:22:46.813 \n3322769 NaN None None \n3364841 972208.0 None 2012-03-18T02:57:48.600 \n3740202 NaN None None \n5037673 NaN None None \n5486539 NaN None None \n5501441 3820025.0 None 2018-12-19T15:54:38.900 \n5517355 NaN None None \n5539724 NaN None None \n5912867 NaN None None \n5979034 NaN None None \n6507098 NaN None None \n7097823 NaN None None \n7323959 NaN None None \n7999028 NaN None None \n10047815 -1.0 None 2017-05-23T10:34:38.073 \n21140430 NaN None None \n23349566 NaN None None \n29807514 NaN None None \n31146549 NaN None None \n31164662 NaN None None \n31482430 NaN None None \n31516660 NaN None None \n32564909 NaN None None \n33284974 NaN None None \n35611090 NaN None None \n36922809 NaN None None \n37288365 -1.0 None 2017-05-23T11:44:09.133 \n41470962 NaN None None \n44950763 NaN None None \n\n Title AnswerCount CommentCount FavoriteCount \\\nPostId \n6930808 None None 0 None \n45239952 None None 0 None \n74335 None None 0 None \n94627 None None 1 None \n109724 None None 1 None \n207065 None None 1 None \n207074 None None 0 None \n224014 None None 0 None \n273994 None None 3 None \n302681 None None 0 None \n338929 None None 2 None \n350913 None None 2 None \n368859 None None 5 None \n562280 None None 0 None \n1166398 None None 0 None \n1423207 None None 0 None \n2726298 None None 5 None \n2883732 None None 0 None \n2973884 None None 0 None \n2974177 None None 3 None \n3322769 None None 2 None \n3364841 None None 4 None \n3740202 None None 0 None \n5037673 None None 0 None \n5486539 None None 0 None \n5501441 None None 2 None \n5517355 None None 0 None \n5539724 None None 0 None \n5912867 None None 0 None \n5979034 None None 0 None \n6507098 None None 0 None \n7097823 None None 0 None \n7323959 None None 2 None \n7999028 None None 0 None \n10047815 None None 2 None \n21140430 None None 3 None \n23349566 None None 0 None \n29807514 None None 3 None \n31146549 None None 0 None \n31164662 None None 3 None \n31482430 None None 0 None \n31516660 None None 0 None \n32564909 None None 1 None \n33284974 None None 0 None \n35611090 None None 0 None \n36922809 None None 0 None \n37288365 None None 1 None \n41470962 None None 0 None \n44950763 None None 0 None \n\n CommunityOwnedDate ContentLicense ParentId \nPostId \n6930808 None CC BY-SA 3.0 6913166 \n45239952 None CC BY-SA 3.0 45238835 \n74335 None CC BY-SA 2.5 48884 \n94627 None CC BY-SA 3.0 93930 \n109724 None CC BY-SA 2.5 108134 \n207065 None CC BY-SA 2.5 206855 \n207074 None CC BY-SA 2.5 206154 \n224014 None CC BY-SA 2.5 223866 \n273994 None CC BY-SA 2.5 273524 \n302681 None CC BY-SA 2.5 302615 \n338929 None CC BY-SA 2.5 338767 \n350913 2008-12-08T21:12:56.517 CC BY-SA 2.5 350799 \n368859 None CC BY-SA 2.5 368805 \n562280 None CC BY-SA 2.5 556967 \n1166398 None CC BY-SA 2.5 1166317 \n1423207 None CC BY-SA 2.5 1423041 \n2726298 None CC BY-SA 4.0 2725852 \n2883732 None CC BY-SA 2.5 2883722 \n2973884 None CC BY-SA 2.5 2970045 \n2974177 None CC BY-SA 3.0 2970045 \n3322769 None CC BY-SA 2.5 3322337 \n3364841 None CC BY-SA 3.0 3360951 \n3740202 None CC BY-SA 2.5 3738381 \n5037673 None CC BY-SA 2.5 5037432 \n5486539 None CC BY-SA 2.5 5486018 \n5501441 None CC BY-SA 4.0 5501118 \n5517355 None CC BY-SA 2.5 5517314 \n5539724 None CC BY-SA 2.5 5538814 \n5912867 None CC BY-SA 3.0 5912701 \n5979034 None CC BY-SA 3.0 5486018 \n6507098 None CC BY-SA 3.0 6497882 \n7097823 None CC BY-SA 3.0 7097475 \n7323959 None CC BY-SA 3.0 7323859 \n7999028 None CC BY-SA 3.0 7998850 \n10047815 None CC BY-SA 3.0 10047387 \n21140430 2014-01-15T14:44:21.213 CC BY-SA 3.0 21027904 \n23349566 None CC BY-SA 3.0 23346270 \n29807514 None CC BY-SA 3.0 29807249 \n31146549 None CC BY-SA 3.0 31146007 \n31164662 None CC BY-SA 3.0 31030307 \n31482430 None CC BY-SA 3.0 31478409 \n31516660 None CC BY-SA 3.0 31482138 \n32564909 None CC BY-SA 3.0 32529149 \n33284974 None CC BY-SA 3.0 33259671 \n35611090 None CC BY-SA 3.0 35603707 \n36922809 None CC BY-SA 3.0 36922532 \n37288365 None CC BY-SA 3.0 37245595 \n41470962 None CC BY-SA 3.0 41467032 \n44950763 None CC BY-SA 3.0 44933724 ",
- "text/html": "<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>Tags</th>\n <th>PostTypeId</th>\n <th>AcceptedAnswerId</th>\n <th>CreationDate</th>\n <th>Score</th>\n <th>ViewCount</th>\n <th>Body</th>\n <th>OwnerUserId</th>\n <th>LastEditorUserId</th>\n <th>LastEditorDisplayName</th>\n <th>LastEditDate</th>\n <th>Title</th>\n <th>AnswerCount</th>\n <th>CommentCount</th>\n <th>FavoriteCount</th>\n <th>CommunityOwnedDate</th>\n <th>ContentLicense</th>\n <th>ParentId</th>\n </tr>\n <tr>\n <th>PostId</th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>6930808</th>\n <td><python><django><django-models><django-admin><...</td>\n <td>2</td>\n <td>None</td>\n <td>2011-08-03T17:45:24.243</td>\n <td>1</td>\n <td>None</td>\n <td><p>Well, here's a work around since I can't fi...</td>\n <td>13009</td>\n <td>13009.0</td>\n <td>None</td>\n <td>2011-08-04T11:44:00.257</td>\n <td>None</td>\n <td>None</td>\n <td>0</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 3.0</td>\n <td>6913166</td>\n </tr>\n <tr>\n <th>45239952</th>\n <td><python><django><migration><django-migrations></td>\n <td>2</td>\n <td>None</td>\n <td>2017-07-21T14:15:08.280</td>\n <td>6</td>\n <td>None</td>\n <td><p>Looks like I just needed to get User the sa...</td>\n <td>13009</td>\n <td>13009.0</td>\n <td>None</td>\n <td>2017-07-21T19:13:22.417</td>\n <td>None</td>\n <td>None</td>\n <td>0</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 3.0</td>\n <td>45238835</td>\n </tr>\n <tr>\n <th>74335</th>\n <td><python><amazon></td>\n <td>2</td>\n <td>None</td>\n <td>2008-09-16T16:40:08.743</td>\n <td>2</td>\n <td>None</td>\n <td><p>pyaws seems to be the best one out there. ...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>0</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>48884</td>\n </tr>\n <tr>\n <th>94627</th>\n <td><python><user-interface><api></td>\n <td>2</td>\n <td>None</td>\n <td>2008-09-18T17:21:42.810</td>\n <td>3</td>\n <td>None</td>\n <td><p><a href=\"http://pythoncard.sourceforge.net/...</td>\n <td>13009</td>\n <td>216356.0</td>\n <td>None</td>\n <td>2012-08-09T19:47:56.843</td>\n <td>None</td>\n <td>None</td>\n <td>1</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 3.0</td>\n <td>93930</td>\n </tr>\n <tr>\n <th>109724</th>\n <td><python><excel><xlwt><pyexcelerator></td>\n <td>2</td>\n <td>None</td>\n <td>2008-09-20T23:10:13.863</td>\n <td>2</td>\n <td>None</td>\n <td><p>Found example here: <a href=\"http://www.ans...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>1</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>108134</td>\n </tr>\n <tr>\n <th>207065</th>\n <td><python><ajax><screen-scraping><beautifulsoup></td>\n <td>2</td>\n <td>None</td>\n <td>2008-10-16T00:58:10.813</td>\n <td>0</td>\n <td>None</td>\n <td><p>This seems like it's a pretty common proble...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>1</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>206855</td>\n </tr>\n <tr>\n <th>207074</th>\n <td><python><soap><soap-client></td>\n <td>2</td>\n <td>None</td>\n <td>2008-10-16T01:00:24.800</td>\n <td>1</td>\n <td>None</td>\n <td><p>As I suggested <a href=\"https://stackoverfl...</td>\n <td>13009</td>\n <td>-1.0</td>\n <td>None</td>\n <td>2017-05-23T12:34:59.060</td>\n <td>None</td>\n <td>None</td>\n <td>0</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>206154</td>\n </tr>\n <tr>\n <th>224014</th>\n <td><python><ruby><perl><text-parsing></td>\n <td>2</td>\n <td>None</td>\n <td>2008-10-22T00:03:23.323</td>\n <td>5</td>\n <td>None</td>\n <td><p><a href=\"http://pyparsing.wikispaces.com/\" ...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>0</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>223866</td>\n </tr>\n <tr>\n <th>273994</th>\n <td><python><programming-languages><python-3.x></td>\n <td>2</td>\n <td>None</td>\n <td>2008-11-07T23:29:44.590</td>\n <td>4</td>\n <td>None</td>\n <td><p>Wouldn't VB6 to VB.net be the biggest examp...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>3</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>273524</td>\n </tr>\n <tr>\n <th>302681</th>\n <td><python><simplehttpserver><embeddedwebserver></td>\n <td>2</td>\n <td>None</td>\n <td>2008-11-19T17:21:06.677</td>\n <td>0</td>\n <td>None</td>\n <td><p>I made this one. <a href=\"http://www.blend...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>0</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>302615</td>\n </tr>\n <tr>\n <th>338929</th>\n <td><python><indentation></td>\n <td>2</td>\n <td>None</td>\n <td>2008-12-03T22:10:01.007</td>\n <td>16</td>\n <td>None</td>\n <td><p>Python includes a script for the opposite (...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>2</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>338767</td>\n </tr>\n <tr>\n <th>350913</th>\n <td><python><django><django-forms></td>\n <td>2</td>\n <td>None</td>\n <td>2008-12-08T21:12:56.517</td>\n <td>40</td>\n <td>None</td>\n <td><p>I went ahead and answered my own question. ...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>2</td>\n <td>None</td>\n <td>2008-12-08T21:12:56.517</td>\n <td>CC BY-SA 2.5</td>\n <td>350799</td>\n </tr>\n <tr>\n <th>368859</th>\n <td><python><unicode><ascii><encode></td>\n <td>2</td>\n <td>None</td>\n <td>2008-12-15T16:10:11.413</td>\n <td>-3</td>\n <td>None</td>\n <td><p>This seems to work:</p>\\n\\n<pre><code>'add ...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>5</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>368805</td>\n </tr>\n <tr>\n <th>562280</th>\n <td><python><excel-2007></td>\n <td>2</td>\n <td>None</td>\n <td>2009-02-18T18:28:00.267</td>\n <td>0</td>\n <td>None</td>\n <td><p>May I humbly suggest my site; <a href=\"http...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>0</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>556967</td>\n </tr>\n <tr>\n <th>1166398</th>\n <td><python><newline><word-wrap></td>\n <td>2</td>\n <td>None</td>\n <td>2009-07-22T16:09:25.197</td>\n <td>1</td>\n <td>None</td>\n <td><p>It looks like it doesn't support that. Thi...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>0</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>1166317</td>\n </tr>\n <tr>\n <th>1423207</th>\n <td><python><frameworks><cgi><nearlyfreespeech></td>\n <td>2</td>\n <td>None</td>\n <td>2009-09-14T18:34:18.867</td>\n <td>2</td>\n <td>None</td>\n <td><p>I got web.py to work on nearly free speech ...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>0</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>1423041</td>\n </tr>\n <tr>\n <th>2726298</th>\n <td><python><xlwt><xlrd></td>\n <td>2</td>\n <td>None</td>\n <td>2010-04-28T01:30:54.397</td>\n <td>263</td>\n <td>None</td>\n <td><p>Here's some sample code I used recently to ...</td>\n <td>13009</td>\n <td>3801587.0</td>\n <td>None</td>\n <td>2019-11-04T13:44:52.230</td>\n <td>None</td>\n <td>None</td>\n <td>5</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 4.0</td>\n <td>2725852</td>\n </tr>\n <tr>\n <th>2883732</th>\n <td><python><sql-server><pyodbc><django-pyodbc></td>\n <td>2</td>\n <td>None</td>\n <td>2010-05-21T16:21:27.240</td>\n <td>10</td>\n <td>None</td>\n <td><p>Sorry, I asked too soon, <a href=\"http://co...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>0</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>2883722</td>\n </tr>\n <tr>\n <th>2973884</th>\n <td><python><windows><winapi><popen><long-running-...</td>\n <td>2</td>\n <td>None</td>\n <td>2010-06-04T12:04:23.607</td>\n <td>1</td>\n <td>None</td>\n <td><p>This almost works (<a href=\"http://docs.pyt...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>0</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>2970045</td>\n </tr>\n <tr>\n <th>2974177</th>\n <td><python><windows><winapi><popen><long-running-...</td>\n <td>2</td>\n <td>None</td>\n <td>2010-06-04T12:41:24.323</td>\n <td>7</td>\n <td>None</td>\n <td><p>Ok, I finally figured this out! This seems...</td>\n <td>13009</td>\n <td>726378.0</td>\n <td>None</td>\n <td>2017-07-28T04:22:46.813</td>\n <td>None</td>\n <td>None</td>\n <td>3</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 3.0</td>\n <td>2970045</td>\n </tr>\n <tr>\n <th>3322769</th>\n <td><python><sqlalchemy><orm></td>\n <td>2</td>\n <td>None</td>\n <td>2010-07-23T22:11:43.417</td>\n <td>42</td>\n <td>None</td>\n <td><p>Ok I found it after further searching:</p>\\...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>2</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>3322337</td>\n </tr>\n <tr>\n <th>3364841</th>\n <td><python><session><timeout><sqlalchemy></td>\n <td>2</td>\n <td>None</td>\n <td>2010-07-29T16:31:24.073</td>\n <td>56</td>\n <td>None</td>\n <td><p>Whenever you create a new session in your c...</td>\n <td>13009</td>\n <td>972208.0</td>\n <td>None</td>\n <td>2012-03-18T02:57:48.600</td>\n <td>None</td>\n <td>None</td>\n <td>4</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 3.0</td>\n <td>3360951</td>\n </tr>\n <tr>\n <th>3740202</th>\n <td><python><dictionary></td>\n <td>2</td>\n <td>None</td>\n <td>2010-09-18T02:57:15.853</td>\n <td>7</td>\n <td>None</td>\n <td><p>What you're describing in your edit is how ...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>0</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>3738381</td>\n </tr>\n <tr>\n <th>5037673</th>\n <td><python><serialization><pickle><inverted-index></td>\n <td>2</td>\n <td>None</td>\n <td>2011-02-18T04:37:27.133</td>\n <td>0</td>\n <td>None</td>\n <td><p>There's the other pickle library you could ...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>0</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>5037432</td>\n </tr>\n <tr>\n <th>5486539</th>\n <td><python><django><django-models><django-admin></td>\n <td>2</td>\n <td>None</td>\n <td>2011-03-30T12:54:01.637</td>\n <td>0</td>\n <td>None</td>\n <td><p>What I did to fix this is I dropped every t...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>0</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>5486018</td>\n </tr>\n <tr>\n <th>5501441</th>\n <td><python><xpath><elementtree></td>\n <td>2</td>\n <td>None</td>\n <td>2011-03-31T14:27:50.847</td>\n <td>56</td>\n <td>None</td>\n <td><p>Turns out I needed to say <code>target.find...</td>\n <td>13009</td>\n <td>3820025.0</td>\n <td>None</td>\n <td>2018-12-19T15:54:38.900</td>\n <td>None</td>\n <td>None</td>\n <td>2</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 4.0</td>\n <td>5501118</td>\n </tr>\n <tr>\n <th>5517355</th>\n <td><python><django><django-models></td>\n <td>2</td>\n <td>None</td>\n <td>2011-04-01T18:30:31.930</td>\n <td>3</td>\n <td>None</td>\n <td><p>Ahh, found it in another SO answer. Weird ...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>0</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>5517314</td>\n </tr>\n <tr>\n <th>5539724</th>\n <td><python><django><django-models></td>\n <td>2</td>\n <td>None</td>\n <td>2011-04-04T14:12:30.027</td>\n <td>1</td>\n <td>None</td>\n <td><p><code>__init__.py</code> in my project's di...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>0</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>5538814</td>\n </tr>\n <tr>\n <th>5912867</th>\n <td><python><apache><mod-wsgi><redhat><setuptools></td>\n <td>2</td>\n <td>None</td>\n <td>2011-05-06T14:28:54.537</td>\n <td>0</td>\n <td>None</td>\n <td><p>Oh well, instead of fooling with that, I to...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>0</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 3.0</td>\n <td>5912701</td>\n </tr>\n <tr>\n <th>5979034</th>\n <td><python><django><django-models><django-admin></td>\n <td>2</td>\n <td>None</td>\n <td>2011-05-12T13:51:05.513</td>\n <td>-2</td>\n <td>None</td>\n <td><p><a href=\"http://www.answermysearches.com/fi...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>0</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 3.0</td>\n <td>5486018</td>\n </tr>\n <tr>\n <th>6507098</th>\n <td><python><django><django-models><django-admin><...</td>\n <td>2</td>\n <td>None</td>\n <td>2011-06-28T13:20:49.480</td>\n <td>0</td>\n <td>None</td>\n <td><p>Ok, as a workaround I ended up defining a <...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>0</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 3.0</td>\n <td>6497882</td>\n </tr>\n <tr>\n <th>7097823</th>\n <td><python><django><django-models></td>\n <td>2</td>\n <td>None</td>\n <td>2011-08-17T18:45:06.860</td>\n <td>3</td>\n <td>None</td>\n <td><p>get_or_create sounds busted to me. I'm jus...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>0</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 3.0</td>\n <td>7097475</td>\n </tr>\n <tr>\n <th>7323959</th>\n <td><python><popen><subprocess></td>\n <td>2</td>\n <td>None</td>\n <td>2011-09-06T17:45:14.537</td>\n <td>8</td>\n <td>None</td>\n <td><p>Ok, I'm not sure why but this seems to work...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>2</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 3.0</td>\n <td>7323859</td>\n </tr>\n <tr>\n <th>7999028</th>\n <td><python><linux><multithreading><threadpool></td>\n <td>2</td>\n <td>None</td>\n <td>2011-11-03T17:09:51.260</td>\n <td>0</td>\n <td>None</td>\n <td><p>Actually this does seem to be working. I s...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>0</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 3.0</td>\n <td>7998850</td>\n </tr>\n <tr>\n <th>10047815</th>\n <td><python><django></td>\n <td>2</td>\n <td>None</td>\n <td>2012-04-06T18:46:30.720</td>\n <td>1</td>\n <td>None</td>\n <td><p><a href=\"https://stackoverflow.com/question...</td>\n <td>13009</td>\n <td>-1.0</td>\n <td>None</td>\n <td>2017-05-23T10:34:38.073</td>\n <td>None</td>\n <td>None</td>\n <td>2</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 3.0</td>\n <td>10047387</td>\n </tr>\n <tr>\n <th>21140430</th>\n <td><python><jdbc><jpype><jaydebeapi></td>\n <td>2</td>\n <td>None</td>\n <td>2014-01-15T14:44:21.213</td>\n <td>5</td>\n <td>None</td>\n <td><p>Ok, thanks to eltabo and Juan Mellado I fig...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>3</td>\n <td>None</td>\n <td>2014-01-15T14:44:21.213</td>\n <td>CC BY-SA 3.0</td>\n <td>21027904</td>\n </tr>\n <tr>\n <th>23349566</th>\n <td><python><rpy2></td>\n <td>2</td>\n <td>None</td>\n <td>2014-04-28T19:26:54.797</td>\n <td>0</td>\n <td>None</td>\n <td><p>So I was trying to install this on a networ...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>0</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 3.0</td>\n <td>23346270</td>\n </tr>\n <tr>\n <th>29807514</th>\n <td><python><curl><python-requests></td>\n <td>2</td>\n <td>None</td>\n <td>2015-04-22T19:53:07.763</td>\n <td>0</td>\n <td>None</td>\n <td><p>Ok, changing to response.content fixed it. ...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>3</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 3.0</td>\n <td>29807249</td>\n </tr>\n <tr>\n <th>31146549</th>\n <td><python><flask><uwsgi></td>\n <td>2</td>\n <td>None</td>\n <td>2015-06-30T19:13:43.577</td>\n <td>7</td>\n <td>None</td>\n <td><p>Ok, @ipinak was on the right track. It loo...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>0</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 3.0</td>\n <td>31146007</td>\n </tr>\n <tr>\n <th>31164662</th>\n <td><python><mongodb><uwsgi><mlab><pymongo-3.x></td>\n <td>2</td>\n <td>None</td>\n <td>2015-07-01T14:47:11.400</td>\n <td>14</td>\n <td>None</td>\n <td><p>I fixed it for myself by downgrading from p...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>3</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 3.0</td>\n <td>31030307</td>\n </tr>\n <tr>\n <th>31482430</th>\n <td><python><nginx><flask><memcached><uwsgi></td>\n <td>2</td>\n <td>None</td>\n <td>2015-07-17T18:30:07.053</td>\n <td>0</td>\n <td>None</td>\n <td><p>This isn't a great answer, but I ended up u...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>0</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 3.0</td>\n <td>31478409</td>\n </tr>\n <tr>\n <th>31516660</th>\n <td><python><memcached><libmemcached><pylibmc></td>\n <td>2</td>\n <td>None</td>\n <td>2015-07-20T12:34:33.923</td>\n <td>0</td>\n <td>None</td>\n <td><p>As far as I can tell it seems to work fine ...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>0</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 3.0</td>\n <td>31482138</td>\n </tr>\n <tr>\n <th>32564909</th>\n <td><python><computer-vision><scikit-image><canny-...</td>\n <td>2</td>\n <td>None</td>\n <td>2015-09-14T12:31:51.097</td>\n <td>1</td>\n <td>None</td>\n <td><p>So the issue was with the canny function re...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>1</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 3.0</td>\n <td>32529149</td>\n </tr>\n <tr>\n <th>33284974</th>\n <td><python><oracle><macos><cx-oracle><osx-elcapitan></td>\n <td>2</td>\n <td>None</td>\n <td>2015-10-22T15:36:24.507</td>\n <td>0</td>\n <td>None</td>\n <td><p>I think I fixed it. Basically everything i...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>0</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 3.0</td>\n <td>33259671</td>\n </tr>\n <tr>\n <th>35611090</th>\n <td><python><django><celery><django-celery></td>\n <td>2</td>\n <td>None</td>\n <td>2016-02-24T19:18:36.617</td>\n <td>0</td>\n <td>None</td>\n <td><p>After tooling around for a while and trying...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>0</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 3.0</td>\n <td>35603707</td>\n </tr>\n <tr>\n <th>36922809</th>\n <td><python><static-methods><python-decorators><fu...</td>\n <td>2</td>\n <td>None</td>\n <td>2016-04-28T18:32:49.863</td>\n <td>2</td>\n <td>None</td>\n <td><p>There's probably a smarter way to do it but...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>0</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 3.0</td>\n <td>36922532</td>\n </tr>\n <tr>\n <th>37288365</th>\n <td><python><python-2.7><unicode><subprocess></td>\n <td>2</td>\n <td>None</td>\n <td>2016-05-18T00:36:59.467</td>\n <td>1</td>\n <td>None</td>\n <td><p>Wow, this was the weirdest issue ever but I...</td>\n <td>13009</td>\n <td>-1.0</td>\n <td>None</td>\n <td>2017-05-23T11:44:09.133</td>\n <td>None</td>\n <td>None</td>\n <td>1</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 3.0</td>\n <td>37245595</td>\n </tr>\n <tr>\n <th>41470962</th>\n <td><python><logging></td>\n <td>2</td>\n <td>None</td>\n <td>2017-01-04T18:37:01.457</td>\n <td>1</td>\n <td>None</td>\n <td><p>Here's what I ended up going with. But I'm...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>0</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 3.0</td>\n <td>41467032</td>\n </tr>\n <tr>\n <th>44950763</th>\n <td><python><django><django-models><django-authent...</td>\n <td>2</td>\n <td>None</td>\n <td>2017-07-06T13:45:42.037</td>\n <td>2</td>\n <td>None</td>\n <td><p>As @adrien mentioned in the comment, that w...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>0</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 3.0</td>\n <td>44933724</td>\n </tr>\n </tbody>\n</table>\n</div>"
- },
- "execution_count": 19,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "answers_df = pd.read_sql_query(f\"\"\"\n",
- " SELECT A.Tags, B.*\n",
- " FROM Post A\n",
- " INNER JOIN Post B ON (B.ParentId = A.PostId) AND (B.ParentId IS NOT NULL)\n",
- " WHERE A.Tags LIKE '%python%' AND (B.PostTypeId = 2) AND ((B.LastEditorUserId = {user_id}) OR (B.OwnerUserId = {user_id}))\n",
- "\"\"\", db)\n",
- "answers_df = answers_df.loc[:,~answers_df.columns.duplicated()].copy()\n",
- "answers_df.set_index('PostId', inplace=True)\n",
- "answers_df"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": 20,
- "outputs": [
- {
- "data": {
- "text/plain": " Tags PostId Score \\\nCommentId \n857928 <python><subprocess><pipe><echo><popen> 1046474 0 \n1513319 <python><django><forms><django-forms> 1640204 0 \n3029786 <python><windows><winapi><popen><long-running-... 2970045 0 \n3421734 <python><permissions><authorization><decorator... 3302844 0 \n6330991 <python><django><django-models><decimal><scien... 5566121 0 \n6331285 <python><django><django-models><decimal><scien... 5566121 0 \n6774887 <python><database><migration><django-south> 5833418 4 \n8234046 <python><django><django-models><django-admin><... 6913166 1 \n8234115 <python><string-formatting><number-formatting>... 6913532 32 \n8235637 <python><django><django-models><django-admin><... 6913166 0 \n8239108 <python><django><django-models><django-admin><... 6913166 0 \n8257824 <python><django><django-models><django-admin><... 6913166 0 \n8499177 <python><django><django-models> 7097475 0 \n10657798 <python><excel><xlwt> 8590741 0 \n10796244 <python><excel><xlwt> 8590741 0 \n11245320 <python> 8976324 0 \n11245634 <python> 8976324 0 \n12490216 <python><django><django-models><django-admin> 9806936 0 \n32554534 <python><django><django-forms><django-admin><d... 19807757 0 \n32567053 <python><django><django-forms><django-admin><d... 19807757 0 \n36034593 <python><numpy> 23497706 0 \n36034937 <python><numpy> 23497706 0 \n36041765 <python><numpy> 23500754 0 \n47738961 <python><python-requests> 29775247 1 \n47742802 <python><curl><python-requests> 29807249 0 \n47743040 <python><curl><python-requests> 29807249 0 \n48550940 <python><matplotlib> 30223161 0 \n48551405 <python><matplotlib> 30223161 0 \n50303593 <python><mongodb><uwsgi><mlab><pymongo-3.x> 31030307 2 \n50336702 <python><mongodb><uwsgi><mlab><pymongo-3.x> 31030307 1 \n50337057 <python><mongodb><uwsgi><mlab><pymongo-3.x> 31030307 0 \n50376360 <python><mongodb><uwsgi><mlab><pymongo-3.x> 31030307 0 \n54364203 <python><oracle><macos><cx-oracle><osx-elcapitan> 33259671 0 \n58665815 <python><django><celery><django-celery> 35486011 0 \n58894206 <python><django><celery><django-celery> 35603707 0 \n62020862 <python><python-2.7><unicode><subprocess> 37245595 0 \n62020942 <python><python-2.7><unicode><subprocess> 37245595 0 \n62020963 <python><python-2.7><unicode><subprocess> 37245595 0 \n68427097 <python><mocking><generator><python-unittest><... 40595679 0 \n70139817 <python><logging> 41467032 0 \n70435606 <python><postgresql><psycopg2><psycopg> 41616578 0 \n76846070 <python><django><django-models><django-authent... 44933724 0 \n77453798 <python><django><migration><django-migrations> 45238835 0 \n77456266 <python><django><migration><django-migrations> 45238835 0 \n80880518 <python><django> 46960782 0 \n\n Body \\\nCommentId \n857928 Yes, it runs from the windows dos console. \n1513319 lemonad, this would be at form creation time, ... \n3029786 Here are a few windows API commands that look ... \n3421734 I don't think I want to use anything built-in.... \n6330991 4.08E+13 has two decimal places, I'm allowing ... \n6331285 I followed those instructions. I've tried all... \n6774887 It's going to be pretty critical data, and hon... \n8234046 I'm thinking I need to make a custom model fie... \n8234115 nah, not at all. I wanted to separate this int... \n8235637 I'm not seeing much action on this thread. I ... \n8239108 I'm not seeing much action on the Django users... \n8257824 IRC seems to be down. No luck there either. \n8499177 @agf. I don't understand what the resolution ... \n10657798 Well, after playing around, the first number i... \n10796244 Thanks for the answers everyone. If anyone is... \n11245320 @Cameron, so you're saying something I import ... \n11245634 Thanks everyone. If anyone wants to post this... \n12490216 @jpic, that's interesting but it's probably ov... \n32554534 I'm coming across the exact same problem. I a... \n32567053 I put an updated question more inline with wha... \n36034593 I was thinking I could reference just the firs... \n36034937 hmm, I can access the first column with array[... \n36041765 hmm, I just ran the code from your answer. Do... \n47738961 @sigmavirus24, that's right I don't want to lo... \n47742802 Yeah, the requests.get step is instant, so I g... \n47743040 That was absolutely the issue. Thanks! Changi... \n48550940 Thanks for the suggestion. what does zlim do?... \n48551405 Thanks. I guess I don't understand what the h... \n50303593 I'm hitting this too on a similar setup. Did ... \n50336702 Want me to start a bounty? Would you be avail... \n50337057 Is this useful? http://blog.fejes.ca/?p=2496 ... \n50376360 Thanks Jesse, I guess we couldn't tell if it w... \n54364203 Thanks. I believe the fix_oralib.rb also does... \n58665815 @zsepi, I updated the question with those. \n58894206 It set's to write to a specified file, and ema... \n62020862 @tdelaney, did you try it on osx? It actually... \n62020942 I tried redirecting to a file and it still out... \n62020963 @tdelaney, I think you're right, it's probably... \n68427097 Good point. I took that line out. Same issue... \n70139817 I have 'A' and 'B' configured elsewhere to do ... \n70435606 I want to do everything in memory. All the do... \n76846070 Thanks. I didn't notice that. Taking it out ... \n77453798 I was wondering about that. But how would I c... \n77456266 That actually fixed my problem. \n80880518 @Jiaaro, thanks, but just tried it and no impr... \n\n CreationDate UserId ContentLicense \nCommentId \n857928 2009-06-25T22:15:13.437 13009 CC BY-SA 2.5 \n1513319 2009-10-29T12:44:20.160 13009 CC BY-SA 2.5 \n3029786 2010-06-03T22:10:42.643 13009 CC BY-SA 2.5 \n3421734 2010-07-21T19:14:03.313 13009 CC BY-SA 2.5 \n6330991 2011-04-06T12:26:33.123 13009 CC BY-SA 2.5 \n6331285 2011-04-06T12:43:15.377 13009 CC BY-SA 2.5 \n6774887 2011-05-04T20:00:35.997 13009 CC BY-SA 3.0 \n8234046 2011-08-02T14:23:53.283 13009 CC BY-SA 3.0 \n8234115 2011-08-02T14:26:37.263 13009 CC BY-SA 3.0 \n8235637 2011-08-02T15:36:12.527 13009 CC BY-SA 3.0 \n8239108 2011-08-02T18:48:59.337 13009 CC BY-SA 3.0 \n8257824 2011-08-03T16:59:56.540 13009 CC BY-SA 3.0 \n8499177 2011-08-17T18:43:55.627 13009 CC BY-SA 3.0 \n10657798 2011-12-21T15:30:22.113 13009 CC BY-SA 3.0 \n10796244 2011-12-30T19:08:28.063 13009 CC BY-SA 3.0 \n11245320 2012-01-23T18:14:14.870 13009 CC BY-SA 3.0 \n11245634 2012-01-23T18:28:32.813 13009 CC BY-SA 3.0 \n12490216 2012-03-21T15:00:45.163 13009 CC BY-SA 3.0 \n32554534 2014-02-04T15:05:23.023 13009 CC BY-SA 3.0 \n32567053 2014-02-04T20:26:56.147 13009 CC BY-SA 3.0 \n36034593 2014-05-06T14:42:07.190 13009 CC BY-SA 3.0 \n36034937 2014-05-06T14:49:57.347 13009 CC BY-SA 3.0 \n36041765 2014-05-06T17:47:18.563 13009 CC BY-SA 3.0 \n47738961 2015-04-22T18:04:58.213 13009 CC BY-SA 3.0 \n47742802 2015-04-22T19:45:33.083 13009 CC BY-SA 3.0 \n47743040 2015-04-22T19:52:21.247 13009 CC BY-SA 3.0 \n48550940 2015-05-13T19:22:13.533 13009 CC BY-SA 3.0 \n48551405 2015-05-13T19:36:25.690 13009 CC BY-SA 3.0 \n50303593 2015-06-30T19:18:02.697 13009 CC BY-SA 3.0 \n50336702 2015-07-01T14:27:34.823 13009 CC BY-SA 3.0 \n50337057 2015-07-01T14:35:16.503 13009 CC BY-SA 3.0 \n50376360 2015-07-02T13:09:14.617 13009 CC BY-SA 3.0 \n54364203 2015-10-22T13:16:49.317 13009 CC BY-SA 3.0 \n58665815 2016-02-18T15:55:59.940 13009 CC BY-SA 3.0 \n58894206 2016-02-24T14:29:13.990 13009 CC BY-SA 3.0 \n62020862 2016-05-16T03:06:55.457 13009 CC BY-SA 3.0 \n62020942 2016-05-16T03:13:12.050 13009 CC BY-SA 3.0 \n62020963 2016-05-16T03:14:39.700 13009 CC BY-SA 3.0 \n68427097 2016-11-14T18:52:50.053 13009 CC BY-SA 3.0 \n70139817 2017-01-04T15:15:07.183 13009 CC BY-SA 3.0 \n70435606 2017-01-12T15:37:23.967 13009 CC BY-SA 3.0 \n76846070 2017-07-05T20:00:37.840 13009 CC BY-SA 3.0 \n77453798 2017-07-21T17:54:41.707 13009 CC BY-SA 3.0 \n77456266 2017-07-21T19:11:37.543 13009 CC BY-SA 3.0 \n80880518 2017-10-27T02:20:12.973 13009 CC BY-SA 3.0 ",
- "text/html": "<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>Tags</th>\n <th>PostId</th>\n <th>Score</th>\n <th>Body</th>\n <th>CreationDate</th>\n <th>UserId</th>\n <th>ContentLicense</th>\n </tr>\n <tr>\n <th>CommentId</th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>857928</th>\n <td><python><subprocess><pipe><echo><popen></td>\n <td>1046474</td>\n <td>0</td>\n <td>Yes, it runs from the windows dos console.</td>\n <td>2009-06-25T22:15:13.437</td>\n <td>13009</td>\n <td>CC BY-SA 2.5</td>\n </tr>\n <tr>\n <th>1513319</th>\n <td><python><django><forms><django-forms></td>\n <td>1640204</td>\n <td>0</td>\n <td>lemonad, this would be at form creation time, ...</td>\n <td>2009-10-29T12:44:20.160</td>\n <td>13009</td>\n <td>CC BY-SA 2.5</td>\n </tr>\n <tr>\n <th>3029786</th>\n <td><python><windows><winapi><popen><long-running-...</td>\n <td>2970045</td>\n <td>0</td>\n <td>Here are a few windows API commands that look ...</td>\n <td>2010-06-03T22:10:42.643</td>\n <td>13009</td>\n <td>CC BY-SA 2.5</td>\n </tr>\n <tr>\n <th>3421734</th>\n <td><python><permissions><authorization><decorator...</td>\n <td>3302844</td>\n <td>0</td>\n <td>I don't think I want to use anything built-in....</td>\n <td>2010-07-21T19:14:03.313</td>\n <td>13009</td>\n <td>CC BY-SA 2.5</td>\n </tr>\n <tr>\n <th>6330991</th>\n <td><python><django><django-models><decimal><scien...</td>\n <td>5566121</td>\n <td>0</td>\n <td>4.08E+13 has two decimal places, I'm allowing ...</td>\n <td>2011-04-06T12:26:33.123</td>\n <td>13009</td>\n <td>CC BY-SA 2.5</td>\n </tr>\n <tr>\n <th>6331285</th>\n <td><python><django><django-models><decimal><scien...</td>\n <td>5566121</td>\n <td>0</td>\n <td>I followed those instructions. I've tried all...</td>\n <td>2011-04-06T12:43:15.377</td>\n <td>13009</td>\n <td>CC BY-SA 2.5</td>\n </tr>\n <tr>\n <th>6774887</th>\n <td><python><database><migration><django-south></td>\n <td>5833418</td>\n <td>4</td>\n <td>It's going to be pretty critical data, and hon...</td>\n <td>2011-05-04T20:00:35.997</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>8234046</th>\n <td><python><django><django-models><django-admin><...</td>\n <td>6913166</td>\n <td>1</td>\n <td>I'm thinking I need to make a custom model fie...</td>\n <td>2011-08-02T14:23:53.283</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>8234115</th>\n <td><python><string-formatting><number-formatting>...</td>\n <td>6913532</td>\n <td>32</td>\n <td>nah, not at all. I wanted to separate this int...</td>\n <td>2011-08-02T14:26:37.263</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>8235637</th>\n <td><python><django><django-models><django-admin><...</td>\n <td>6913166</td>\n <td>0</td>\n <td>I'm not seeing much action on this thread. I ...</td>\n <td>2011-08-02T15:36:12.527</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>8239108</th>\n <td><python><django><django-models><django-admin><...</td>\n <td>6913166</td>\n <td>0</td>\n <td>I'm not seeing much action on the Django users...</td>\n <td>2011-08-02T18:48:59.337</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>8257824</th>\n <td><python><django><django-models><django-admin><...</td>\n <td>6913166</td>\n <td>0</td>\n <td>IRC seems to be down. No luck there either.</td>\n <td>2011-08-03T16:59:56.540</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>8499177</th>\n <td><python><django><django-models></td>\n <td>7097475</td>\n <td>0</td>\n <td>@agf. I don't understand what the resolution ...</td>\n <td>2011-08-17T18:43:55.627</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>10657798</th>\n <td><python><excel><xlwt></td>\n <td>8590741</td>\n <td>0</td>\n <td>Well, after playing around, the first number i...</td>\n <td>2011-12-21T15:30:22.113</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>10796244</th>\n <td><python><excel><xlwt></td>\n <td>8590741</td>\n <td>0</td>\n <td>Thanks for the answers everyone. If anyone is...</td>\n <td>2011-12-30T19:08:28.063</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>11245320</th>\n <td><python></td>\n <td>8976324</td>\n <td>0</td>\n <td>@Cameron, so you're saying something I import ...</td>\n <td>2012-01-23T18:14:14.870</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>11245634</th>\n <td><python></td>\n <td>8976324</td>\n <td>0</td>\n <td>Thanks everyone. If anyone wants to post this...</td>\n <td>2012-01-23T18:28:32.813</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>12490216</th>\n <td><python><django><django-models><django-admin></td>\n <td>9806936</td>\n <td>0</td>\n <td>@jpic, that's interesting but it's probably ov...</td>\n <td>2012-03-21T15:00:45.163</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>32554534</th>\n <td><python><django><django-forms><django-admin><d...</td>\n <td>19807757</td>\n <td>0</td>\n <td>I'm coming across the exact same problem. I a...</td>\n <td>2014-02-04T15:05:23.023</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>32567053</th>\n <td><python><django><django-forms><django-admin><d...</td>\n <td>19807757</td>\n <td>0</td>\n <td>I put an updated question more inline with wha...</td>\n <td>2014-02-04T20:26:56.147</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>36034593</th>\n <td><python><numpy></td>\n <td>23497706</td>\n <td>0</td>\n <td>I was thinking I could reference just the firs...</td>\n <td>2014-05-06T14:42:07.190</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>36034937</th>\n <td><python><numpy></td>\n <td>23497706</td>\n <td>0</td>\n <td>hmm, I can access the first column with array[...</td>\n <td>2014-05-06T14:49:57.347</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>36041765</th>\n <td><python><numpy></td>\n <td>23500754</td>\n <td>0</td>\n <td>hmm, I just ran the code from your answer. Do...</td>\n <td>2014-05-06T17:47:18.563</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>47738961</th>\n <td><python><python-requests></td>\n <td>29775247</td>\n <td>1</td>\n <td>@sigmavirus24, that's right I don't want to lo...</td>\n <td>2015-04-22T18:04:58.213</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>47742802</th>\n <td><python><curl><python-requests></td>\n <td>29807249</td>\n <td>0</td>\n <td>Yeah, the requests.get step is instant, so I g...</td>\n <td>2015-04-22T19:45:33.083</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>47743040</th>\n <td><python><curl><python-requests></td>\n <td>29807249</td>\n <td>0</td>\n <td>That was absolutely the issue. Thanks! Changi...</td>\n <td>2015-04-22T19:52:21.247</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>48550940</th>\n <td><python><matplotlib></td>\n <td>30223161</td>\n <td>0</td>\n <td>Thanks for the suggestion. what does zlim do?...</td>\n <td>2015-05-13T19:22:13.533</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>48551405</th>\n <td><python><matplotlib></td>\n <td>30223161</td>\n <td>0</td>\n <td>Thanks. I guess I don't understand what the h...</td>\n <td>2015-05-13T19:36:25.690</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>50303593</th>\n <td><python><mongodb><uwsgi><mlab><pymongo-3.x></td>\n <td>31030307</td>\n <td>2</td>\n <td>I'm hitting this too on a similar setup. Did ...</td>\n <td>2015-06-30T19:18:02.697</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>50336702</th>\n <td><python><mongodb><uwsgi><mlab><pymongo-3.x></td>\n <td>31030307</td>\n <td>1</td>\n <td>Want me to start a bounty? Would you be avail...</td>\n <td>2015-07-01T14:27:34.823</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>50337057</th>\n <td><python><mongodb><uwsgi><mlab><pymongo-3.x></td>\n <td>31030307</td>\n <td>0</td>\n <td>Is this useful? http://blog.fejes.ca/?p=2496 ...</td>\n <td>2015-07-01T14:35:16.503</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>50376360</th>\n <td><python><mongodb><uwsgi><mlab><pymongo-3.x></td>\n <td>31030307</td>\n <td>0</td>\n <td>Thanks Jesse, I guess we couldn't tell if it w...</td>\n <td>2015-07-02T13:09:14.617</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>54364203</th>\n <td><python><oracle><macos><cx-oracle><osx-elcapitan></td>\n <td>33259671</td>\n <td>0</td>\n <td>Thanks. I believe the fix_oralib.rb also does...</td>\n <td>2015-10-22T13:16:49.317</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>58665815</th>\n <td><python><django><celery><django-celery></td>\n <td>35486011</td>\n <td>0</td>\n <td>@zsepi, I updated the question with those.</td>\n <td>2016-02-18T15:55:59.940</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>58894206</th>\n <td><python><django><celery><django-celery></td>\n <td>35603707</td>\n <td>0</td>\n <td>It set's to write to a specified file, and ema...</td>\n <td>2016-02-24T14:29:13.990</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>62020862</th>\n <td><python><python-2.7><unicode><subprocess></td>\n <td>37245595</td>\n <td>0</td>\n <td>@tdelaney, did you try it on osx? It actually...</td>\n <td>2016-05-16T03:06:55.457</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>62020942</th>\n <td><python><python-2.7><unicode><subprocess></td>\n <td>37245595</td>\n <td>0</td>\n <td>I tried redirecting to a file and it still out...</td>\n <td>2016-05-16T03:13:12.050</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>62020963</th>\n <td><python><python-2.7><unicode><subprocess></td>\n <td>37245595</td>\n <td>0</td>\n <td>@tdelaney, I think you're right, it's probably...</td>\n <td>2016-05-16T03:14:39.700</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>68427097</th>\n <td><python><mocking><generator><python-unittest><...</td>\n <td>40595679</td>\n <td>0</td>\n <td>Good point. I took that line out. Same issue...</td>\n <td>2016-11-14T18:52:50.053</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>70139817</th>\n <td><python><logging></td>\n <td>41467032</td>\n <td>0</td>\n <td>I have 'A' and 'B' configured elsewhere to do ...</td>\n <td>2017-01-04T15:15:07.183</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>70435606</th>\n <td><python><postgresql><psycopg2><psycopg></td>\n <td>41616578</td>\n <td>0</td>\n <td>I want to do everything in memory. All the do...</td>\n <td>2017-01-12T15:37:23.967</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>76846070</th>\n <td><python><django><django-models><django-authent...</td>\n <td>44933724</td>\n <td>0</td>\n <td>Thanks. I didn't notice that. Taking it out ...</td>\n <td>2017-07-05T20:00:37.840</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>77453798</th>\n <td><python><django><migration><django-migrations></td>\n <td>45238835</td>\n <td>0</td>\n <td>I was wondering about that. But how would I c...</td>\n <td>2017-07-21T17:54:41.707</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>77456266</th>\n <td><python><django><migration><django-migrations></td>\n <td>45238835</td>\n <td>0</td>\n <td>That actually fixed my problem.</td>\n <td>2017-07-21T19:11:37.543</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>80880518</th>\n <td><python><django></td>\n <td>46960782</td>\n <td>0</td>\n <td>@Jiaaro, thanks, but just tried it and no impr...</td>\n <td>2017-10-27T02:20:12.973</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n </tbody>\n</table>\n</div>"
- },
- "execution_count": 20,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "comments_on_questions_df = pd.read_sql_query(f\"\"\"\n",
- " SELECT A.Tags, B.*\n",
- " FROM Post A\n",
- " INNER JOIN Comment B ON (B.PostId = A.PostId)\n",
- " WHERE A.Tags LIKE '%python%' AND (B.UserId = {user_id}) AND (A.PostTypeId = 1)\n",
- "\"\"\", db)\n",
- "comments_on_questions_df.set_index('CommentId', inplace=True)\n",
- "comments_on_questions_df"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": 21,
- "outputs": [
- {
- "data": {
- "text/plain": " Tags PostId Score \\\nCommentId \n27452 <python><memory-management><short> 120454 0 \n30223 <python> 125052 0 \n63505 <python> 92318 0 \n124749 <python><mysql><database><deadlock> 270449 0 \n124761 <python><mysql><database><deadlock> 270492 0 \n... ... ... ... \n68725297 <python><subprocess><fork> 40749648 0 \n68725576 <python><subprocess><fork> 40749648 1 \n70480473 <python><postgresql><psycopg2><psycopg> 41623932 0 \n70641464 <python><django><testing><sqlite> 1203379 0 \n79329507 <python> 13091300 9 \n\n Body \\\nCommentId \n27452 Can I use IIBTree without installing all of Zo... \n30223 Keep in mind there are some unpythonic idioms ... \n63505 What about iterators exactly? \n124749 That would just cause a OperationalError: (120... \n124761 How would I make sure they run at exactly the ... \n... ... \n68725297 Follow up question. What if the child finishe... \n68725576 Excellent thanks! From your article, I guess ... \n70480473 Yes, I verified that worked to remove the quot... \n70641464 @bstpierre, how did you force transaction supp... \n79329507 Only problem with this is I get code lint warn... \n\n CreationDate UserId ContentLicense \nCommentId \n27452 2008-09-23T16:48:24.133 13009 CC BY-SA 2.5 \n30223 2008-09-24T14:02:17.330 13009 CC BY-SA 2.5 \n63505 2008-10-08T01:43:15.823 13009 CC BY-SA 2.5 \n124749 2008-11-06T22:10:52.610 13009 CC BY-SA 2.5 \n124761 2008-11-06T22:12:43.137 13009 CC BY-SA 2.5 \n... ... ... ... \n68725297 2016-11-22T19:04:27.827 13009 CC BY-SA 3.0 \n68725576 2016-11-22T19:13:12.043 13009 CC BY-SA 3.0 \n70480473 2017-01-13T17:35:23.640 13009 CC BY-SA 3.0 \n70641464 2017-01-18T15:34:03.417 13009 CC BY-SA 3.0 \n79329507 2017-09-12T18:41:40.393 13009 CC BY-SA 3.0 \n\n[99 rows x 7 columns]",
- "text/html": "<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>Tags</th>\n <th>PostId</th>\n <th>Score</th>\n <th>Body</th>\n <th>CreationDate</th>\n <th>UserId</th>\n <th>ContentLicense</th>\n </tr>\n <tr>\n <th>CommentId</th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>27452</th>\n <td><python><memory-management><short></td>\n <td>120454</td>\n <td>0</td>\n <td>Can I use IIBTree without installing all of Zo...</td>\n <td>2008-09-23T16:48:24.133</td>\n <td>13009</td>\n <td>CC BY-SA 2.5</td>\n </tr>\n <tr>\n <th>30223</th>\n <td><python></td>\n <td>125052</td>\n <td>0</td>\n <td>Keep in mind there are some unpythonic idioms ...</td>\n <td>2008-09-24T14:02:17.330</td>\n <td>13009</td>\n <td>CC BY-SA 2.5</td>\n </tr>\n <tr>\n <th>63505</th>\n <td><python></td>\n <td>92318</td>\n <td>0</td>\n <td>What about iterators exactly?</td>\n <td>2008-10-08T01:43:15.823</td>\n <td>13009</td>\n <td>CC BY-SA 2.5</td>\n </tr>\n <tr>\n <th>124749</th>\n <td><python><mysql><database><deadlock></td>\n <td>270449</td>\n <td>0</td>\n <td>That would just cause a OperationalError: (120...</td>\n <td>2008-11-06T22:10:52.610</td>\n <td>13009</td>\n <td>CC BY-SA 2.5</td>\n </tr>\n <tr>\n <th>124761</th>\n <td><python><mysql><database><deadlock></td>\n <td>270492</td>\n <td>0</td>\n <td>How would I make sure they run at exactly the ...</td>\n <td>2008-11-06T22:12:43.137</td>\n <td>13009</td>\n <td>CC BY-SA 2.5</td>\n </tr>\n <tr>\n <th>...</th>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n </tr>\n <tr>\n <th>68725297</th>\n <td><python><subprocess><fork></td>\n <td>40749648</td>\n <td>0</td>\n <td>Follow up question. What if the child finishe...</td>\n <td>2016-11-22T19:04:27.827</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>68725576</th>\n <td><python><subprocess><fork></td>\n <td>40749648</td>\n <td>1</td>\n <td>Excellent thanks! From your article, I guess ...</td>\n <td>2016-11-22T19:13:12.043</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>70480473</th>\n <td><python><postgresql><psycopg2><psycopg></td>\n <td>41623932</td>\n <td>0</td>\n <td>Yes, I verified that worked to remove the quot...</td>\n <td>2017-01-13T17:35:23.640</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>70641464</th>\n <td><python><django><testing><sqlite></td>\n <td>1203379</td>\n <td>0</td>\n <td>@bstpierre, how did you force transaction supp...</td>\n <td>2017-01-18T15:34:03.417</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>79329507</th>\n <td><python></td>\n <td>13091300</td>\n <td>9</td>\n <td>Only problem with this is I get code lint warn...</td>\n <td>2017-09-12T18:41:40.393</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n </tbody>\n</table>\n<p>99 rows × 7 columns</p>\n</div>"
- },
- "execution_count": 21,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "comments_on_answers_df = pd.read_sql_query(f\"\"\"\n",
- " SELECT A.Tags, C.*\n",
- " FROM Post A\n",
- " INNER JOIN Post B ON (B.ParentId = A.PostId) AND (B.ParentId IS NOT NULL)\n",
- " INNER JOIN Comment C ON (B.PostId = C.PostId)\n",
- " WHERE A.Tags LIKE '%python%' AND (C.UserId = {user_id}) AND (B.PostTypeId = 2)\n",
- "\"\"\", db)\n",
- "comments_on_answers_df.set_index('CommentId', inplace=True)\n",
- "comments_on_answers_df"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": 22,
- "outputs": [],
- "source": [
- "from post_embedding_builder import Import"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": 23,
- "outputs": [],
- "source": [
- "from static_graph_construction import StaticGraphConstruction"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "markdown",
- "source": [
- "Let's construct the heterogenous graph"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": 24,
- "outputs": [],
- "source": [
- "comments_df = pd.concat([comments_on_questions_df, comments_on_answers_df])"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": 27,
- "outputs": [],
- "source": [
- "graph_constructor = StaticGraphConstruction()"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": 26,
- "outputs": [
- {
- "ename": "KeyboardInterrupt",
- "evalue": "",
- "output_type": "error",
- "traceback": [
- "\u001B[1;31m---------------------------------------------------------------------------\u001B[0m",
- "\u001B[1;31mKeyboardInterrupt\u001B[0m Traceback (most recent call last)",
- "Cell \u001B[1;32mIn [26], line 3\u001B[0m\n\u001B[0;32m 1\u001B[0m \u001B[38;5;28;01mimport\u001B[39;00m \u001B[38;5;21;01mtorch_geometric\u001B[39;00m\u001B[38;5;21;01m.\u001B[39;00m\u001B[38;5;21;01mtransforms\u001B[39;00m \u001B[38;5;28;01mas\u001B[39;00m \u001B[38;5;21;01mT\u001B[39;00m\n\u001B[0;32m 2\u001B[0m graph_constructor \u001B[38;5;241m=\u001B[39m StaticGraphConstruction()\n\u001B[1;32m----> 3\u001B[0m graph_out \u001B[38;5;241m=\u001B[39m \u001B[43mgraph_constructor\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mconstruct\u001B[49m\u001B[43m(\u001B[49m\u001B[43mquestions_df\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43manswers_df\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mcomments_df\u001B[49m\u001B[43m)\u001B[49m\n\u001B[0;32m 4\u001B[0m \u001B[38;5;66;03m#graph_out['module'].x = torch.empty(0, 110, dtype=torch.long)\u001B[39;00m\n\u001B[0;32m 5\u001B[0m graph_out\n",
- "File \u001B[1;32m~\\Documents\\graph4stackoverflow\\embeddings\\static_graph_construction.py:120\u001B[0m, in \u001B[0;36mStaticGraphConstruction.construct\u001B[1;34m(self, questions, answers, comments)\u001B[0m\n\u001B[0;32m 114\u001B[0m comments \u001B[38;5;241m=\u001B[39m comments\u001B[38;5;241m.\u001B[39mhead(\u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_post_count_limit)\n\u001B[0;32m 116\u001B[0m \u001B[38;5;66;03m# questions.reset_index(inplace=True)\u001B[39;00m\n\u001B[0;32m 117\u001B[0m \u001B[38;5;66;03m# answers.reset_index(inplace=True)\u001B[39;00m\n\u001B[0;32m 118\u001B[0m \u001B[38;5;66;03m# comments.reset_index(inplace=True)\u001B[39;00m\n\u001B[1;32m--> 120\u001B[0m question_nodes \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;43mlist\u001B[39;49m\u001B[43m(\u001B[49m\u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mprocess_questions\u001B[49m\u001B[43m(\u001B[49m\u001B[43mquestions\u001B[49m\u001B[43m)\u001B[49m\u001B[43m)\u001B[49m\n\u001B[0;32m 121\u001B[0m answer_nodes \u001B[38;5;241m=\u001B[39m \u001B[38;5;28mlist\u001B[39m(\u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mprocess_answers(answers))\n\u001B[0;32m 122\u001B[0m comment_nodes \u001B[38;5;241m=\u001B[39m \u001B[38;5;28mlist\u001B[39m(\u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mprocess_comments(comments))\n",
- "File \u001B[1;32m~\\Documents\\graph4stackoverflow\\embeddings\\static_graph_construction.py:39\u001B[0m, in \u001B[0;36mStaticGraphConstruction.process_questions\u001B[1;34m(self, questions)\u001B[0m\n\u001B[0;32m 38\u001B[0m \u001B[38;5;28;01mdef\u001B[39;00m \u001B[38;5;21mprocess_questions\u001B[39m(\u001B[38;5;28mself\u001B[39m, questions: pd\u001B[38;5;241m.\u001B[39mDataFrame) \u001B[38;5;241m-\u001B[39m\u001B[38;5;241m>\u001B[39m torch\u001B[38;5;241m.\u001B[39mTensor:\n\u001B[1;32m---> 39\u001B[0m word_embedding, code_embedding, modules \u001B[38;5;241m=\u001B[39m \u001B[43mStaticGraphConstruction\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mpost_embedding_builder\u001B[49m\u001B[43m(\u001B[49m\u001B[43mquestions\u001B[49m\u001B[43m[\u001B[49m\u001B[38;5;124;43m'\u001B[39;49m\u001B[38;5;124;43mBody\u001B[39;49m\u001B[38;5;124;43m'\u001B[39;49m\u001B[43m]\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43m_use_bert\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mquestions\u001B[49m\u001B[43m[\u001B[49m\u001B[38;5;124;43m'\u001B[39;49m\u001B[38;5;124;43mTitle\u001B[39;49m\u001B[38;5;124;43m'\u001B[39;49m\u001B[43m]\u001B[49m\u001B[43m)\u001B[49m\n\u001B[0;32m 40\u001B[0m \u001B[38;5;28;01mfor\u001B[39;00m i, body, title, tags \u001B[38;5;129;01min\u001B[39;00m questions[[\u001B[38;5;124m'\u001B[39m\u001B[38;5;124mBody\u001B[39m\u001B[38;5;124m'\u001B[39m, \u001B[38;5;124m'\u001B[39m\u001B[38;5;124mTitle\u001B[39m\u001B[38;5;124m'\u001B[39m, \u001B[38;5;124m'\u001B[39m\u001B[38;5;124mTags\u001B[39m\u001B[38;5;124m'\u001B[39m]]\u001B[38;5;241m.\u001B[39mitertuples():\n\u001B[0;32m 42\u001B[0m modules \u001B[38;5;241m=\u001B[39m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mprocess_module_names(modules)\n",
- "File \u001B[1;32m~\\Documents\\graph4stackoverflow\\venv\\lib\\site-packages\\torch\\nn\\modules\\module.py:1190\u001B[0m, in \u001B[0;36mModule._call_impl\u001B[1;34m(self, *input, **kwargs)\u001B[0m\n\u001B[0;32m 1186\u001B[0m \u001B[38;5;66;03m# If we don't have any hooks, we want to skip the rest of the logic in\u001B[39;00m\n\u001B[0;32m 1187\u001B[0m \u001B[38;5;66;03m# this function, and just call forward.\u001B[39;00m\n\u001B[0;32m 1188\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m \u001B[38;5;129;01mnot\u001B[39;00m (\u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_backward_hooks \u001B[38;5;129;01mor\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_forward_hooks \u001B[38;5;129;01mor\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_forward_pre_hooks \u001B[38;5;129;01mor\u001B[39;00m _global_backward_hooks\n\u001B[0;32m 1189\u001B[0m \u001B[38;5;129;01mor\u001B[39;00m _global_forward_hooks \u001B[38;5;129;01mor\u001B[39;00m _global_forward_pre_hooks):\n\u001B[1;32m-> 1190\u001B[0m \u001B[38;5;28;01mreturn\u001B[39;00m \u001B[43mforward_call\u001B[49m\u001B[43m(\u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[38;5;28;43minput\u001B[39;49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[43mkwargs\u001B[49m\u001B[43m)\u001B[49m\n\u001B[0;32m 1191\u001B[0m \u001B[38;5;66;03m# Do not call functions when jit is used\u001B[39;00m\n\u001B[0;32m 1192\u001B[0m full_backward_hooks, non_full_backward_hooks \u001B[38;5;241m=\u001B[39m [], []\n",
- "File \u001B[1;32m~\\Documents\\graph4stackoverflow\\embeddings\\post_embedding_builder.py:64\u001B[0m, in \u001B[0;36mPostEmbedding.forward\u001B[1;34m(self, html_batch, use_bert, title_batch)\u001B[0m\n\u001B[0;32m 62\u001B[0m t1 \u001B[38;5;241m=\u001B[39m time\u001B[38;5;241m.\u001B[39mtime()\n\u001B[0;32m 63\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m use_bert:\n\u001B[1;32m---> 64\u001B[0m para_emb \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mto_bert_embedding\u001B[49m\u001B[43m(\u001B[49m\u001B[43m[\u001B[49m\u001B[38;5;124;43m\"\u001B[39;49m\u001B[38;5;124;43m \u001B[39;49m\u001B[38;5;124;43m\"\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mjoin\u001B[49m\u001B[43m(\u001B[49m\u001B[43mps\u001B[49m\u001B[43m)\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;28;43;01mfor\u001B[39;49;00m\u001B[43m \u001B[49m\u001B[43mps\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;129;43;01min\u001B[39;49;00m\u001B[43m \u001B[49m\u001B[43mparagraph_batches\u001B[49m\u001B[43m]\u001B[49m\u001B[43m)\u001B[49m\n\u001B[0;32m 65\u001B[0m \u001B[38;5;28;01melse\u001B[39;00m:\n\u001B[0;32m 66\u001B[0m \u001B[38;5;66;03m#para_emb = self.to_glove_paragraph_embedding(ps)\u001B[39;00m\n\u001B[0;32m 67\u001B[0m \u001B[38;5;28;01mraise\u001B[39;00m \u001B[38;5;167;01mNotImplementedError\u001B[39;00m(\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mGloVe paragraph embedding need to be refactored to work with batches\u001B[39m\u001B[38;5;124m\"\u001B[39m)\n",
- "File \u001B[1;32m~\\Documents\\graph4stackoverflow\\embeddings\\post_embedding_builder.py:154\u001B[0m, in \u001B[0;36mPostEmbedding.to_bert_embedding\u001B[1;34m(self, texts)\u001B[0m\n\u001B[0;32m 152\u001B[0m encodings \u001B[38;5;241m=\u001B[39m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_bert_tokenizer(texts, padding\u001B[38;5;241m=\u001B[39m\u001B[38;5;28;01mTrue\u001B[39;00m, truncation\u001B[38;5;241m=\u001B[39m\u001B[38;5;28;01mTrue\u001B[39;00m, return_tensors\u001B[38;5;241m=\u001B[39m\u001B[38;5;124m'\u001B[39m\u001B[38;5;124mpt\u001B[39m\u001B[38;5;124m'\u001B[39m, max_length\u001B[38;5;241m=\u001B[39m\u001B[38;5;241m512\u001B[39m)\n\u001B[0;32m 153\u001B[0m \u001B[38;5;28;01mwith\u001B[39;00m torch\u001B[38;5;241m.\u001B[39mno_grad():\n\u001B[1;32m--> 154\u001B[0m outputs \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43m_bert_model\u001B[49m\u001B[43m(\u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[43mencodings\u001B[49m\u001B[43m)\u001B[49m\n\u001B[0;32m 155\u001B[0m last_layer \u001B[38;5;241m=\u001B[39m outputs\u001B[38;5;241m.\u001B[39mlast_hidden_state\n\u001B[0;32m 156\u001B[0m \u001B[38;5;28mcls\u001B[39m \u001B[38;5;241m=\u001B[39m last_layer[:, \u001B[38;5;241m0\u001B[39m, :]\n",
- "File \u001B[1;32m~\\Documents\\graph4stackoverflow\\venv\\lib\\site-packages\\torch\\nn\\modules\\module.py:1190\u001B[0m, in \u001B[0;36mModule._call_impl\u001B[1;34m(self, *input, **kwargs)\u001B[0m\n\u001B[0;32m 1186\u001B[0m \u001B[38;5;66;03m# If we don't have any hooks, we want to skip the rest of the logic in\u001B[39;00m\n\u001B[0;32m 1187\u001B[0m \u001B[38;5;66;03m# this function, and just call forward.\u001B[39;00m\n\u001B[0;32m 1188\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m \u001B[38;5;129;01mnot\u001B[39;00m (\u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_backward_hooks \u001B[38;5;129;01mor\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_forward_hooks \u001B[38;5;129;01mor\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_forward_pre_hooks \u001B[38;5;129;01mor\u001B[39;00m _global_backward_hooks\n\u001B[0;32m 1189\u001B[0m \u001B[38;5;129;01mor\u001B[39;00m _global_forward_hooks \u001B[38;5;129;01mor\u001B[39;00m _global_forward_pre_hooks):\n\u001B[1;32m-> 1190\u001B[0m \u001B[38;5;28;01mreturn\u001B[39;00m \u001B[43mforward_call\u001B[49m\u001B[43m(\u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[38;5;28;43minput\u001B[39;49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[43mkwargs\u001B[49m\u001B[43m)\u001B[49m\n\u001B[0;32m 1191\u001B[0m \u001B[38;5;66;03m# Do not call functions when jit is used\u001B[39;00m\n\u001B[0;32m 1192\u001B[0m full_backward_hooks, non_full_backward_hooks \u001B[38;5;241m=\u001B[39m [], []\n",
- "File \u001B[1;32m~\\Documents\\graph4stackoverflow\\venv\\lib\\site-packages\\transformers\\models\\bert\\modeling_bert.py:1014\u001B[0m, in \u001B[0;36mBertModel.forward\u001B[1;34m(self, input_ids, attention_mask, token_type_ids, position_ids, head_mask, inputs_embeds, encoder_hidden_states, encoder_attention_mask, past_key_values, use_cache, output_attentions, output_hidden_states, return_dict)\u001B[0m\n\u001B[0;32m 1005\u001B[0m head_mask \u001B[38;5;241m=\u001B[39m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mget_head_mask(head_mask, \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mconfig\u001B[38;5;241m.\u001B[39mnum_hidden_layers)\n\u001B[0;32m 1007\u001B[0m embedding_output \u001B[38;5;241m=\u001B[39m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39membeddings(\n\u001B[0;32m 1008\u001B[0m input_ids\u001B[38;5;241m=\u001B[39minput_ids,\n\u001B[0;32m 1009\u001B[0m position_ids\u001B[38;5;241m=\u001B[39mposition_ids,\n\u001B[1;32m (...)\u001B[0m\n\u001B[0;32m 1012\u001B[0m past_key_values_length\u001B[38;5;241m=\u001B[39mpast_key_values_length,\n\u001B[0;32m 1013\u001B[0m )\n\u001B[1;32m-> 1014\u001B[0m encoder_outputs \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mencoder\u001B[49m\u001B[43m(\u001B[49m\n\u001B[0;32m 1015\u001B[0m \u001B[43m \u001B[49m\u001B[43membedding_output\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 1016\u001B[0m \u001B[43m \u001B[49m\u001B[43mattention_mask\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mextended_attention_mask\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 1017\u001B[0m \u001B[43m \u001B[49m\u001B[43mhead_mask\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mhead_mask\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 1018\u001B[0m \u001B[43m \u001B[49m\u001B[43mencoder_hidden_states\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mencoder_hidden_states\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 1019\u001B[0m \u001B[43m \u001B[49m\u001B[43mencoder_attention_mask\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mencoder_extended_attention_mask\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 1020\u001B[0m \u001B[43m \u001B[49m\u001B[43mpast_key_values\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mpast_key_values\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 1021\u001B[0m \u001B[43m \u001B[49m\u001B[43muse_cache\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43muse_cache\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 1022\u001B[0m \u001B[43m \u001B[49m\u001B[43moutput_attentions\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43moutput_attentions\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 1023\u001B[0m \u001B[43m \u001B[49m\u001B[43moutput_hidden_states\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43moutput_hidden_states\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 1024\u001B[0m \u001B[43m \u001B[49m\u001B[43mreturn_dict\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mreturn_dict\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 1025\u001B[0m \u001B[43m\u001B[49m\u001B[43m)\u001B[49m\n\u001B[0;32m 1026\u001B[0m sequence_output \u001B[38;5;241m=\u001B[39m encoder_outputs[\u001B[38;5;241m0\u001B[39m]\n\u001B[0;32m 1027\u001B[0m pooled_output \u001B[38;5;241m=\u001B[39m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mpooler(sequence_output) \u001B[38;5;28;01mif\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mpooler \u001B[38;5;129;01mis\u001B[39;00m \u001B[38;5;129;01mnot\u001B[39;00m \u001B[38;5;28;01mNone\u001B[39;00m \u001B[38;5;28;01melse\u001B[39;00m \u001B[38;5;28;01mNone\u001B[39;00m\n",
- "File \u001B[1;32m~\\Documents\\graph4stackoverflow\\venv\\lib\\site-packages\\torch\\nn\\modules\\module.py:1190\u001B[0m, in \u001B[0;36mModule._call_impl\u001B[1;34m(self, *input, **kwargs)\u001B[0m\n\u001B[0;32m 1186\u001B[0m \u001B[38;5;66;03m# If we don't have any hooks, we want to skip the rest of the logic in\u001B[39;00m\n\u001B[0;32m 1187\u001B[0m \u001B[38;5;66;03m# this function, and just call forward.\u001B[39;00m\n\u001B[0;32m 1188\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m \u001B[38;5;129;01mnot\u001B[39;00m (\u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_backward_hooks \u001B[38;5;129;01mor\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_forward_hooks \u001B[38;5;129;01mor\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_forward_pre_hooks \u001B[38;5;129;01mor\u001B[39;00m _global_backward_hooks\n\u001B[0;32m 1189\u001B[0m \u001B[38;5;129;01mor\u001B[39;00m _global_forward_hooks \u001B[38;5;129;01mor\u001B[39;00m _global_forward_pre_hooks):\n\u001B[1;32m-> 1190\u001B[0m \u001B[38;5;28;01mreturn\u001B[39;00m \u001B[43mforward_call\u001B[49m\u001B[43m(\u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[38;5;28;43minput\u001B[39;49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[43mkwargs\u001B[49m\u001B[43m)\u001B[49m\n\u001B[0;32m 1191\u001B[0m \u001B[38;5;66;03m# Do not call functions when jit is used\u001B[39;00m\n\u001B[0;32m 1192\u001B[0m full_backward_hooks, non_full_backward_hooks \u001B[38;5;241m=\u001B[39m [], []\n",
- "File \u001B[1;32m~\\Documents\\graph4stackoverflow\\venv\\lib\\site-packages\\transformers\\models\\bert\\modeling_bert.py:603\u001B[0m, in \u001B[0;36mBertEncoder.forward\u001B[1;34m(self, hidden_states, attention_mask, head_mask, encoder_hidden_states, encoder_attention_mask, past_key_values, use_cache, output_attentions, output_hidden_states, return_dict)\u001B[0m\n\u001B[0;32m 594\u001B[0m layer_outputs \u001B[38;5;241m=\u001B[39m torch\u001B[38;5;241m.\u001B[39mutils\u001B[38;5;241m.\u001B[39mcheckpoint\u001B[38;5;241m.\u001B[39mcheckpoint(\n\u001B[0;32m 595\u001B[0m create_custom_forward(layer_module),\n\u001B[0;32m 596\u001B[0m hidden_states,\n\u001B[1;32m (...)\u001B[0m\n\u001B[0;32m 600\u001B[0m encoder_attention_mask,\n\u001B[0;32m 601\u001B[0m )\n\u001B[0;32m 602\u001B[0m \u001B[38;5;28;01melse\u001B[39;00m:\n\u001B[1;32m--> 603\u001B[0m layer_outputs \u001B[38;5;241m=\u001B[39m \u001B[43mlayer_module\u001B[49m\u001B[43m(\u001B[49m\n\u001B[0;32m 604\u001B[0m \u001B[43m \u001B[49m\u001B[43mhidden_states\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 605\u001B[0m \u001B[43m \u001B[49m\u001B[43mattention_mask\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 606\u001B[0m \u001B[43m \u001B[49m\u001B[43mlayer_head_mask\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 607\u001B[0m \u001B[43m \u001B[49m\u001B[43mencoder_hidden_states\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 608\u001B[0m \u001B[43m \u001B[49m\u001B[43mencoder_attention_mask\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 609\u001B[0m \u001B[43m \u001B[49m\u001B[43mpast_key_value\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 610\u001B[0m \u001B[43m \u001B[49m\u001B[43moutput_attentions\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 611\u001B[0m \u001B[43m \u001B[49m\u001B[43m)\u001B[49m\n\u001B[0;32m 613\u001B[0m hidden_states \u001B[38;5;241m=\u001B[39m layer_outputs[\u001B[38;5;241m0\u001B[39m]\n\u001B[0;32m 614\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m use_cache:\n",
- "File \u001B[1;32m~\\Documents\\graph4stackoverflow\\venv\\lib\\site-packages\\torch\\nn\\modules\\module.py:1190\u001B[0m, in \u001B[0;36mModule._call_impl\u001B[1;34m(self, *input, **kwargs)\u001B[0m\n\u001B[0;32m 1186\u001B[0m \u001B[38;5;66;03m# If we don't have any hooks, we want to skip the rest of the logic in\u001B[39;00m\n\u001B[0;32m 1187\u001B[0m \u001B[38;5;66;03m# this function, and just call forward.\u001B[39;00m\n\u001B[0;32m 1188\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m \u001B[38;5;129;01mnot\u001B[39;00m (\u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_backward_hooks \u001B[38;5;129;01mor\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_forward_hooks \u001B[38;5;129;01mor\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_forward_pre_hooks \u001B[38;5;129;01mor\u001B[39;00m _global_backward_hooks\n\u001B[0;32m 1189\u001B[0m \u001B[38;5;129;01mor\u001B[39;00m _global_forward_hooks \u001B[38;5;129;01mor\u001B[39;00m _global_forward_pre_hooks):\n\u001B[1;32m-> 1190\u001B[0m \u001B[38;5;28;01mreturn\u001B[39;00m \u001B[43mforward_call\u001B[49m\u001B[43m(\u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[38;5;28;43minput\u001B[39;49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[43mkwargs\u001B[49m\u001B[43m)\u001B[49m\n\u001B[0;32m 1191\u001B[0m \u001B[38;5;66;03m# Do not call functions when jit is used\u001B[39;00m\n\u001B[0;32m 1192\u001B[0m full_backward_hooks, non_full_backward_hooks \u001B[38;5;241m=\u001B[39m [], []\n",
- "File \u001B[1;32m~\\Documents\\graph4stackoverflow\\venv\\lib\\site-packages\\transformers\\models\\bert\\modeling_bert.py:489\u001B[0m, in \u001B[0;36mBertLayer.forward\u001B[1;34m(self, hidden_states, attention_mask, head_mask, encoder_hidden_states, encoder_attention_mask, past_key_value, output_attentions)\u001B[0m\n\u001B[0;32m 477\u001B[0m \u001B[38;5;28;01mdef\u001B[39;00m \u001B[38;5;21mforward\u001B[39m(\n\u001B[0;32m 478\u001B[0m \u001B[38;5;28mself\u001B[39m,\n\u001B[0;32m 479\u001B[0m hidden_states: torch\u001B[38;5;241m.\u001B[39mTensor,\n\u001B[1;32m (...)\u001B[0m\n\u001B[0;32m 486\u001B[0m ) \u001B[38;5;241m-\u001B[39m\u001B[38;5;241m>\u001B[39m Tuple[torch\u001B[38;5;241m.\u001B[39mTensor]:\n\u001B[0;32m 487\u001B[0m \u001B[38;5;66;03m# decoder uni-directional self-attention cached key/values tuple is at positions 1,2\u001B[39;00m\n\u001B[0;32m 488\u001B[0m self_attn_past_key_value \u001B[38;5;241m=\u001B[39m past_key_value[:\u001B[38;5;241m2\u001B[39m] \u001B[38;5;28;01mif\u001B[39;00m past_key_value \u001B[38;5;129;01mis\u001B[39;00m \u001B[38;5;129;01mnot\u001B[39;00m \u001B[38;5;28;01mNone\u001B[39;00m \u001B[38;5;28;01melse\u001B[39;00m \u001B[38;5;28;01mNone\u001B[39;00m\n\u001B[1;32m--> 489\u001B[0m self_attention_outputs \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mattention\u001B[49m\u001B[43m(\u001B[49m\n\u001B[0;32m 490\u001B[0m \u001B[43m \u001B[49m\u001B[43mhidden_states\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 491\u001B[0m \u001B[43m \u001B[49m\u001B[43mattention_mask\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 492\u001B[0m \u001B[43m \u001B[49m\u001B[43mhead_mask\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 493\u001B[0m \u001B[43m \u001B[49m\u001B[43moutput_attentions\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43moutput_attentions\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 494\u001B[0m \u001B[43m \u001B[49m\u001B[43mpast_key_value\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mself_attn_past_key_value\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 495\u001B[0m \u001B[43m \u001B[49m\u001B[43m)\u001B[49m\n\u001B[0;32m 496\u001B[0m attention_output \u001B[38;5;241m=\u001B[39m self_attention_outputs[\u001B[38;5;241m0\u001B[39m]\n\u001B[0;32m 498\u001B[0m \u001B[38;5;66;03m# if decoder, the last output is tuple of self-attn cache\u001B[39;00m\n",
- "File \u001B[1;32m~\\Documents\\graph4stackoverflow\\venv\\lib\\site-packages\\torch\\nn\\modules\\module.py:1190\u001B[0m, in \u001B[0;36mModule._call_impl\u001B[1;34m(self, *input, **kwargs)\u001B[0m\n\u001B[0;32m 1186\u001B[0m \u001B[38;5;66;03m# If we don't have any hooks, we want to skip the rest of the logic in\u001B[39;00m\n\u001B[0;32m 1187\u001B[0m \u001B[38;5;66;03m# this function, and just call forward.\u001B[39;00m\n\u001B[0;32m 1188\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m \u001B[38;5;129;01mnot\u001B[39;00m (\u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_backward_hooks \u001B[38;5;129;01mor\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_forward_hooks \u001B[38;5;129;01mor\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_forward_pre_hooks \u001B[38;5;129;01mor\u001B[39;00m _global_backward_hooks\n\u001B[0;32m 1189\u001B[0m \u001B[38;5;129;01mor\u001B[39;00m _global_forward_hooks \u001B[38;5;129;01mor\u001B[39;00m _global_forward_pre_hooks):\n\u001B[1;32m-> 1190\u001B[0m \u001B[38;5;28;01mreturn\u001B[39;00m \u001B[43mforward_call\u001B[49m\u001B[43m(\u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[38;5;28;43minput\u001B[39;49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[43mkwargs\u001B[49m\u001B[43m)\u001B[49m\n\u001B[0;32m 1191\u001B[0m \u001B[38;5;66;03m# Do not call functions when jit is used\u001B[39;00m\n\u001B[0;32m 1192\u001B[0m full_backward_hooks, non_full_backward_hooks \u001B[38;5;241m=\u001B[39m [], []\n",
- "File \u001B[1;32m~\\Documents\\graph4stackoverflow\\venv\\lib\\site-packages\\transformers\\models\\bert\\modeling_bert.py:419\u001B[0m, in \u001B[0;36mBertAttention.forward\u001B[1;34m(self, hidden_states, attention_mask, head_mask, encoder_hidden_states, encoder_attention_mask, past_key_value, output_attentions)\u001B[0m\n\u001B[0;32m 409\u001B[0m \u001B[38;5;28;01mdef\u001B[39;00m \u001B[38;5;21mforward\u001B[39m(\n\u001B[0;32m 410\u001B[0m \u001B[38;5;28mself\u001B[39m,\n\u001B[0;32m 411\u001B[0m hidden_states: torch\u001B[38;5;241m.\u001B[39mTensor,\n\u001B[1;32m (...)\u001B[0m\n\u001B[0;32m 417\u001B[0m output_attentions: Optional[\u001B[38;5;28mbool\u001B[39m] \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;01mFalse\u001B[39;00m,\n\u001B[0;32m 418\u001B[0m ) \u001B[38;5;241m-\u001B[39m\u001B[38;5;241m>\u001B[39m Tuple[torch\u001B[38;5;241m.\u001B[39mTensor]:\n\u001B[1;32m--> 419\u001B[0m self_outputs \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mself\u001B[49m\u001B[43m(\u001B[49m\n\u001B[0;32m 420\u001B[0m \u001B[43m \u001B[49m\u001B[43mhidden_states\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 421\u001B[0m \u001B[43m \u001B[49m\u001B[43mattention_mask\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 422\u001B[0m \u001B[43m \u001B[49m\u001B[43mhead_mask\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 423\u001B[0m \u001B[43m \u001B[49m\u001B[43mencoder_hidden_states\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 424\u001B[0m \u001B[43m \u001B[49m\u001B[43mencoder_attention_mask\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 425\u001B[0m \u001B[43m \u001B[49m\u001B[43mpast_key_value\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 426\u001B[0m \u001B[43m \u001B[49m\u001B[43moutput_attentions\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 427\u001B[0m \u001B[43m \u001B[49m\u001B[43m)\u001B[49m\n\u001B[0;32m 428\u001B[0m attention_output \u001B[38;5;241m=\u001B[39m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39moutput(self_outputs[\u001B[38;5;241m0\u001B[39m], hidden_states)\n\u001B[0;32m 429\u001B[0m outputs \u001B[38;5;241m=\u001B[39m (attention_output,) \u001B[38;5;241m+\u001B[39m self_outputs[\u001B[38;5;241m1\u001B[39m:] \u001B[38;5;66;03m# add attentions if we output them\u001B[39;00m\n",
- "File \u001B[1;32m~\\Documents\\graph4stackoverflow\\venv\\lib\\site-packages\\torch\\nn\\modules\\module.py:1190\u001B[0m, in \u001B[0;36mModule._call_impl\u001B[1;34m(self, *input, **kwargs)\u001B[0m\n\u001B[0;32m 1186\u001B[0m \u001B[38;5;66;03m# If we don't have any hooks, we want to skip the rest of the logic in\u001B[39;00m\n\u001B[0;32m 1187\u001B[0m \u001B[38;5;66;03m# this function, and just call forward.\u001B[39;00m\n\u001B[0;32m 1188\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m \u001B[38;5;129;01mnot\u001B[39;00m (\u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_backward_hooks \u001B[38;5;129;01mor\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_forward_hooks \u001B[38;5;129;01mor\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_forward_pre_hooks \u001B[38;5;129;01mor\u001B[39;00m _global_backward_hooks\n\u001B[0;32m 1189\u001B[0m \u001B[38;5;129;01mor\u001B[39;00m _global_forward_hooks \u001B[38;5;129;01mor\u001B[39;00m _global_forward_pre_hooks):\n\u001B[1;32m-> 1190\u001B[0m \u001B[38;5;28;01mreturn\u001B[39;00m \u001B[43mforward_call\u001B[49m\u001B[43m(\u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[38;5;28;43minput\u001B[39;49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[43mkwargs\u001B[49m\u001B[43m)\u001B[49m\n\u001B[0;32m 1191\u001B[0m \u001B[38;5;66;03m# Do not call functions when jit is used\u001B[39;00m\n\u001B[0;32m 1192\u001B[0m full_backward_hooks, non_full_backward_hooks \u001B[38;5;241m=\u001B[39m [], []\n",
- "File \u001B[1;32m~\\Documents\\graph4stackoverflow\\venv\\lib\\site-packages\\transformers\\models\\bert\\modeling_bert.py:347\u001B[0m, in \u001B[0;36mBertSelfAttention.forward\u001B[1;34m(self, hidden_states, attention_mask, head_mask, encoder_hidden_states, encoder_attention_mask, past_key_value, output_attentions)\u001B[0m\n\u001B[0;32m 344\u001B[0m attention_scores \u001B[38;5;241m=\u001B[39m attention_scores \u001B[38;5;241m+\u001B[39m attention_mask\n\u001B[0;32m 346\u001B[0m \u001B[38;5;66;03m# Normalize the attention scores to probabilities.\u001B[39;00m\n\u001B[1;32m--> 347\u001B[0m attention_probs \u001B[38;5;241m=\u001B[39m \u001B[43mnn\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mfunctional\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43msoftmax\u001B[49m\u001B[43m(\u001B[49m\u001B[43mattention_scores\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mdim\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[38;5;241;43m-\u001B[39;49m\u001B[38;5;241;43m1\u001B[39;49m\u001B[43m)\u001B[49m\n\u001B[0;32m 349\u001B[0m \u001B[38;5;66;03m# This is actually dropping out entire tokens to attend to, which might\u001B[39;00m\n\u001B[0;32m 350\u001B[0m \u001B[38;5;66;03m# seem a bit unusual, but is taken from the original Transformer paper.\u001B[39;00m\n\u001B[0;32m 351\u001B[0m attention_probs \u001B[38;5;241m=\u001B[39m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mdropout(attention_probs)\n",
- "File \u001B[1;32m~\\Documents\\graph4stackoverflow\\venv\\lib\\site-packages\\torch\\nn\\functional.py:1841\u001B[0m, in \u001B[0;36msoftmax\u001B[1;34m(input, dim, _stacklevel, dtype)\u001B[0m\n\u001B[0;32m 1839\u001B[0m dim \u001B[38;5;241m=\u001B[39m _get_softmax_dim(\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124msoftmax\u001B[39m\u001B[38;5;124m\"\u001B[39m, \u001B[38;5;28minput\u001B[39m\u001B[38;5;241m.\u001B[39mdim(), _stacklevel)\n\u001B[0;32m 1840\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m dtype \u001B[38;5;129;01mis\u001B[39;00m \u001B[38;5;28;01mNone\u001B[39;00m:\n\u001B[1;32m-> 1841\u001B[0m ret \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;43minput\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43msoftmax\u001B[49m\u001B[43m(\u001B[49m\u001B[43mdim\u001B[49m\u001B[43m)\u001B[49m\n\u001B[0;32m 1842\u001B[0m \u001B[38;5;28;01melse\u001B[39;00m:\n\u001B[0;32m 1843\u001B[0m ret \u001B[38;5;241m=\u001B[39m \u001B[38;5;28minput\u001B[39m\u001B[38;5;241m.\u001B[39msoftmax(dim, dtype\u001B[38;5;241m=\u001B[39mdtype)\n",
- "\u001B[1;31mKeyboardInterrupt\u001B[0m: "
- ]
- }
- ],
- "source": [
- "import torch_geometric.transforms as T\n",
- "graph_out = graph_constructor.construct(questions_df, answers_df, comments_df)\n",
- "#graph_out['module'].x = torch.empty(0, 110, dtype=torch.long)\n",
- "graph_out"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "outputs": [],
- "source": [
- "graph_out.__setattr__('question_emb', torch.rand(300))\n",
- "graph_out.edge_index_dict"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "outputs": [],
- "source": [
- "from torch_geometric.utils import to_networkx\n",
- "\n",
- "nx_graph = to_networkx(graph_out.to_homogeneous())\n",
- "pos_ug = nx.spring_layout(nx_graph)#, k=0.15, iterations=20)\n",
- "plt.figure(figsize=(40,40))\n",
- "nx.draw(nx_graph, pos_ug, with_labels=True)\n"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "markdown",
- "source": [
- "Let's build a GNN"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "outputs": [],
- "source": [
- "from torch.nn import Linear\n",
- "import torch.nn.functional as F\n",
- "from torch_geometric.nn import GCNConv, MeanAggregation, GATConv\n",
- "from torch_geometric.nn import global_mean_pool\n",
- "\n",
- "\n",
- "class GAT(torch.nn.Module):\n",
- " def __init__(self, hidden_channels):\n",
- " super(GAT, self).__init__()\n",
- " torch.manual_seed(12345)\n",
- " self.conv1 = GATConv((-1, -1), hidden_channels, add_self_loops=False)\n",
- " self.conv2 = GATConv((-1, -1), hidden_channels, add_self_loops=False)\n",
- " self.conv3 = GATConv((-1, -1), hidden_channels, add_self_loops=False)\n",
- " self.lin = Linear(hidden_channels, 2)\n",
- " self.softmax = torch.nn.Softmax(dim=1)\n",
- " #self.pool = global_mean_pool()#MeanAggregation()\n",
- "\n",
- " def forward(self, x, edge_index, batch, post_emb):\n",
- " # 1. Obtain node embeddings\n",
- " x = self.conv1(x, edge_index)\n",
- " x = x.relu()\n",
- " x = self.conv2(x, edge_index)\n",
- " x = x.relu()\n",
- " x = self.conv3(x, edge_index)\n",
- "\n",
- " # 2. Readout layer\n",
- " x = self.pool(x, batch) # [batch_size, hidden_channels]\n",
- " #x = torch.cat((x, post_emb))\n",
- " # 3. Apply a final classifier\n",
- " # x = F.dropout(x, p=0.5, training=self.training)\n",
- " x = self.lin(x)\n",
- "\n",
- " #x = self.softmax(x)\n",
- " return x\n",
- "model = GAT(hidden_channels=64)\n",
- "print(model)"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "outputs": [],
- "source": [
- "from torch_geometric.nn.module_dict import ModuleDict\n",
- "from torch_geometric.nn import HeteroConv\n",
- "\n",
- "\n",
- "class HeteroGNN(torch.nn.Module):\n",
- " def __init__(self, hidden_channels, out_channels, num_layers):\n",
- " super().__init__()\n",
- "\n",
- " self.convs = torch.nn.ModuleList()\n",
- " for _ in range(num_layers):\n",
- " conv = HeteroConv({\n",
- " ('tag', 'describes', 'question') : GATConv((-1,-1), hidden_channels, add_self_loops=False),\n",
- " ('tag', 'describes', 'answer') : GATConv((-1,-1), hidden_channels, add_self_loops=False),\n",
- " ('tag', 'describes', 'comment') : GATConv((-1,-1), hidden_channels, add_self_loops=False),\n",
- " ('module', 'imported_in', 'question') : GATConv((-1,-1), hidden_channels, add_self_loops=False),\n",
- " ('module', 'imported_in', 'answer') : GATConv((-1,-1), hidden_channels, add_self_loops=False),\n",
- " ('question', 'rev_describes', 'tag') : GATConv((-1,-1), hidden_channels, add_self_loops=False),\n",
- " ('answer', 'rev_describes', 'tag') : GATConv((-1,-1), hidden_channels, add_self_loops=False),\n",
- " ('comment', 'rev_describes', 'tag') : GATConv((-1,-1), hidden_channels, add_self_loops=False),\n",
- " ('question', 'rev_imported_in', 'module') : GATConv((-1,-1), hidden_channels, add_self_loops=False),\n",
- " ('answer', 'rev_imported_in', 'module') : GATConv((-1,-1), hidden_channels, add_self_loops=False),\n",
- " }, aggr='sum')\n",
- " self.convs.append(conv)\n",
- "\n",
- " self.lin = Linear(hidden_channels, out_channels)\n",
- " #self.softmax = torch.nn.Softmax(dim=1)\n",
- "\n",
- "\n",
- " def forward(self, x_dict, edge_index_dict, batch_dict, post_emb=2):\n",
- " for conv in self.convs:\n",
- " x_dict = conv(x_dict, edge_index_dict)\n",
- " x_dict = {key: x.relu() for key, x in x_dict.items()}\n",
- " #return x_dict\n",
- " outs = []\n",
- " for x, batch in zip(x_dict.values(), batch_dict.values()):\n",
- " outs.append(global_mean_pool(x, batch))\n",
- " out = torch.cat(outs, dim=-1)\n",
- "\n",
- " return out\n",
- "\n",
- "\n",
- "hgnn = HeteroGNN(hidden_channels=64, out_channels=2, num_layers=3)\n",
- "hgnn"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "outputs": [],
- "source": [
- "hgnn(graph_out.x_dict, graph_out.edge_index_dict, graph_out.batch_dict, 1)"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "outputs": [],
- "source": [
- "from torch_geometric.nn import to_hetero, to_hetero_with_bases\n",
- "\n",
- "metadata = (['question', 'answer', 'comment', 'tag', 'module'], [('tag', 'describes', 'question'), ('tag', 'describes', 'answer'), ('tag', 'describes', 'comment'), ('module', 'imported_in', 'question'), ('module', 'imported_in', 'answer'), ('question', 'rev_describes', 'tag'), ('answer', 'rev_describes', 'tag'), ('comment', 'rev_describes', 'tag'), ('question', 'rev_imported_in', 'module'), ('answer', 'rev_imported_in', 'module')])\n",
- "model = to_hetero(model, metadata)\n",
- "model"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "outputs": [],
- "source": [
- "model(graph_out.x_dict, graph_out.edge_index_dict, graph_out.batch_dict, 1)"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "outputs": [],
- "source": [
- "graph_out.batch_dict"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "outputs": [],
- "source": [
- "print(\"Question ndim:\", graph_out.x_dict['question'].dim())\n",
- "print(\"Answer ndim:\", graph_out.x_dict['answer'].dim())\n",
- "print(\"Comment ndim:\", graph_out.x_dict['comment'].dim())\n",
- "print(\"Tag ndim:\", graph_out.x_dict['tag'].dim())\n",
- "print(\"Module ndim:\", graph_out.x_dict['module'].dim())"
- ],
- "metadata": {
- "collapsed": false
- }
- },
- {
- "cell_type": "code",
- "execution_count": null,
- "outputs": [],
- "source": [],
- "metadata": {
- "collapsed": false
- }
- }
- ],
- "metadata": {
- "kernelspec": {
- "display_name": "Python 3",
- "language": "python",
- "name": "python3"
- },
- "language_info": {
- "codemirror_mode": {
- "name": "ipython",
- "version": 2
- },
- "file_extension": ".py",
- "mimetype": "text/x-python",
- "name": "python",
- "nbconvert_exporter": "python",
- "pygments_lexer": "ipython2",
- "version": "2.7.6"
- }
- },
- "nbformat": 4,
- "nbformat_minor": 0
-}
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 15,
+ "outputs": [],
+ "source": [
+ "import sqlite3\n",
+ "\n",
+ "import numpy as np\n",
+ "import pandas as pd\n",
+ "from typing import *\n",
+ "import ast\n",
+ "\n",
+ "import torch\n",
+ "from torch_geometric.data import HeteroData\n",
+ "from bs4 import BeautifulSoup\n",
+ "from post_embedding_builder import PostEmbedding\n",
+ "import networkx as nx\n",
+ "from matplotlib import pyplot as plt"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 16,
+ "outputs": [],
+ "source": [
+ "# Create your connection.\n",
+ "db = sqlite3.connect('../stackoverflow.db')"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 17,
+ "outputs": [],
+ "source": [
+ "user_id = 13009"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 18,
+ "outputs": [
+ {
+ "data": {
+ "text/plain": " PostTypeId AcceptedAnswerId CreationDate Score \\\nPostId \n269676 1 NaN 2008-11-06T18:06:13.213 10 \n1046474 1 1046522.0 2009-06-25T22:04:16.890 5 \n2970045 1 2974177.0 2010-06-03T21:52:14.793 6 \n3712445 1 3712645.0 2010-09-14T20:04:19.940 1 \n5538814 1 5539724.0 2011-04-04T13:00:53.620 0 \n... ... ... ... ... \n36922532 1 36922586.0 2016-04-28T18:18:49.007 6 \n40749339 1 40749648.0 2016-11-22T18:42:04.867 1 \n41616578 1 41623932.0 2017-01-12T15:10:45.340 2 \n44933724 1 44950763.0 2017-07-05T18:40:48.800 0 \n45238835 1 45239952.0 2017-07-21T13:23:56.527 4 \n\n ViewCount Body \\\nPostId \n269676 7250 <p>I want to make my Python library working wi... \n1046474 12418 <p>How do I run this command with subprocess?<... \n2970045 7850 <p>I have a python web application that needs ... \n3712445 405 <p>Say I have text 'C:\\somedir\\test.log' and I... \n5538814 631 <p>I have multiple Django apps, and I have som... \n... ... ... \n36922532 3284 <p>I know there must be a way to do this. But... \n40749339 1271 <p>Say I have a script like this:</p>\\n\\n<pre>... \n41616578 24094 <p>I'm trying to run code like this:</p>\\n\\n<p... \n44933724 388 <p>I've been running fine on Django 1.7. I'm ... \n45238835 1191 <p>I'm on Django 1.9, Python 3.6. I made this... \n\n OwnerUserId LastEditorUserId LastEditorDisplayName \\\nPostId \n269676 13009 13009.0 Greg \n1046474 13009 13009.0 None \n2970045 13009 13009.0 None \n3712445 13009 13009.0 None \n5538814 13009 13009.0 None \n... ... ... ... \n36922532 13009 NaN None \n40749339 13009 NaN None \n41616578 13009 NaN None \n44933724 13009 NaN None \n45238835 13009 NaN None \n\n LastEditDate \\\nPostId \n269676 2008-11-10T15:12:18.133 \n1046474 2009-06-25T22:21:41.520 \n2970045 2010-06-03T22:11:27.260 \n3712445 2010-09-14T20:18:32.083 \n5538814 2011-04-04T13:15:37.903 \n... ... \n36922532 None \n40749339 None \n41616578 None \n44933724 None \n45238835 None \n\n Title \\\nPostId \n269676 How can I Cause a Deadlock in MySQL for Testin... \n1046474 Python - Subprocess - How to call a Piped comm... \n2970045 Python - Launch a Long Running Process from a ... \n3712445 Python Regular Expression Question \n5538814 Django - non app specific models.py? \n... ... \n36922532 Python functools.partial - How to apply it to ... \n40749339 Python subprocess - check exit codes of forked... \n41616578 Psycopg copy_expert method - How to use properly \n44933724 Django 1.11 upgrade - object has no attribute ... \n45238835 Django failing migration - Cannot query \"peter... \n\n Tags AnswerCount \\\nPostId \n269676 <python><mysql><database><deadlock> 5 \n1046474 <python><subprocess><pipe><echo><popen> 2 \n2970045 <python><windows><winapi><popen><long-running-... 4 \n3712445 <python><regex> 4 \n5538814 <python><django><django-models> 3 \n... ... ... \n36922532 <python><static-methods><python-decorators><fu... 3 \n40749339 <python><subprocess><fork> 1 \n41616578 <python><postgresql><psycopg2><psycopg> 2 \n44933724 <python><django><django-models><django-authent... 1 \n45238835 <python><django><migration><django-migrations> 1 \n\n CommentCount FavoriteCount CommunityOwnedDate ContentLicense \\\nPostId \n269676 0 3.0 None CC BY-SA 2.5 \n1046474 2 3.0 None CC BY-SA 2.5 \n2970045 2 6.0 None CC BY-SA 2.5 \n3712445 0 1.0 None CC BY-SA 2.5 \n5538814 0 1.0 None CC BY-SA 2.5 \n... ... ... ... ... \n36922532 0 1.0 None CC BY-SA 3.0 \n40749339 0 NaN None CC BY-SA 3.0 \n41616578 2 NaN None CC BY-SA 3.0 \n44933724 2 0.0 None CC BY-SA 3.0 \n45238835 4 NaN None CC BY-SA 3.0 \n\n ParentId \nPostId \n269676 None \n1046474 None \n2970045 None \n3712445 None \n5538814 None \n... ... \n36922532 None \n40749339 None \n41616578 None \n44933724 None \n45238835 None \n\n[105 rows x 18 columns]",
+ "text/html": "<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>PostTypeId</th>\n <th>AcceptedAnswerId</th>\n <th>CreationDate</th>\n <th>Score</th>\n <th>ViewCount</th>\n <th>Body</th>\n <th>OwnerUserId</th>\n <th>LastEditorUserId</th>\n <th>LastEditorDisplayName</th>\n <th>LastEditDate</th>\n <th>Title</th>\n <th>Tags</th>\n <th>AnswerCount</th>\n <th>CommentCount</th>\n <th>FavoriteCount</th>\n <th>CommunityOwnedDate</th>\n <th>ContentLicense</th>\n <th>ParentId</th>\n </tr>\n <tr>\n <th>PostId</th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>269676</th>\n <td>1</td>\n <td>NaN</td>\n <td>2008-11-06T18:06:13.213</td>\n <td>10</td>\n <td>7250</td>\n <td><p>I want to make my Python library working wi...</td>\n <td>13009</td>\n <td>13009.0</td>\n <td>Greg</td>\n <td>2008-11-10T15:12:18.133</td>\n <td>How can I Cause a Deadlock in MySQL for Testin...</td>\n <td><python><mysql><database><deadlock></td>\n <td>5</td>\n <td>0</td>\n <td>3.0</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>None</td>\n </tr>\n <tr>\n <th>1046474</th>\n <td>1</td>\n <td>1046522.0</td>\n <td>2009-06-25T22:04:16.890</td>\n <td>5</td>\n <td>12418</td>\n <td><p>How do I run this command with subprocess?<...</td>\n <td>13009</td>\n <td>13009.0</td>\n <td>None</td>\n <td>2009-06-25T22:21:41.520</td>\n <td>Python - Subprocess - How to call a Piped comm...</td>\n <td><python><subprocess><pipe><echo><popen></td>\n <td>2</td>\n <td>2</td>\n <td>3.0</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>None</td>\n </tr>\n <tr>\n <th>2970045</th>\n <td>1</td>\n <td>2974177.0</td>\n <td>2010-06-03T21:52:14.793</td>\n <td>6</td>\n <td>7850</td>\n <td><p>I have a python web application that needs ...</td>\n <td>13009</td>\n <td>13009.0</td>\n <td>None</td>\n <td>2010-06-03T22:11:27.260</td>\n <td>Python - Launch a Long Running Process from a ...</td>\n <td><python><windows><winapi><popen><long-running-...</td>\n <td>4</td>\n <td>2</td>\n <td>6.0</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>None</td>\n </tr>\n <tr>\n <th>3712445</th>\n <td>1</td>\n <td>3712645.0</td>\n <td>2010-09-14T20:04:19.940</td>\n <td>1</td>\n <td>405</td>\n <td><p>Say I have text 'C:\\somedir\\test.log' and I...</td>\n <td>13009</td>\n <td>13009.0</td>\n <td>None</td>\n <td>2010-09-14T20:18:32.083</td>\n <td>Python Regular Expression Question</td>\n <td><python><regex></td>\n <td>4</td>\n <td>0</td>\n <td>1.0</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>None</td>\n </tr>\n <tr>\n <th>5538814</th>\n <td>1</td>\n <td>5539724.0</td>\n <td>2011-04-04T13:00:53.620</td>\n <td>0</td>\n <td>631</td>\n <td><p>I have multiple Django apps, and I have som...</td>\n <td>13009</td>\n <td>13009.0</td>\n <td>None</td>\n <td>2011-04-04T13:15:37.903</td>\n <td>Django - non app specific models.py?</td>\n <td><python><django><django-models></td>\n <td>3</td>\n <td>0</td>\n <td>1.0</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>None</td>\n </tr>\n <tr>\n <th>...</th>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n </tr>\n <tr>\n <th>36922532</th>\n <td>1</td>\n <td>36922586.0</td>\n <td>2016-04-28T18:18:49.007</td>\n <td>6</td>\n <td>3284</td>\n <td><p>I know there must be a way to do this. But...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>Python functools.partial - How to apply it to ...</td>\n <td><python><static-methods><python-decorators><fu...</td>\n <td>3</td>\n <td>0</td>\n <td>1.0</td>\n <td>None</td>\n <td>CC BY-SA 3.0</td>\n <td>None</td>\n </tr>\n <tr>\n <th>40749339</th>\n <td>1</td>\n <td>40749648.0</td>\n <td>2016-11-22T18:42:04.867</td>\n <td>1</td>\n <td>1271</td>\n <td><p>Say I have a script like this:</p>\\n\\n<pre>...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>Python subprocess - check exit codes of forked...</td>\n <td><python><subprocess><fork></td>\n <td>1</td>\n <td>0</td>\n <td>NaN</td>\n <td>None</td>\n <td>CC BY-SA 3.0</td>\n <td>None</td>\n </tr>\n <tr>\n <th>41616578</th>\n <td>1</td>\n <td>41623932.0</td>\n <td>2017-01-12T15:10:45.340</td>\n <td>2</td>\n <td>24094</td>\n <td><p>I'm trying to run code like this:</p>\\n\\n<p...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>Psycopg copy_expert method - How to use properly</td>\n <td><python><postgresql><psycopg2><psycopg></td>\n <td>2</td>\n <td>2</td>\n <td>NaN</td>\n <td>None</td>\n <td>CC BY-SA 3.0</td>\n <td>None</td>\n </tr>\n <tr>\n <th>44933724</th>\n <td>1</td>\n <td>44950763.0</td>\n <td>2017-07-05T18:40:48.800</td>\n <td>0</td>\n <td>388</td>\n <td><p>I've been running fine on Django 1.7. I'm ...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>Django 1.11 upgrade - object has no attribute ...</td>\n <td><python><django><django-models><django-authent...</td>\n <td>1</td>\n <td>2</td>\n <td>0.0</td>\n <td>None</td>\n <td>CC BY-SA 3.0</td>\n <td>None</td>\n </tr>\n <tr>\n <th>45238835</th>\n <td>1</td>\n <td>45239952.0</td>\n <td>2017-07-21T13:23:56.527</td>\n <td>4</td>\n <td>1191</td>\n <td><p>I'm on Django 1.9, Python 3.6. I made this...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>Django failing migration - Cannot query \"peter...</td>\n <td><python><django><migration><django-migrations></td>\n <td>1</td>\n <td>4</td>\n <td>NaN</td>\n <td>None</td>\n <td>CC BY-SA 3.0</td>\n <td>None</td>\n </tr>\n </tbody>\n</table>\n<p>105 rows × 18 columns</p>\n</div>"
+ },
+ "execution_count": 18,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "questions_df = pd.read_sql_query(f\"\"\"\n",
+ " SELECT *\n",
+ " FROM Post\n",
+ " WHERE Tags LIKE '%python%' AND (PostTypeId = 1) AND ((LastEditorUserId = {user_id}) OR (OwnerUserId = {user_id}))\n",
+ "\"\"\", db)\n",
+ "questions_df.set_index('PostId', inplace=True)\n",
+ "questions_df"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 19,
+ "outputs": [
+ {
+ "data": {
+ "text/plain": " Tags PostTypeId \\\nPostId \n6930808 <python><django><django-models><django-admin><... 2 \n45239952 <python><django><migration><django-migrations> 2 \n74335 <python><amazon> 2 \n94627 <python><user-interface><api> 2 \n109724 <python><excel><xlwt><pyexcelerator> 2 \n207065 <python><ajax><screen-scraping><beautifulsoup> 2 \n207074 <python><soap><soap-client> 2 \n224014 <python><ruby><perl><text-parsing> 2 \n273994 <python><programming-languages><python-3.x> 2 \n302681 <python><simplehttpserver><embeddedwebserver> 2 \n338929 <python><indentation> 2 \n350913 <python><django><django-forms> 2 \n368859 <python><unicode><ascii><encode> 2 \n562280 <python><excel-2007> 2 \n1166398 <python><newline><word-wrap> 2 \n1423207 <python><frameworks><cgi><nearlyfreespeech> 2 \n2726298 <python><xlwt><xlrd> 2 \n2883732 <python><sql-server><pyodbc><django-pyodbc> 2 \n2973884 <python><windows><winapi><popen><long-running-... 2 \n2974177 <python><windows><winapi><popen><long-running-... 2 \n3322769 <python><sqlalchemy><orm> 2 \n3364841 <python><session><timeout><sqlalchemy> 2 \n3740202 <python><dictionary> 2 \n5037673 <python><serialization><pickle><inverted-index> 2 \n5486539 <python><django><django-models><django-admin> 2 \n5501441 <python><xpath><elementtree> 2 \n5517355 <python><django><django-models> 2 \n5539724 <python><django><django-models> 2 \n5912867 <python><apache><mod-wsgi><redhat><setuptools> 2 \n5979034 <python><django><django-models><django-admin> 2 \n6507098 <python><django><django-models><django-admin><... 2 \n7097823 <python><django><django-models> 2 \n7323959 <python><popen><subprocess> 2 \n7999028 <python><linux><multithreading><threadpool> 2 \n10047815 <python><django> 2 \n21140430 <python><jdbc><jpype><jaydebeapi> 2 \n23349566 <python><rpy2> 2 \n29807514 <python><curl><python-requests> 2 \n31146549 <python><flask><uwsgi> 2 \n31164662 <python><mongodb><uwsgi><mlab><pymongo-3.x> 2 \n31482430 <python><nginx><flask><memcached><uwsgi> 2 \n31516660 <python><memcached><libmemcached><pylibmc> 2 \n32564909 <python><computer-vision><scikit-image><canny-... 2 \n33284974 <python><oracle><macos><cx-oracle><osx-elcapitan> 2 \n35611090 <python><django><celery><django-celery> 2 \n36922809 <python><static-methods><python-decorators><fu... 2 \n37288365 <python><python-2.7><unicode><subprocess> 2 \n41470962 <python><logging> 2 \n44950763 <python><django><django-models><django-authent... 2 \n\n AcceptedAnswerId CreationDate Score ViewCount \\\nPostId \n6930808 None 2011-08-03T17:45:24.243 1 None \n45239952 None 2017-07-21T14:15:08.280 6 None \n74335 None 2008-09-16T16:40:08.743 2 None \n94627 None 2008-09-18T17:21:42.810 3 None \n109724 None 2008-09-20T23:10:13.863 2 None \n207065 None 2008-10-16T00:58:10.813 0 None \n207074 None 2008-10-16T01:00:24.800 1 None \n224014 None 2008-10-22T00:03:23.323 5 None \n273994 None 2008-11-07T23:29:44.590 4 None \n302681 None 2008-11-19T17:21:06.677 0 None \n338929 None 2008-12-03T22:10:01.007 16 None \n350913 None 2008-12-08T21:12:56.517 40 None \n368859 None 2008-12-15T16:10:11.413 -3 None \n562280 None 2009-02-18T18:28:00.267 0 None \n1166398 None 2009-07-22T16:09:25.197 1 None \n1423207 None 2009-09-14T18:34:18.867 2 None \n2726298 None 2010-04-28T01:30:54.397 263 None \n2883732 None 2010-05-21T16:21:27.240 10 None \n2973884 None 2010-06-04T12:04:23.607 1 None \n2974177 None 2010-06-04T12:41:24.323 7 None \n3322769 None 2010-07-23T22:11:43.417 42 None \n3364841 None 2010-07-29T16:31:24.073 56 None \n3740202 None 2010-09-18T02:57:15.853 7 None \n5037673 None 2011-02-18T04:37:27.133 0 None \n5486539 None 2011-03-30T12:54:01.637 0 None \n5501441 None 2011-03-31T14:27:50.847 56 None \n5517355 None 2011-04-01T18:30:31.930 3 None \n5539724 None 2011-04-04T14:12:30.027 1 None \n5912867 None 2011-05-06T14:28:54.537 0 None \n5979034 None 2011-05-12T13:51:05.513 -2 None \n6507098 None 2011-06-28T13:20:49.480 0 None \n7097823 None 2011-08-17T18:45:06.860 3 None \n7323959 None 2011-09-06T17:45:14.537 8 None \n7999028 None 2011-11-03T17:09:51.260 0 None \n10047815 None 2012-04-06T18:46:30.720 1 None \n21140430 None 2014-01-15T14:44:21.213 5 None \n23349566 None 2014-04-28T19:26:54.797 0 None \n29807514 None 2015-04-22T19:53:07.763 0 None \n31146549 None 2015-06-30T19:13:43.577 7 None \n31164662 None 2015-07-01T14:47:11.400 14 None \n31482430 None 2015-07-17T18:30:07.053 0 None \n31516660 None 2015-07-20T12:34:33.923 0 None \n32564909 None 2015-09-14T12:31:51.097 1 None \n33284974 None 2015-10-22T15:36:24.507 0 None \n35611090 None 2016-02-24T19:18:36.617 0 None \n36922809 None 2016-04-28T18:32:49.863 2 None \n37288365 None 2016-05-18T00:36:59.467 1 None \n41470962 None 2017-01-04T18:37:01.457 1 None \n44950763 None 2017-07-06T13:45:42.037 2 None \n\n Body OwnerUserId \\\nPostId \n6930808 <p>Well, here's a work around since I can't fi... 13009 \n45239952 <p>Looks like I just needed to get User the sa... 13009 \n74335 <p>pyaws seems to be the best one out there. ... 13009 \n94627 <p><a href=\"http://pythoncard.sourceforge.net/... 13009 \n109724 <p>Found example here: <a href=\"http://www.ans... 13009 \n207065 <p>This seems like it's a pretty common proble... 13009 \n207074 <p>As I suggested <a href=\"https://stackoverfl... 13009 \n224014 <p><a href=\"http://pyparsing.wikispaces.com/\" ... 13009 \n273994 <p>Wouldn't VB6 to VB.net be the biggest examp... 13009 \n302681 <p>I made this one. <a href=\"http://www.blend... 13009 \n338929 <p>Python includes a script for the opposite (... 13009 \n350913 <p>I went ahead and answered my own question. ... 13009 \n368859 <p>This seems to work:</p>\\n\\n<pre><code>'add ... 13009 \n562280 <p>May I humbly suggest my site; <a href=\"http... 13009 \n1166398 <p>It looks like it doesn't support that. Thi... 13009 \n1423207 <p>I got web.py to work on nearly free speech ... 13009 \n2726298 <p>Here's some sample code I used recently to ... 13009 \n2883732 <p>Sorry, I asked too soon, <a href=\"http://co... 13009 \n2973884 <p>This almost works (<a href=\"http://docs.pyt... 13009 \n2974177 <p>Ok, I finally figured this out! This seems... 13009 \n3322769 <p>Ok I found it after further searching:</p>\\... 13009 \n3364841 <p>Whenever you create a new session in your c... 13009 \n3740202 <p>What you're describing in your edit is how ... 13009 \n5037673 <p>There's the other pickle library you could ... 13009 \n5486539 <p>What I did to fix this is I dropped every t... 13009 \n5501441 <p>Turns out I needed to say <code>target.find... 13009 \n5517355 <p>Ahh, found it in another SO answer. Weird ... 13009 \n5539724 <p><code>__init__.py</code> in my project's di... 13009 \n5912867 <p>Oh well, instead of fooling with that, I to... 13009 \n5979034 <p><a href=\"http://www.answermysearches.com/fi... 13009 \n6507098 <p>Ok, as a workaround I ended up defining a <... 13009 \n7097823 <p>get_or_create sounds busted to me. I'm jus... 13009 \n7323959 <p>Ok, I'm not sure why but this seems to work... 13009 \n7999028 <p>Actually this does seem to be working. I s... 13009 \n10047815 <p><a href=\"https://stackoverflow.com/question... 13009 \n21140430 <p>Ok, thanks to eltabo and Juan Mellado I fig... 13009 \n23349566 <p>So I was trying to install this on a networ... 13009 \n29807514 <p>Ok, changing to response.content fixed it. ... 13009 \n31146549 <p>Ok, @ipinak was on the right track. It loo... 13009 \n31164662 <p>I fixed it for myself by downgrading from p... 13009 \n31482430 <p>This isn't a great answer, but I ended up u... 13009 \n31516660 <p>As far as I can tell it seems to work fine ... 13009 \n32564909 <p>So the issue was with the canny function re... 13009 \n33284974 <p>I think I fixed it. Basically everything i... 13009 \n35611090 <p>After tooling around for a while and trying... 13009 \n36922809 <p>There's probably a smarter way to do it but... 13009 \n37288365 <p>Wow, this was the weirdest issue ever but I... 13009 \n41470962 <p>Here's what I ended up going with. But I'm... 13009 \n44950763 <p>As @adrien mentioned in the comment, that w... 13009 \n\n LastEditorUserId LastEditorDisplayName LastEditDate \\\nPostId \n6930808 13009.0 None 2011-08-04T11:44:00.257 \n45239952 13009.0 None 2017-07-21T19:13:22.417 \n74335 NaN None None \n94627 216356.0 None 2012-08-09T19:47:56.843 \n109724 NaN None None \n207065 NaN None None \n207074 -1.0 None 2017-05-23T12:34:59.060 \n224014 NaN None None \n273994 NaN None None \n302681 NaN None None \n338929 NaN None None \n350913 NaN None None \n368859 NaN None None \n562280 NaN None None \n1166398 NaN None None \n1423207 NaN None None \n2726298 3801587.0 None 2019-11-04T13:44:52.230 \n2883732 NaN None None \n2973884 NaN None None \n2974177 726378.0 None 2017-07-28T04:22:46.813 \n3322769 NaN None None \n3364841 972208.0 None 2012-03-18T02:57:48.600 \n3740202 NaN None None \n5037673 NaN None None \n5486539 NaN None None \n5501441 3820025.0 None 2018-12-19T15:54:38.900 \n5517355 NaN None None \n5539724 NaN None None \n5912867 NaN None None \n5979034 NaN None None \n6507098 NaN None None \n7097823 NaN None None \n7323959 NaN None None \n7999028 NaN None None \n10047815 -1.0 None 2017-05-23T10:34:38.073 \n21140430 NaN None None \n23349566 NaN None None \n29807514 NaN None None \n31146549 NaN None None \n31164662 NaN None None \n31482430 NaN None None \n31516660 NaN None None \n32564909 NaN None None \n33284974 NaN None None \n35611090 NaN None None \n36922809 NaN None None \n37288365 -1.0 None 2017-05-23T11:44:09.133 \n41470962 NaN None None \n44950763 NaN None None \n\n Title AnswerCount CommentCount FavoriteCount \\\nPostId \n6930808 None None 0 None \n45239952 None None 0 None \n74335 None None 0 None \n94627 None None 1 None \n109724 None None 1 None \n207065 None None 1 None \n207074 None None 0 None \n224014 None None 0 None \n273994 None None 3 None \n302681 None None 0 None \n338929 None None 2 None \n350913 None None 2 None \n368859 None None 5 None \n562280 None None 0 None \n1166398 None None 0 None \n1423207 None None 0 None \n2726298 None None 5 None \n2883732 None None 0 None \n2973884 None None 0 None \n2974177 None None 3 None \n3322769 None None 2 None \n3364841 None None 4 None \n3740202 None None 0 None \n5037673 None None 0 None \n5486539 None None 0 None \n5501441 None None 2 None \n5517355 None None 0 None \n5539724 None None 0 None \n5912867 None None 0 None \n5979034 None None 0 None \n6507098 None None 0 None \n7097823 None None 0 None \n7323959 None None 2 None \n7999028 None None 0 None \n10047815 None None 2 None \n21140430 None None 3 None \n23349566 None None 0 None \n29807514 None None 3 None \n31146549 None None 0 None \n31164662 None None 3 None \n31482430 None None 0 None \n31516660 None None 0 None \n32564909 None None 1 None \n33284974 None None 0 None \n35611090 None None 0 None \n36922809 None None 0 None \n37288365 None None 1 None \n41470962 None None 0 None \n44950763 None None 0 None \n\n CommunityOwnedDate ContentLicense ParentId \nPostId \n6930808 None CC BY-SA 3.0 6913166 \n45239952 None CC BY-SA 3.0 45238835 \n74335 None CC BY-SA 2.5 48884 \n94627 None CC BY-SA 3.0 93930 \n109724 None CC BY-SA 2.5 108134 \n207065 None CC BY-SA 2.5 206855 \n207074 None CC BY-SA 2.5 206154 \n224014 None CC BY-SA 2.5 223866 \n273994 None CC BY-SA 2.5 273524 \n302681 None CC BY-SA 2.5 302615 \n338929 None CC BY-SA 2.5 338767 \n350913 2008-12-08T21:12:56.517 CC BY-SA 2.5 350799 \n368859 None CC BY-SA 2.5 368805 \n562280 None CC BY-SA 2.5 556967 \n1166398 None CC BY-SA 2.5 1166317 \n1423207 None CC BY-SA 2.5 1423041 \n2726298 None CC BY-SA 4.0 2725852 \n2883732 None CC BY-SA 2.5 2883722 \n2973884 None CC BY-SA 2.5 2970045 \n2974177 None CC BY-SA 3.0 2970045 \n3322769 None CC BY-SA 2.5 3322337 \n3364841 None CC BY-SA 3.0 3360951 \n3740202 None CC BY-SA 2.5 3738381 \n5037673 None CC BY-SA 2.5 5037432 \n5486539 None CC BY-SA 2.5 5486018 \n5501441 None CC BY-SA 4.0 5501118 \n5517355 None CC BY-SA 2.5 5517314 \n5539724 None CC BY-SA 2.5 5538814 \n5912867 None CC BY-SA 3.0 5912701 \n5979034 None CC BY-SA 3.0 5486018 \n6507098 None CC BY-SA 3.0 6497882 \n7097823 None CC BY-SA 3.0 7097475 \n7323959 None CC BY-SA 3.0 7323859 \n7999028 None CC BY-SA 3.0 7998850 \n10047815 None CC BY-SA 3.0 10047387 \n21140430 2014-01-15T14:44:21.213 CC BY-SA 3.0 21027904 \n23349566 None CC BY-SA 3.0 23346270 \n29807514 None CC BY-SA 3.0 29807249 \n31146549 None CC BY-SA 3.0 31146007 \n31164662 None CC BY-SA 3.0 31030307 \n31482430 None CC BY-SA 3.0 31478409 \n31516660 None CC BY-SA 3.0 31482138 \n32564909 None CC BY-SA 3.0 32529149 \n33284974 None CC BY-SA 3.0 33259671 \n35611090 None CC BY-SA 3.0 35603707 \n36922809 None CC BY-SA 3.0 36922532 \n37288365 None CC BY-SA 3.0 37245595 \n41470962 None CC BY-SA 3.0 41467032 \n44950763 None CC BY-SA 3.0 44933724 ",
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</thead>\n <tbody>\n <tr>\n <th>6930808</th>\n <td><python><django><django-models><django-admin><...</td>\n <td>2</td>\n <td>None</td>\n <td>2011-08-03T17:45:24.243</td>\n <td>1</td>\n <td>None</td>\n <td><p>Well, here's a work around since I can't fi...</td>\n <td>13009</td>\n <td>13009.0</td>\n <td>None</td>\n <td>2011-08-04T11:44:00.257</td>\n <td>None</td>\n <td>None</td>\n <td>0</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 3.0</td>\n <td>6913166</td>\n </tr>\n <tr>\n <th>45239952</th>\n <td><python><django><migration><django-migrations></td>\n <td>2</td>\n <td>None</td>\n <td>2017-07-21T14:15:08.280</td>\n <td>6</td>\n <td>None</td>\n <td><p>Looks like I just needed to get User the sa...</td>\n <td>13009</td>\n <td>13009.0</td>\n <td>None</td>\n <td>2017-07-21T19:13:22.417</td>\n <td>None</td>\n <td>None</td>\n <td>0</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 3.0</td>\n <td>45238835</td>\n </tr>\n <tr>\n <th>74335</th>\n <td><python><amazon></td>\n <td>2</td>\n <td>None</td>\n <td>2008-09-16T16:40:08.743</td>\n <td>2</td>\n <td>None</td>\n <td><p>pyaws seems to be the best one out there. ...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>0</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>48884</td>\n </tr>\n <tr>\n <th>94627</th>\n <td><python><user-interface><api></td>\n <td>2</td>\n <td>None</td>\n <td>2008-09-18T17:21:42.810</td>\n <td>3</td>\n <td>None</td>\n <td><p><a href=\"http://pythoncard.sourceforge.net/...</td>\n <td>13009</td>\n <td>216356.0</td>\n <td>None</td>\n <td>2012-08-09T19:47:56.843</td>\n <td>None</td>\n <td>None</td>\n <td>1</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 3.0</td>\n <td>93930</td>\n </tr>\n <tr>\n <th>109724</th>\n <td><python><excel><xlwt><pyexcelerator></td>\n <td>2</td>\n <td>None</td>\n <td>2008-09-20T23:10:13.863</td>\n <td>2</td>\n <td>None</td>\n <td><p>Found example here: <a href=\"http://www.ans...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>1</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>108134</td>\n </tr>\n <tr>\n <th>207065</th>\n <td><python><ajax><screen-scraping><beautifulsoup></td>\n <td>2</td>\n <td>None</td>\n <td>2008-10-16T00:58:10.813</td>\n <td>0</td>\n <td>None</td>\n <td><p>This seems like it's a pretty common proble...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>1</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>206855</td>\n </tr>\n <tr>\n <th>207074</th>\n <td><python><soap><soap-client></td>\n <td>2</td>\n <td>None</td>\n <td>2008-10-16T01:00:24.800</td>\n <td>1</td>\n <td>None</td>\n <td><p>As I suggested <a href=\"https://stackoverfl...</td>\n <td>13009</td>\n <td>-1.0</td>\n <td>None</td>\n <td>2017-05-23T12:34:59.060</td>\n <td>None</td>\n <td>None</td>\n <td>0</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>206154</td>\n </tr>\n <tr>\n <th>224014</th>\n <td><python><ruby><perl><text-parsing></td>\n <td>2</td>\n <td>None</td>\n <td>2008-10-22T00:03:23.323</td>\n <td>5</td>\n <td>None</td>\n <td><p><a href=\"http://pyparsing.wikispaces.com/\" ...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>0</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>223866</td>\n </tr>\n <tr>\n <th>273994</th>\n <td><python><programming-languages><python-3.x></td>\n <td>2</td>\n <td>None</td>\n <td>2008-11-07T23:29:44.590</td>\n <td>4</td>\n <td>None</td>\n <td><p>Wouldn't VB6 to VB.net be the biggest examp...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>3</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>273524</td>\n </tr>\n <tr>\n <th>302681</th>\n <td><python><simplehttpserver><embeddedwebserver></td>\n <td>2</td>\n <td>None</td>\n <td>2008-11-19T17:21:06.677</td>\n <td>0</td>\n <td>None</td>\n <td><p>I made this one. <a href=\"http://www.blend...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>0</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>302615</td>\n </tr>\n <tr>\n <th>338929</th>\n <td><python><indentation></td>\n <td>2</td>\n <td>None</td>\n <td>2008-12-03T22:10:01.007</td>\n <td>16</td>\n <td>None</td>\n <td><p>Python includes a script for the opposite (...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>2</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>338767</td>\n </tr>\n <tr>\n <th>350913</th>\n <td><python><django><django-forms></td>\n <td>2</td>\n <td>None</td>\n <td>2008-12-08T21:12:56.517</td>\n <td>40</td>\n <td>None</td>\n <td><p>I went ahead and answered my own question. ...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>2</td>\n <td>None</td>\n <td>2008-12-08T21:12:56.517</td>\n <td>CC BY-SA 2.5</td>\n <td>350799</td>\n </tr>\n <tr>\n <th>368859</th>\n <td><python><unicode><ascii><encode></td>\n <td>2</td>\n <td>None</td>\n <td>2008-12-15T16:10:11.413</td>\n <td>-3</td>\n <td>None</td>\n <td><p>This seems to work:</p>\\n\\n<pre><code>'add ...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>5</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>368805</td>\n </tr>\n <tr>\n <th>562280</th>\n <td><python><excel-2007></td>\n <td>2</td>\n <td>None</td>\n <td>2009-02-18T18:28:00.267</td>\n <td>0</td>\n <td>None</td>\n <td><p>May I humbly suggest my site; <a href=\"http...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>0</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>556967</td>\n </tr>\n <tr>\n <th>1166398</th>\n <td><python><newline><word-wrap></td>\n <td>2</td>\n <td>None</td>\n <td>2009-07-22T16:09:25.197</td>\n <td>1</td>\n <td>None</td>\n <td><p>It looks like it doesn't support that. Thi...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>0</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>1166317</td>\n </tr>\n <tr>\n <th>1423207</th>\n <td><python><frameworks><cgi><nearlyfreespeech></td>\n <td>2</td>\n <td>None</td>\n <td>2009-09-14T18:34:18.867</td>\n <td>2</td>\n <td>None</td>\n <td><p>I got web.py to work on nearly free speech ...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>0</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>1423041</td>\n </tr>\n <tr>\n <th>2726298</th>\n <td><python><xlwt><xlrd></td>\n <td>2</td>\n <td>None</td>\n <td>2010-04-28T01:30:54.397</td>\n <td>263</td>\n <td>None</td>\n <td><p>Here's some sample code I used recently to ...</td>\n <td>13009</td>\n <td>3801587.0</td>\n <td>None</td>\n <td>2019-11-04T13:44:52.230</td>\n <td>None</td>\n <td>None</td>\n <td>5</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 4.0</td>\n <td>2725852</td>\n </tr>\n <tr>\n <th>2883732</th>\n <td><python><sql-server><pyodbc><django-pyodbc></td>\n <td>2</td>\n <td>None</td>\n <td>2010-05-21T16:21:27.240</td>\n <td>10</td>\n <td>None</td>\n <td><p>Sorry, I asked too soon, <a href=\"http://co...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>0</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>2883722</td>\n </tr>\n <tr>\n <th>2973884</th>\n <td><python><windows><winapi><popen><long-running-...</td>\n <td>2</td>\n <td>None</td>\n <td>2010-06-04T12:04:23.607</td>\n <td>1</td>\n <td>None</td>\n <td><p>This almost works (<a href=\"http://docs.pyt...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>0</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>2970045</td>\n </tr>\n <tr>\n <th>2974177</th>\n <td><python><windows><winapi><popen><long-running-...</td>\n <td>2</td>\n <td>None</td>\n <td>2010-06-04T12:41:24.323</td>\n <td>7</td>\n <td>None</td>\n <td><p>Ok, I finally figured this out! This seems...</td>\n <td>13009</td>\n <td>726378.0</td>\n <td>None</td>\n <td>2017-07-28T04:22:46.813</td>\n <td>None</td>\n <td>None</td>\n <td>3</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 3.0</td>\n <td>2970045</td>\n </tr>\n <tr>\n <th>3322769</th>\n <td><python><sqlalchemy><orm></td>\n <td>2</td>\n <td>None</td>\n <td>2010-07-23T22:11:43.417</td>\n <td>42</td>\n <td>None</td>\n <td><p>Ok I found it after further searching:</p>\\...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>2</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>3322337</td>\n </tr>\n <tr>\n <th>3364841</th>\n <td><python><session><timeout><sqlalchemy></td>\n <td>2</td>\n <td>None</td>\n <td>2010-07-29T16:31:24.073</td>\n <td>56</td>\n <td>None</td>\n <td><p>Whenever you create a new session in your c...</td>\n <td>13009</td>\n <td>972208.0</td>\n <td>None</td>\n <td>2012-03-18T02:57:48.600</td>\n <td>None</td>\n <td>None</td>\n <td>4</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 3.0</td>\n <td>3360951</td>\n </tr>\n <tr>\n <th>3740202</th>\n <td><python><dictionary></td>\n <td>2</td>\n <td>None</td>\n <td>2010-09-18T02:57:15.853</td>\n <td>7</td>\n <td>None</td>\n <td><p>What you're describing in your edit is how ...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>0</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>3738381</td>\n </tr>\n <tr>\n <th>5037673</th>\n <td><python><serialization><pickle><inverted-index></td>\n <td>2</td>\n <td>None</td>\n <td>2011-02-18T04:37:27.133</td>\n <td>0</td>\n <td>None</td>\n <td><p>There's the other pickle library you could ...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>0</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>5037432</td>\n </tr>\n <tr>\n <th>5486539</th>\n <td><python><django><django-models><django-admin></td>\n <td>2</td>\n <td>None</td>\n <td>2011-03-30T12:54:01.637</td>\n <td>0</td>\n <td>None</td>\n <td><p>What I did to fix this is I dropped every t...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>0</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>5486018</td>\n </tr>\n <tr>\n <th>5501441</th>\n <td><python><xpath><elementtree></td>\n <td>2</td>\n <td>None</td>\n <td>2011-03-31T14:27:50.847</td>\n <td>56</td>\n <td>None</td>\n <td><p>Turns out I needed to say <code>target.find...</td>\n <td>13009</td>\n <td>3820025.0</td>\n <td>None</td>\n <td>2018-12-19T15:54:38.900</td>\n <td>None</td>\n <td>None</td>\n <td>2</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 4.0</td>\n <td>5501118</td>\n </tr>\n <tr>\n <th>5517355</th>\n <td><python><django><django-models></td>\n <td>2</td>\n <td>None</td>\n <td>2011-04-01T18:30:31.930</td>\n <td>3</td>\n <td>None</td>\n <td><p>Ahh, found it in another SO answer. Weird ...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>0</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>5517314</td>\n </tr>\n <tr>\n <th>5539724</th>\n <td><python><django><django-models></td>\n <td>2</td>\n <td>None</td>\n <td>2011-04-04T14:12:30.027</td>\n <td>1</td>\n <td>None</td>\n <td><p><code>__init__.py</code> in my project's di...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>0</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 2.5</td>\n <td>5538814</td>\n </tr>\n <tr>\n <th>5912867</th>\n <td><python><apache><mod-wsgi><redhat><setuptools></td>\n <td>2</td>\n <td>None</td>\n <td>2011-05-06T14:28:54.537</td>\n <td>0</td>\n <td>None</td>\n <td><p>Oh well, instead of fooling with that, I to...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>0</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 3.0</td>\n <td>5912701</td>\n </tr>\n <tr>\n <th>5979034</th>\n <td><python><django><django-models><django-admin></td>\n <td>2</td>\n <td>None</td>\n <td>2011-05-12T13:51:05.513</td>\n <td>-2</td>\n <td>None</td>\n <td><p><a href=\"http://www.answermysearches.com/fi...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>0</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 3.0</td>\n <td>5486018</td>\n </tr>\n <tr>\n <th>6507098</th>\n <td><python><django><django-models><django-admin><...</td>\n <td>2</td>\n <td>None</td>\n <td>2011-06-28T13:20:49.480</td>\n <td>0</td>\n <td>None</td>\n <td><p>Ok, as a workaround I ended up defining a <...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>0</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 3.0</td>\n <td>6497882</td>\n </tr>\n <tr>\n <th>7097823</th>\n <td><python><django><django-models></td>\n <td>2</td>\n <td>None</td>\n <td>2011-08-17T18:45:06.860</td>\n <td>3</td>\n <td>None</td>\n <td><p>get_or_create sounds busted to me. I'm jus...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>0</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 3.0</td>\n <td>7097475</td>\n </tr>\n <tr>\n <th>7323959</th>\n <td><python><popen><subprocess></td>\n <td>2</td>\n <td>None</td>\n <td>2011-09-06T17:45:14.537</td>\n <td>8</td>\n <td>None</td>\n <td><p>Ok, I'm not sure why but this seems to work...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>2</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 3.0</td>\n <td>7323859</td>\n </tr>\n <tr>\n <th>7999028</th>\n <td><python><linux><multithreading><threadpool></td>\n <td>2</td>\n <td>None</td>\n <td>2011-11-03T17:09:51.260</td>\n <td>0</td>\n <td>None</td>\n <td><p>Actually this does seem to be working. I s...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>0</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 3.0</td>\n <td>7998850</td>\n </tr>\n <tr>\n <th>10047815</th>\n <td><python><django></td>\n <td>2</td>\n <td>None</td>\n <td>2012-04-06T18:46:30.720</td>\n <td>1</td>\n <td>None</td>\n <td><p><a href=\"https://stackoverflow.com/question...</td>\n <td>13009</td>\n <td>-1.0</td>\n <td>None</td>\n <td>2017-05-23T10:34:38.073</td>\n <td>None</td>\n <td>None</td>\n <td>2</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 3.0</td>\n <td>10047387</td>\n </tr>\n <tr>\n <th>21140430</th>\n <td><python><jdbc><jpype><jaydebeapi></td>\n <td>2</td>\n <td>None</td>\n <td>2014-01-15T14:44:21.213</td>\n <td>5</td>\n <td>None</td>\n <td><p>Ok, thanks to eltabo and Juan Mellado I fig...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>3</td>\n <td>None</td>\n <td>2014-01-15T14:44:21.213</td>\n <td>CC BY-SA 3.0</td>\n <td>21027904</td>\n </tr>\n <tr>\n <th>23349566</th>\n <td><python><rpy2></td>\n <td>2</td>\n <td>None</td>\n <td>2014-04-28T19:26:54.797</td>\n <td>0</td>\n <td>None</td>\n <td><p>So I was trying to install this on a networ...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>0</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 3.0</td>\n <td>23346270</td>\n </tr>\n <tr>\n <th>29807514</th>\n <td><python><curl><python-requests></td>\n <td>2</td>\n <td>None</td>\n <td>2015-04-22T19:53:07.763</td>\n <td>0</td>\n <td>None</td>\n <td><p>Ok, changing to response.content fixed it. ...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>3</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 3.0</td>\n <td>29807249</td>\n </tr>\n <tr>\n <th>31146549</th>\n <td><python><flask><uwsgi></td>\n <td>2</td>\n <td>None</td>\n <td>2015-06-30T19:13:43.577</td>\n <td>7</td>\n <td>None</td>\n <td><p>Ok, @ipinak was on the right track. It loo...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>0</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 3.0</td>\n <td>31146007</td>\n </tr>\n <tr>\n <th>31164662</th>\n <td><python><mongodb><uwsgi><mlab><pymongo-3.x></td>\n <td>2</td>\n <td>None</td>\n <td>2015-07-01T14:47:11.400</td>\n <td>14</td>\n <td>None</td>\n <td><p>I fixed it for myself by downgrading from p...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>3</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 3.0</td>\n <td>31030307</td>\n </tr>\n <tr>\n <th>31482430</th>\n <td><python><nginx><flask><memcached><uwsgi></td>\n <td>2</td>\n <td>None</td>\n <td>2015-07-17T18:30:07.053</td>\n <td>0</td>\n <td>None</td>\n <td><p>This isn't a great answer, but I ended up u...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>0</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 3.0</td>\n <td>31478409</td>\n </tr>\n <tr>\n <th>31516660</th>\n <td><python><memcached><libmemcached><pylibmc></td>\n <td>2</td>\n <td>None</td>\n <td>2015-07-20T12:34:33.923</td>\n <td>0</td>\n <td>None</td>\n <td><p>As far as I can tell it seems to work fine ...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>0</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 3.0</td>\n <td>31482138</td>\n </tr>\n <tr>\n <th>32564909</th>\n <td><python><computer-vision><scikit-image><canny-...</td>\n <td>2</td>\n <td>None</td>\n <td>2015-09-14T12:31:51.097</td>\n <td>1</td>\n <td>None</td>\n <td><p>So the issue was with the canny function re...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>1</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 3.0</td>\n <td>32529149</td>\n </tr>\n <tr>\n <th>33284974</th>\n <td><python><oracle><macos><cx-oracle><osx-elcapitan></td>\n <td>2</td>\n <td>None</td>\n <td>2015-10-22T15:36:24.507</td>\n <td>0</td>\n <td>None</td>\n <td><p>I think I fixed it. Basically everything i...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>0</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 3.0</td>\n <td>33259671</td>\n </tr>\n <tr>\n <th>35611090</th>\n <td><python><django><celery><django-celery></td>\n <td>2</td>\n <td>None</td>\n <td>2016-02-24T19:18:36.617</td>\n <td>0</td>\n <td>None</td>\n <td><p>After tooling around for a while and trying...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>0</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 3.0</td>\n <td>35603707</td>\n </tr>\n <tr>\n <th>36922809</th>\n <td><python><static-methods><python-decorators><fu...</td>\n <td>2</td>\n <td>None</td>\n <td>2016-04-28T18:32:49.863</td>\n <td>2</td>\n <td>None</td>\n <td><p>There's probably a smarter way to do it but...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>0</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 3.0</td>\n <td>36922532</td>\n </tr>\n <tr>\n <th>37288365</th>\n <td><python><python-2.7><unicode><subprocess></td>\n <td>2</td>\n <td>None</td>\n <td>2016-05-18T00:36:59.467</td>\n <td>1</td>\n <td>None</td>\n <td><p>Wow, this was the weirdest issue ever but I...</td>\n <td>13009</td>\n <td>-1.0</td>\n <td>None</td>\n <td>2017-05-23T11:44:09.133</td>\n <td>None</td>\n <td>None</td>\n <td>1</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 3.0</td>\n <td>37245595</td>\n </tr>\n <tr>\n <th>41470962</th>\n <td><python><logging></td>\n <td>2</td>\n <td>None</td>\n <td>2017-01-04T18:37:01.457</td>\n <td>1</td>\n <td>None</td>\n <td><p>Here's what I ended up going with. But I'm...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>0</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 3.0</td>\n <td>41467032</td>\n </tr>\n <tr>\n <th>44950763</th>\n <td><python><django><django-models><django-authent...</td>\n <td>2</td>\n <td>None</td>\n <td>2017-07-06T13:45:42.037</td>\n <td>2</td>\n <td>None</td>\n <td><p>As @adrien mentioned in the comment, that w...</td>\n <td>13009</td>\n <td>NaN</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>None</td>\n <td>0</td>\n <td>None</td>\n <td>None</td>\n <td>CC BY-SA 3.0</td>\n <td>44933724</td>\n </tr>\n </tbody>\n</table>\n</div>"
+ },
+ "execution_count": 19,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "answers_df = pd.read_sql_query(f\"\"\"\n",
+ " SELECT A.Tags, B.*\n",
+ " FROM Post A\n",
+ " INNER JOIN Post B ON (B.ParentId = A.PostId) AND (B.ParentId IS NOT NULL)\n",
+ " WHERE A.Tags LIKE '%python%' AND (B.PostTypeId = 2) AND ((B.LastEditorUserId = {user_id}) OR (B.OwnerUserId = {user_id}))\n",
+ "\"\"\", db)\n",
+ "answers_df = answers_df.loc[:,~answers_df.columns.duplicated()].copy()\n",
+ "answers_df.set_index('PostId', inplace=True)\n",
+ "answers_df"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 20,
+ "outputs": [
+ {
+ "data": {
+ "text/plain": " Tags PostId Score \\\nCommentId \n857928 <python><subprocess><pipe><echo><popen> 1046474 0 \n1513319 <python><django><forms><django-forms> 1640204 0 \n3029786 <python><windows><winapi><popen><long-running-... 2970045 0 \n3421734 <python><permissions><authorization><decorator... 3302844 0 \n6330991 <python><django><django-models><decimal><scien... 5566121 0 \n6331285 <python><django><django-models><decimal><scien... 5566121 0 \n6774887 <python><database><migration><django-south> 5833418 4 \n8234046 <python><django><django-models><django-admin><... 6913166 1 \n8234115 <python><string-formatting><number-formatting>... 6913532 32 \n8235637 <python><django><django-models><django-admin><... 6913166 0 \n8239108 <python><django><django-models><django-admin><... 6913166 0 \n8257824 <python><django><django-models><django-admin><... 6913166 0 \n8499177 <python><django><django-models> 7097475 0 \n10657798 <python><excel><xlwt> 8590741 0 \n10796244 <python><excel><xlwt> 8590741 0 \n11245320 <python> 8976324 0 \n11245634 <python> 8976324 0 \n12490216 <python><django><django-models><django-admin> 9806936 0 \n32554534 <python><django><django-forms><django-admin><d... 19807757 0 \n32567053 <python><django><django-forms><django-admin><d... 19807757 0 \n36034593 <python><numpy> 23497706 0 \n36034937 <python><numpy> 23497706 0 \n36041765 <python><numpy> 23500754 0 \n47738961 <python><python-requests> 29775247 1 \n47742802 <python><curl><python-requests> 29807249 0 \n47743040 <python><curl><python-requests> 29807249 0 \n48550940 <python><matplotlib> 30223161 0 \n48551405 <python><matplotlib> 30223161 0 \n50303593 <python><mongodb><uwsgi><mlab><pymongo-3.x> 31030307 2 \n50336702 <python><mongodb><uwsgi><mlab><pymongo-3.x> 31030307 1 \n50337057 <python><mongodb><uwsgi><mlab><pymongo-3.x> 31030307 0 \n50376360 <python><mongodb><uwsgi><mlab><pymongo-3.x> 31030307 0 \n54364203 <python><oracle><macos><cx-oracle><osx-elcapitan> 33259671 0 \n58665815 <python><django><celery><django-celery> 35486011 0 \n58894206 <python><django><celery><django-celery> 35603707 0 \n62020862 <python><python-2.7><unicode><subprocess> 37245595 0 \n62020942 <python><python-2.7><unicode><subprocess> 37245595 0 \n62020963 <python><python-2.7><unicode><subprocess> 37245595 0 \n68427097 <python><mocking><generator><python-unittest><... 40595679 0 \n70139817 <python><logging> 41467032 0 \n70435606 <python><postgresql><psycopg2><psycopg> 41616578 0 \n76846070 <python><django><django-models><django-authent... 44933724 0 \n77453798 <python><django><migration><django-migrations> 45238835 0 \n77456266 <python><django><migration><django-migrations> 45238835 0 \n80880518 <python><django> 46960782 0 \n\n Body \\\nCommentId \n857928 Yes, it runs from the windows dos console. \n1513319 lemonad, this would be at form creation time, ... \n3029786 Here are a few windows API commands that look ... \n3421734 I don't think I want to use anything built-in.... \n6330991 4.08E+13 has two decimal places, I'm allowing ... \n6331285 I followed those instructions. I've tried all... \n6774887 It's going to be pretty critical data, and hon... \n8234046 I'm thinking I need to make a custom model fie... \n8234115 nah, not at all. I wanted to separate this int... \n8235637 I'm not seeing much action on this thread. I ... \n8239108 I'm not seeing much action on the Django users... \n8257824 IRC seems to be down. No luck there either. \n8499177 @agf. I don't understand what the resolution ... \n10657798 Well, after playing around, the first number i... \n10796244 Thanks for the answers everyone. If anyone is... \n11245320 @Cameron, so you're saying something I import ... \n11245634 Thanks everyone. If anyone wants to post this... \n12490216 @jpic, that's interesting but it's probably ov... \n32554534 I'm coming across the exact same problem. I a... \n32567053 I put an updated question more inline with wha... \n36034593 I was thinking I could reference just the firs... \n36034937 hmm, I can access the first column with array[... \n36041765 hmm, I just ran the code from your answer. Do... \n47738961 @sigmavirus24, that's right I don't want to lo... \n47742802 Yeah, the requests.get step is instant, so I g... \n47743040 That was absolutely the issue. Thanks! Changi... \n48550940 Thanks for the suggestion. what does zlim do?... \n48551405 Thanks. I guess I don't understand what the h... \n50303593 I'm hitting this too on a similar setup. Did ... \n50336702 Want me to start a bounty? Would you be avail... \n50337057 Is this useful? http://blog.fejes.ca/?p=2496 ... \n50376360 Thanks Jesse, I guess we couldn't tell if it w... \n54364203 Thanks. I believe the fix_oralib.rb also does... \n58665815 @zsepi, I updated the question with those. \n58894206 It set's to write to a specified file, and ema... \n62020862 @tdelaney, did you try it on osx? It actually... \n62020942 I tried redirecting to a file and it still out... \n62020963 @tdelaney, I think you're right, it's probably... \n68427097 Good point. I took that line out. Same issue... \n70139817 I have 'A' and 'B' configured elsewhere to do ... \n70435606 I want to do everything in memory. All the do... \n76846070 Thanks. I didn't notice that. Taking it out ... \n77453798 I was wondering about that. But how would I c... \n77456266 That actually fixed my problem. \n80880518 @Jiaaro, thanks, but just tried it and no impr... \n\n CreationDate UserId ContentLicense \nCommentId \n857928 2009-06-25T22:15:13.437 13009 CC BY-SA 2.5 \n1513319 2009-10-29T12:44:20.160 13009 CC BY-SA 2.5 \n3029786 2010-06-03T22:10:42.643 13009 CC BY-SA 2.5 \n3421734 2010-07-21T19:14:03.313 13009 CC BY-SA 2.5 \n6330991 2011-04-06T12:26:33.123 13009 CC BY-SA 2.5 \n6331285 2011-04-06T12:43:15.377 13009 CC BY-SA 2.5 \n6774887 2011-05-04T20:00:35.997 13009 CC BY-SA 3.0 \n8234046 2011-08-02T14:23:53.283 13009 CC BY-SA 3.0 \n8234115 2011-08-02T14:26:37.263 13009 CC BY-SA 3.0 \n8235637 2011-08-02T15:36:12.527 13009 CC BY-SA 3.0 \n8239108 2011-08-02T18:48:59.337 13009 CC BY-SA 3.0 \n8257824 2011-08-03T16:59:56.540 13009 CC BY-SA 3.0 \n8499177 2011-08-17T18:43:55.627 13009 CC BY-SA 3.0 \n10657798 2011-12-21T15:30:22.113 13009 CC BY-SA 3.0 \n10796244 2011-12-30T19:08:28.063 13009 CC BY-SA 3.0 \n11245320 2012-01-23T18:14:14.870 13009 CC BY-SA 3.0 \n11245634 2012-01-23T18:28:32.813 13009 CC BY-SA 3.0 \n12490216 2012-03-21T15:00:45.163 13009 CC BY-SA 3.0 \n32554534 2014-02-04T15:05:23.023 13009 CC BY-SA 3.0 \n32567053 2014-02-04T20:26:56.147 13009 CC BY-SA 3.0 \n36034593 2014-05-06T14:42:07.190 13009 CC BY-SA 3.0 \n36034937 2014-05-06T14:49:57.347 13009 CC BY-SA 3.0 \n36041765 2014-05-06T17:47:18.563 13009 CC BY-SA 3.0 \n47738961 2015-04-22T18:04:58.213 13009 CC BY-SA 3.0 \n47742802 2015-04-22T19:45:33.083 13009 CC BY-SA 3.0 \n47743040 2015-04-22T19:52:21.247 13009 CC BY-SA 3.0 \n48550940 2015-05-13T19:22:13.533 13009 CC BY-SA 3.0 \n48551405 2015-05-13T19:36:25.690 13009 CC BY-SA 3.0 \n50303593 2015-06-30T19:18:02.697 13009 CC BY-SA 3.0 \n50336702 2015-07-01T14:27:34.823 13009 CC BY-SA 3.0 \n50337057 2015-07-01T14:35:16.503 13009 CC BY-SA 3.0 \n50376360 2015-07-02T13:09:14.617 13009 CC BY-SA 3.0 \n54364203 2015-10-22T13:16:49.317 13009 CC BY-SA 3.0 \n58665815 2016-02-18T15:55:59.940 13009 CC BY-SA 3.0 \n58894206 2016-02-24T14:29:13.990 13009 CC BY-SA 3.0 \n62020862 2016-05-16T03:06:55.457 13009 CC BY-SA 3.0 \n62020942 2016-05-16T03:13:12.050 13009 CC BY-SA 3.0 \n62020963 2016-05-16T03:14:39.700 13009 CC BY-SA 3.0 \n68427097 2016-11-14T18:52:50.053 13009 CC BY-SA 3.0 \n70139817 2017-01-04T15:15:07.183 13009 CC BY-SA 3.0 \n70435606 2017-01-12T15:37:23.967 13009 CC BY-SA 3.0 \n76846070 2017-07-05T20:00:37.840 13009 CC BY-SA 3.0 \n77453798 2017-07-21T17:54:41.707 13009 CC BY-SA 3.0 \n77456266 2017-07-21T19:11:37.543 13009 CC BY-SA 3.0 \n80880518 2017-10-27T02:20:12.973 13009 CC BY-SA 3.0 ",
+ "text/html": "<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>Tags</th>\n <th>PostId</th>\n <th>Score</th>\n <th>Body</th>\n <th>CreationDate</th>\n <th>UserId</th>\n <th>ContentLicense</th>\n </tr>\n <tr>\n <th>CommentId</th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>857928</th>\n <td><python><subprocess><pipe><echo><popen></td>\n <td>1046474</td>\n <td>0</td>\n <td>Yes, it runs from the windows dos console.</td>\n <td>2009-06-25T22:15:13.437</td>\n <td>13009</td>\n <td>CC BY-SA 2.5</td>\n </tr>\n <tr>\n <th>1513319</th>\n <td><python><django><forms><django-forms></td>\n <td>1640204</td>\n <td>0</td>\n <td>lemonad, this would be at form creation time, ...</td>\n <td>2009-10-29T12:44:20.160</td>\n <td>13009</td>\n <td>CC BY-SA 2.5</td>\n </tr>\n <tr>\n <th>3029786</th>\n <td><python><windows><winapi><popen><long-running-...</td>\n <td>2970045</td>\n <td>0</td>\n <td>Here are a few windows API commands that look ...</td>\n <td>2010-06-03T22:10:42.643</td>\n <td>13009</td>\n <td>CC BY-SA 2.5</td>\n </tr>\n <tr>\n <th>3421734</th>\n <td><python><permissions><authorization><decorator...</td>\n <td>3302844</td>\n <td>0</td>\n <td>I don't think I want to use anything built-in....</td>\n <td>2010-07-21T19:14:03.313</td>\n <td>13009</td>\n <td>CC BY-SA 2.5</td>\n </tr>\n <tr>\n <th>6330991</th>\n <td><python><django><django-models><decimal><scien...</td>\n <td>5566121</td>\n <td>0</td>\n <td>4.08E+13 has two decimal places, I'm allowing ...</td>\n <td>2011-04-06T12:26:33.123</td>\n <td>13009</td>\n <td>CC BY-SA 2.5</td>\n </tr>\n <tr>\n <th>6331285</th>\n <td><python><django><django-models><decimal><scien...</td>\n <td>5566121</td>\n <td>0</td>\n <td>I followed those instructions. I've tried all...</td>\n <td>2011-04-06T12:43:15.377</td>\n <td>13009</td>\n <td>CC BY-SA 2.5</td>\n </tr>\n <tr>\n <th>6774887</th>\n <td><python><database><migration><django-south></td>\n <td>5833418</td>\n <td>4</td>\n <td>It's going to be pretty critical data, and hon...</td>\n <td>2011-05-04T20:00:35.997</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>8234046</th>\n <td><python><django><django-models><django-admin><...</td>\n <td>6913166</td>\n <td>1</td>\n <td>I'm thinking I need to make a custom model fie...</td>\n <td>2011-08-02T14:23:53.283</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>8234115</th>\n <td><python><string-formatting><number-formatting>...</td>\n <td>6913532</td>\n <td>32</td>\n <td>nah, not at all. I wanted to separate this int...</td>\n <td>2011-08-02T14:26:37.263</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>8235637</th>\n <td><python><django><django-models><django-admin><...</td>\n <td>6913166</td>\n <td>0</td>\n <td>I'm not seeing much action on this thread. I ...</td>\n <td>2011-08-02T15:36:12.527</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>8239108</th>\n <td><python><django><django-models><django-admin><...</td>\n <td>6913166</td>\n <td>0</td>\n <td>I'm not seeing much action on the Django users...</td>\n <td>2011-08-02T18:48:59.337</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>8257824</th>\n <td><python><django><django-models><django-admin><...</td>\n <td>6913166</td>\n <td>0</td>\n <td>IRC seems to be down. No luck there either.</td>\n <td>2011-08-03T16:59:56.540</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>8499177</th>\n <td><python><django><django-models></td>\n <td>7097475</td>\n <td>0</td>\n <td>@agf. I don't understand what the resolution ...</td>\n <td>2011-08-17T18:43:55.627</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>10657798</th>\n <td><python><excel><xlwt></td>\n <td>8590741</td>\n <td>0</td>\n <td>Well, after playing around, the first number i...</td>\n <td>2011-12-21T15:30:22.113</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>10796244</th>\n <td><python><excel><xlwt></td>\n <td>8590741</td>\n <td>0</td>\n <td>Thanks for the answers everyone. If anyone is...</td>\n <td>2011-12-30T19:08:28.063</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>11245320</th>\n <td><python></td>\n <td>8976324</td>\n <td>0</td>\n <td>@Cameron, so you're saying something I import ...</td>\n <td>2012-01-23T18:14:14.870</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>11245634</th>\n <td><python></td>\n <td>8976324</td>\n <td>0</td>\n <td>Thanks everyone. If anyone wants to post this...</td>\n <td>2012-01-23T18:28:32.813</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>12490216</th>\n <td><python><django><django-models><django-admin></td>\n <td>9806936</td>\n <td>0</td>\n <td>@jpic, that's interesting but it's probably ov...</td>\n <td>2012-03-21T15:00:45.163</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>32554534</th>\n <td><python><django><django-forms><django-admin><d...</td>\n <td>19807757</td>\n <td>0</td>\n <td>I'm coming across the exact same problem. I a...</td>\n <td>2014-02-04T15:05:23.023</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>32567053</th>\n <td><python><django><django-forms><django-admin><d...</td>\n <td>19807757</td>\n <td>0</td>\n <td>I put an updated question more inline with wha...</td>\n <td>2014-02-04T20:26:56.147</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>36034593</th>\n <td><python><numpy></td>\n <td>23497706</td>\n <td>0</td>\n <td>I was thinking I could reference just the firs...</td>\n <td>2014-05-06T14:42:07.190</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>36034937</th>\n <td><python><numpy></td>\n <td>23497706</td>\n <td>0</td>\n <td>hmm, I can access the first column with array[...</td>\n <td>2014-05-06T14:49:57.347</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>36041765</th>\n <td><python><numpy></td>\n <td>23500754</td>\n <td>0</td>\n <td>hmm, I just ran the code from your answer. Do...</td>\n <td>2014-05-06T17:47:18.563</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>47738961</th>\n <td><python><python-requests></td>\n <td>29775247</td>\n <td>1</td>\n <td>@sigmavirus24, that's right I don't want to lo...</td>\n <td>2015-04-22T18:04:58.213</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>47742802</th>\n <td><python><curl><python-requests></td>\n <td>29807249</td>\n <td>0</td>\n <td>Yeah, the requests.get step is instant, so I g...</td>\n <td>2015-04-22T19:45:33.083</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>47743040</th>\n <td><python><curl><python-requests></td>\n <td>29807249</td>\n <td>0</td>\n <td>That was absolutely the issue. Thanks! Changi...</td>\n <td>2015-04-22T19:52:21.247</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>48550940</th>\n <td><python><matplotlib></td>\n <td>30223161</td>\n <td>0</td>\n <td>Thanks for the suggestion. what does zlim do?...</td>\n <td>2015-05-13T19:22:13.533</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>48551405</th>\n <td><python><matplotlib></td>\n <td>30223161</td>\n <td>0</td>\n <td>Thanks. I guess I don't understand what the h...</td>\n <td>2015-05-13T19:36:25.690</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>50303593</th>\n <td><python><mongodb><uwsgi><mlab><pymongo-3.x></td>\n <td>31030307</td>\n <td>2</td>\n <td>I'm hitting this too on a similar setup. Did ...</td>\n <td>2015-06-30T19:18:02.697</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>50336702</th>\n <td><python><mongodb><uwsgi><mlab><pymongo-3.x></td>\n <td>31030307</td>\n <td>1</td>\n <td>Want me to start a bounty? Would you be avail...</td>\n <td>2015-07-01T14:27:34.823</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>50337057</th>\n <td><python><mongodb><uwsgi><mlab><pymongo-3.x></td>\n <td>31030307</td>\n <td>0</td>\n <td>Is this useful? http://blog.fejes.ca/?p=2496 ...</td>\n <td>2015-07-01T14:35:16.503</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>50376360</th>\n <td><python><mongodb><uwsgi><mlab><pymongo-3.x></td>\n <td>31030307</td>\n <td>0</td>\n <td>Thanks Jesse, I guess we couldn't tell if it w...</td>\n <td>2015-07-02T13:09:14.617</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>54364203</th>\n <td><python><oracle><macos><cx-oracle><osx-elcapitan></td>\n <td>33259671</td>\n <td>0</td>\n <td>Thanks. I believe the fix_oralib.rb also does...</td>\n <td>2015-10-22T13:16:49.317</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>58665815</th>\n <td><python><django><celery><django-celery></td>\n <td>35486011</td>\n <td>0</td>\n <td>@zsepi, I updated the question with those.</td>\n <td>2016-02-18T15:55:59.940</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>58894206</th>\n <td><python><django><celery><django-celery></td>\n <td>35603707</td>\n <td>0</td>\n <td>It set's to write to a specified file, and ema...</td>\n <td>2016-02-24T14:29:13.990</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>62020862</th>\n <td><python><python-2.7><unicode><subprocess></td>\n <td>37245595</td>\n <td>0</td>\n <td>@tdelaney, did you try it on osx? It actually...</td>\n <td>2016-05-16T03:06:55.457</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>62020942</th>\n <td><python><python-2.7><unicode><subprocess></td>\n <td>37245595</td>\n <td>0</td>\n <td>I tried redirecting to a file and it still out...</td>\n <td>2016-05-16T03:13:12.050</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>62020963</th>\n <td><python><python-2.7><unicode><subprocess></td>\n <td>37245595</td>\n <td>0</td>\n <td>@tdelaney, I think you're right, it's probably...</td>\n <td>2016-05-16T03:14:39.700</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>68427097</th>\n <td><python><mocking><generator><python-unittest><...</td>\n <td>40595679</td>\n <td>0</td>\n <td>Good point. I took that line out. Same issue...</td>\n <td>2016-11-14T18:52:50.053</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>70139817</th>\n <td><python><logging></td>\n <td>41467032</td>\n <td>0</td>\n <td>I have 'A' and 'B' configured elsewhere to do ...</td>\n <td>2017-01-04T15:15:07.183</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>70435606</th>\n <td><python><postgresql><psycopg2><psycopg></td>\n <td>41616578</td>\n <td>0</td>\n <td>I want to do everything in memory. All the do...</td>\n <td>2017-01-12T15:37:23.967</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>76846070</th>\n <td><python><django><django-models><django-authent...</td>\n <td>44933724</td>\n <td>0</td>\n <td>Thanks. I didn't notice that. Taking it out ...</td>\n <td>2017-07-05T20:00:37.840</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>77453798</th>\n <td><python><django><migration><django-migrations></td>\n <td>45238835</td>\n <td>0</td>\n <td>I was wondering about that. But how would I c...</td>\n <td>2017-07-21T17:54:41.707</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>77456266</th>\n <td><python><django><migration><django-migrations></td>\n <td>45238835</td>\n <td>0</td>\n <td>That actually fixed my problem.</td>\n <td>2017-07-21T19:11:37.543</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>80880518</th>\n <td><python><django></td>\n <td>46960782</td>\n <td>0</td>\n <td>@Jiaaro, thanks, but just tried it and no impr...</td>\n <td>2017-10-27T02:20:12.973</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n </tbody>\n</table>\n</div>"
+ },
+ "execution_count": 20,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "comments_on_questions_df = pd.read_sql_query(f\"\"\"\n",
+ " SELECT A.Tags, B.*\n",
+ " FROM Post A\n",
+ " INNER JOIN Comment B ON (B.PostId = A.PostId)\n",
+ " WHERE A.Tags LIKE '%python%' AND (B.UserId = {user_id}) AND (A.PostTypeId = 1)\n",
+ "\"\"\", db)\n",
+ "comments_on_questions_df.set_index('CommentId', inplace=True)\n",
+ "comments_on_questions_df"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 21,
+ "outputs": [
+ {
+ "data": {
+ "text/plain": " Tags PostId Score \\\nCommentId \n27452 <python><memory-management><short> 120454 0 \n30223 <python> 125052 0 \n63505 <python> 92318 0 \n124749 <python><mysql><database><deadlock> 270449 0 \n124761 <python><mysql><database><deadlock> 270492 0 \n... ... ... ... \n68725297 <python><subprocess><fork> 40749648 0 \n68725576 <python><subprocess><fork> 40749648 1 \n70480473 <python><postgresql><psycopg2><psycopg> 41623932 0 \n70641464 <python><django><testing><sqlite> 1203379 0 \n79329507 <python> 13091300 9 \n\n Body \\\nCommentId \n27452 Can I use IIBTree without installing all of Zo... \n30223 Keep in mind there are some unpythonic idioms ... \n63505 What about iterators exactly? \n124749 That would just cause a OperationalError: (120... \n124761 How would I make sure they run at exactly the ... \n... ... \n68725297 Follow up question. What if the child finishe... \n68725576 Excellent thanks! From your article, I guess ... \n70480473 Yes, I verified that worked to remove the quot... \n70641464 @bstpierre, how did you force transaction supp... \n79329507 Only problem with this is I get code lint warn... \n\n CreationDate UserId ContentLicense \nCommentId \n27452 2008-09-23T16:48:24.133 13009 CC BY-SA 2.5 \n30223 2008-09-24T14:02:17.330 13009 CC BY-SA 2.5 \n63505 2008-10-08T01:43:15.823 13009 CC BY-SA 2.5 \n124749 2008-11-06T22:10:52.610 13009 CC BY-SA 2.5 \n124761 2008-11-06T22:12:43.137 13009 CC BY-SA 2.5 \n... ... ... ... \n68725297 2016-11-22T19:04:27.827 13009 CC BY-SA 3.0 \n68725576 2016-11-22T19:13:12.043 13009 CC BY-SA 3.0 \n70480473 2017-01-13T17:35:23.640 13009 CC BY-SA 3.0 \n70641464 2017-01-18T15:34:03.417 13009 CC BY-SA 3.0 \n79329507 2017-09-12T18:41:40.393 13009 CC BY-SA 3.0 \n\n[99 rows x 7 columns]",
+ "text/html": "<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>Tags</th>\n <th>PostId</th>\n <th>Score</th>\n <th>Body</th>\n <th>CreationDate</th>\n <th>UserId</th>\n <th>ContentLicense</th>\n </tr>\n <tr>\n <th>CommentId</th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n <th></th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>27452</th>\n <td><python><memory-management><short></td>\n <td>120454</td>\n <td>0</td>\n <td>Can I use IIBTree without installing all of Zo...</td>\n <td>2008-09-23T16:48:24.133</td>\n <td>13009</td>\n <td>CC BY-SA 2.5</td>\n </tr>\n <tr>\n <th>30223</th>\n <td><python></td>\n <td>125052</td>\n <td>0</td>\n <td>Keep in mind there are some unpythonic idioms ...</td>\n <td>2008-09-24T14:02:17.330</td>\n <td>13009</td>\n <td>CC BY-SA 2.5</td>\n </tr>\n <tr>\n <th>63505</th>\n <td><python></td>\n <td>92318</td>\n <td>0</td>\n <td>What about iterators exactly?</td>\n <td>2008-10-08T01:43:15.823</td>\n <td>13009</td>\n <td>CC BY-SA 2.5</td>\n </tr>\n <tr>\n <th>124749</th>\n <td><python><mysql><database><deadlock></td>\n <td>270449</td>\n <td>0</td>\n <td>That would just cause a OperationalError: (120...</td>\n <td>2008-11-06T22:10:52.610</td>\n <td>13009</td>\n <td>CC BY-SA 2.5</td>\n </tr>\n <tr>\n <th>124761</th>\n <td><python><mysql><database><deadlock></td>\n <td>270492</td>\n <td>0</td>\n <td>How would I make sure they run at exactly the ...</td>\n <td>2008-11-06T22:12:43.137</td>\n <td>13009</td>\n <td>CC BY-SA 2.5</td>\n </tr>\n <tr>\n <th>...</th>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n </tr>\n <tr>\n <th>68725297</th>\n <td><python><subprocess><fork></td>\n <td>40749648</td>\n <td>0</td>\n <td>Follow up question. What if the child finishe...</td>\n <td>2016-11-22T19:04:27.827</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>68725576</th>\n <td><python><subprocess><fork></td>\n <td>40749648</td>\n <td>1</td>\n <td>Excellent thanks! From your article, I guess ...</td>\n <td>2016-11-22T19:13:12.043</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>70480473</th>\n <td><python><postgresql><psycopg2><psycopg></td>\n <td>41623932</td>\n <td>0</td>\n <td>Yes, I verified that worked to remove the quot...</td>\n <td>2017-01-13T17:35:23.640</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>70641464</th>\n <td><python><django><testing><sqlite></td>\n <td>1203379</td>\n <td>0</td>\n <td>@bstpierre, how did you force transaction supp...</td>\n <td>2017-01-18T15:34:03.417</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n <tr>\n <th>79329507</th>\n <td><python></td>\n <td>13091300</td>\n <td>9</td>\n <td>Only problem with this is I get code lint warn...</td>\n <td>2017-09-12T18:41:40.393</td>\n <td>13009</td>\n <td>CC BY-SA 3.0</td>\n </tr>\n </tbody>\n</table>\n<p>99 rows × 7 columns</p>\n</div>"
+ },
+ "execution_count": 21,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "comments_on_answers_df = pd.read_sql_query(f\"\"\"\n",
+ " SELECT A.Tags, C.*\n",
+ " FROM Post A\n",
+ " INNER JOIN Post B ON (B.ParentId = A.PostId) AND (B.ParentId IS NOT NULL)\n",
+ " INNER JOIN Comment C ON (B.PostId = C.PostId)\n",
+ " WHERE A.Tags LIKE '%python%' AND (C.UserId = {user_id}) AND (B.PostTypeId = 2)\n",
+ "\"\"\", db)\n",
+ "comments_on_answers_df.set_index('CommentId', inplace=True)\n",
+ "comments_on_answers_df"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 22,
+ "outputs": [],
+ "source": [
+ "from post_embedding_builder import Import"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 23,
+ "outputs": [],
+ "source": [
+ "from static_graph_construction import StaticGraphConstruction"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "markdown",
+ "source": [
+ "Let's construct the heterogenous graph"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 24,
+ "outputs": [],
+ "source": [
+ "comments_df = pd.concat([comments_on_questions_df, comments_on_answers_df])"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 27,
+ "outputs": [],
+ "source": [
+ "graph_constructor = StaticGraphConstruction()"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 26,
+ "outputs": [
+ {
+ "ename": "KeyboardInterrupt",
+ "evalue": "",
+ "output_type": "error",
+ "traceback": [
+ "\u001B[1;31m---------------------------------------------------------------------------\u001B[0m",
+ "\u001B[1;31mKeyboardInterrupt\u001B[0m Traceback (most recent call last)",
+ "Cell \u001B[1;32mIn [26], line 3\u001B[0m\n\u001B[0;32m 1\u001B[0m \u001B[38;5;28;01mimport\u001B[39;00m \u001B[38;5;21;01mtorch_geometric\u001B[39;00m\u001B[38;5;21;01m.\u001B[39;00m\u001B[38;5;21;01mtransforms\u001B[39;00m \u001B[38;5;28;01mas\u001B[39;00m \u001B[38;5;21;01mT\u001B[39;00m\n\u001B[0;32m 2\u001B[0m graph_constructor \u001B[38;5;241m=\u001B[39m StaticGraphConstruction()\n\u001B[1;32m----> 3\u001B[0m graph_out \u001B[38;5;241m=\u001B[39m \u001B[43mgraph_constructor\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mconstruct\u001B[49m\u001B[43m(\u001B[49m\u001B[43mquestions_df\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43manswers_df\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mcomments_df\u001B[49m\u001B[43m)\u001B[49m\n\u001B[0;32m 4\u001B[0m \u001B[38;5;66;03m#graph_out['module'].x = torch.empty(0, 110, dtype=torch.long)\u001B[39;00m\n\u001B[0;32m 5\u001B[0m graph_out\n",
+ "File \u001B[1;32m~\\Documents\\graph4stackoverflow\\embeddings\\static_graph_construction.py:120\u001B[0m, in \u001B[0;36mStaticGraphConstruction.construct\u001B[1;34m(self, questions, answers, comments)\u001B[0m\n\u001B[0;32m 114\u001B[0m comments \u001B[38;5;241m=\u001B[39m comments\u001B[38;5;241m.\u001B[39mhead(\u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_post_count_limit)\n\u001B[0;32m 116\u001B[0m \u001B[38;5;66;03m# questions.reset_index(inplace=True)\u001B[39;00m\n\u001B[0;32m 117\u001B[0m \u001B[38;5;66;03m# answers.reset_index(inplace=True)\u001B[39;00m\n\u001B[0;32m 118\u001B[0m \u001B[38;5;66;03m# comments.reset_index(inplace=True)\u001B[39;00m\n\u001B[1;32m--> 120\u001B[0m question_nodes \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;43mlist\u001B[39;49m\u001B[43m(\u001B[49m\u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mprocess_questions\u001B[49m\u001B[43m(\u001B[49m\u001B[43mquestions\u001B[49m\u001B[43m)\u001B[49m\u001B[43m)\u001B[49m\n\u001B[0;32m 121\u001B[0m answer_nodes \u001B[38;5;241m=\u001B[39m \u001B[38;5;28mlist\u001B[39m(\u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mprocess_answers(answers))\n\u001B[0;32m 122\u001B[0m comment_nodes \u001B[38;5;241m=\u001B[39m \u001B[38;5;28mlist\u001B[39m(\u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mprocess_comments(comments))\n",
+ "File \u001B[1;32m~\\Documents\\graph4stackoverflow\\embeddings\\static_graph_construction.py:39\u001B[0m, in \u001B[0;36mStaticGraphConstruction.process_questions\u001B[1;34m(self, questions)\u001B[0m\n\u001B[0;32m 38\u001B[0m \u001B[38;5;28;01mdef\u001B[39;00m \u001B[38;5;21mprocess_questions\u001B[39m(\u001B[38;5;28mself\u001B[39m, questions: pd\u001B[38;5;241m.\u001B[39mDataFrame) \u001B[38;5;241m-\u001B[39m\u001B[38;5;241m>\u001B[39m torch\u001B[38;5;241m.\u001B[39mTensor:\n\u001B[1;32m---> 39\u001B[0m word_embedding, code_embedding, modules \u001B[38;5;241m=\u001B[39m \u001B[43mStaticGraphConstruction\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mpost_embedding_builder\u001B[49m\u001B[43m(\u001B[49m\u001B[43mquestions\u001B[49m\u001B[43m[\u001B[49m\u001B[38;5;124;43m'\u001B[39;49m\u001B[38;5;124;43mBody\u001B[39;49m\u001B[38;5;124;43m'\u001B[39;49m\u001B[43m]\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43m_use_bert\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mquestions\u001B[49m\u001B[43m[\u001B[49m\u001B[38;5;124;43m'\u001B[39;49m\u001B[38;5;124;43mTitle\u001B[39;49m\u001B[38;5;124;43m'\u001B[39;49m\u001B[43m]\u001B[49m\u001B[43m)\u001B[49m\n\u001B[0;32m 40\u001B[0m \u001B[38;5;28;01mfor\u001B[39;00m i, body, title, tags \u001B[38;5;129;01min\u001B[39;00m questions[[\u001B[38;5;124m'\u001B[39m\u001B[38;5;124mBody\u001B[39m\u001B[38;5;124m'\u001B[39m, \u001B[38;5;124m'\u001B[39m\u001B[38;5;124mTitle\u001B[39m\u001B[38;5;124m'\u001B[39m, \u001B[38;5;124m'\u001B[39m\u001B[38;5;124mTags\u001B[39m\u001B[38;5;124m'\u001B[39m]]\u001B[38;5;241m.\u001B[39mitertuples():\n\u001B[0;32m 42\u001B[0m modules \u001B[38;5;241m=\u001B[39m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mprocess_module_names(modules)\n",
+ "File \u001B[1;32m~\\Documents\\graph4stackoverflow\\venv\\lib\\site-packages\\torch\\nn\\modules\\module.py:1190\u001B[0m, in \u001B[0;36mModule._call_impl\u001B[1;34m(self, *input, **kwargs)\u001B[0m\n\u001B[0;32m 1186\u001B[0m \u001B[38;5;66;03m# If we don't have any hooks, we want to skip the rest of the logic in\u001B[39;00m\n\u001B[0;32m 1187\u001B[0m \u001B[38;5;66;03m# this function, and just call forward.\u001B[39;00m\n\u001B[0;32m 1188\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m \u001B[38;5;129;01mnot\u001B[39;00m (\u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_backward_hooks \u001B[38;5;129;01mor\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_forward_hooks \u001B[38;5;129;01mor\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_forward_pre_hooks \u001B[38;5;129;01mor\u001B[39;00m _global_backward_hooks\n\u001B[0;32m 1189\u001B[0m \u001B[38;5;129;01mor\u001B[39;00m _global_forward_hooks \u001B[38;5;129;01mor\u001B[39;00m _global_forward_pre_hooks):\n\u001B[1;32m-> 1190\u001B[0m \u001B[38;5;28;01mreturn\u001B[39;00m \u001B[43mforward_call\u001B[49m\u001B[43m(\u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[38;5;28;43minput\u001B[39;49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[43mkwargs\u001B[49m\u001B[43m)\u001B[49m\n\u001B[0;32m 1191\u001B[0m \u001B[38;5;66;03m# Do not call functions when jit is used\u001B[39;00m\n\u001B[0;32m 1192\u001B[0m full_backward_hooks, non_full_backward_hooks \u001B[38;5;241m=\u001B[39m [], []\n",
+ "File \u001B[1;32m~\\Documents\\graph4stackoverflow\\embeddings\\post_embedding_builder.py:64\u001B[0m, in \u001B[0;36mPostEmbedding.forward\u001B[1;34m(self, html_batch, use_bert, title_batch)\u001B[0m\n\u001B[0;32m 62\u001B[0m t1 \u001B[38;5;241m=\u001B[39m time\u001B[38;5;241m.\u001B[39mtime()\n\u001B[0;32m 63\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m use_bert:\n\u001B[1;32m---> 64\u001B[0m para_emb \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mto_bert_embedding\u001B[49m\u001B[43m(\u001B[49m\u001B[43m[\u001B[49m\u001B[38;5;124;43m\"\u001B[39;49m\u001B[38;5;124;43m \u001B[39;49m\u001B[38;5;124;43m\"\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mjoin\u001B[49m\u001B[43m(\u001B[49m\u001B[43mps\u001B[49m\u001B[43m)\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;28;43;01mfor\u001B[39;49;00m\u001B[43m \u001B[49m\u001B[43mps\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;129;43;01min\u001B[39;49;00m\u001B[43m \u001B[49m\u001B[43mparagraph_batches\u001B[49m\u001B[43m]\u001B[49m\u001B[43m)\u001B[49m\n\u001B[0;32m 65\u001B[0m \u001B[38;5;28;01melse\u001B[39;00m:\n\u001B[0;32m 66\u001B[0m \u001B[38;5;66;03m#para_emb = self.to_glove_paragraph_embedding(ps)\u001B[39;00m\n\u001B[0;32m 67\u001B[0m \u001B[38;5;28;01mraise\u001B[39;00m \u001B[38;5;167;01mNotImplementedError\u001B[39;00m(\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mGloVe paragraph embedding need to be refactored to work with batches\u001B[39m\u001B[38;5;124m\"\u001B[39m)\n",
+ "File \u001B[1;32m~\\Documents\\graph4stackoverflow\\embeddings\\post_embedding_builder.py:154\u001B[0m, in \u001B[0;36mPostEmbedding.to_bert_embedding\u001B[1;34m(self, texts)\u001B[0m\n\u001B[0;32m 152\u001B[0m encodings \u001B[38;5;241m=\u001B[39m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_bert_tokenizer(texts, padding\u001B[38;5;241m=\u001B[39m\u001B[38;5;28;01mTrue\u001B[39;00m, truncation\u001B[38;5;241m=\u001B[39m\u001B[38;5;28;01mTrue\u001B[39;00m, return_tensors\u001B[38;5;241m=\u001B[39m\u001B[38;5;124m'\u001B[39m\u001B[38;5;124mpt\u001B[39m\u001B[38;5;124m'\u001B[39m, max_length\u001B[38;5;241m=\u001B[39m\u001B[38;5;241m512\u001B[39m)\n\u001B[0;32m 153\u001B[0m \u001B[38;5;28;01mwith\u001B[39;00m torch\u001B[38;5;241m.\u001B[39mno_grad():\n\u001B[1;32m--> 154\u001B[0m outputs \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43m_bert_model\u001B[49m\u001B[43m(\u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[43mencodings\u001B[49m\u001B[43m)\u001B[49m\n\u001B[0;32m 155\u001B[0m last_layer \u001B[38;5;241m=\u001B[39m outputs\u001B[38;5;241m.\u001B[39mlast_hidden_state\n\u001B[0;32m 156\u001B[0m \u001B[38;5;28mcls\u001B[39m \u001B[38;5;241m=\u001B[39m last_layer[:, \u001B[38;5;241m0\u001B[39m, :]\n",
+ "File \u001B[1;32m~\\Documents\\graph4stackoverflow\\venv\\lib\\site-packages\\torch\\nn\\modules\\module.py:1190\u001B[0m, in \u001B[0;36mModule._call_impl\u001B[1;34m(self, *input, **kwargs)\u001B[0m\n\u001B[0;32m 1186\u001B[0m \u001B[38;5;66;03m# If we don't have any hooks, we want to skip the rest of the logic in\u001B[39;00m\n\u001B[0;32m 1187\u001B[0m \u001B[38;5;66;03m# this function, and just call forward.\u001B[39;00m\n\u001B[0;32m 1188\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m \u001B[38;5;129;01mnot\u001B[39;00m (\u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_backward_hooks \u001B[38;5;129;01mor\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_forward_hooks \u001B[38;5;129;01mor\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_forward_pre_hooks \u001B[38;5;129;01mor\u001B[39;00m _global_backward_hooks\n\u001B[0;32m 1189\u001B[0m \u001B[38;5;129;01mor\u001B[39;00m _global_forward_hooks \u001B[38;5;129;01mor\u001B[39;00m _global_forward_pre_hooks):\n\u001B[1;32m-> 1190\u001B[0m \u001B[38;5;28;01mreturn\u001B[39;00m \u001B[43mforward_call\u001B[49m\u001B[43m(\u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[38;5;28;43minput\u001B[39;49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[43mkwargs\u001B[49m\u001B[43m)\u001B[49m\n\u001B[0;32m 1191\u001B[0m \u001B[38;5;66;03m# Do not call functions when jit is used\u001B[39;00m\n\u001B[0;32m 1192\u001B[0m full_backward_hooks, non_full_backward_hooks \u001B[38;5;241m=\u001B[39m [], []\n",
+ "File \u001B[1;32m~\\Documents\\graph4stackoverflow\\venv\\lib\\site-packages\\transformers\\models\\bert\\modeling_bert.py:1014\u001B[0m, in \u001B[0;36mBertModel.forward\u001B[1;34m(self, input_ids, attention_mask, token_type_ids, position_ids, head_mask, inputs_embeds, encoder_hidden_states, encoder_attention_mask, past_key_values, use_cache, output_attentions, output_hidden_states, return_dict)\u001B[0m\n\u001B[0;32m 1005\u001B[0m head_mask \u001B[38;5;241m=\u001B[39m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mget_head_mask(head_mask, \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mconfig\u001B[38;5;241m.\u001B[39mnum_hidden_layers)\n\u001B[0;32m 1007\u001B[0m embedding_output \u001B[38;5;241m=\u001B[39m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39membeddings(\n\u001B[0;32m 1008\u001B[0m input_ids\u001B[38;5;241m=\u001B[39minput_ids,\n\u001B[0;32m 1009\u001B[0m position_ids\u001B[38;5;241m=\u001B[39mposition_ids,\n\u001B[1;32m (...)\u001B[0m\n\u001B[0;32m 1012\u001B[0m past_key_values_length\u001B[38;5;241m=\u001B[39mpast_key_values_length,\n\u001B[0;32m 1013\u001B[0m )\n\u001B[1;32m-> 1014\u001B[0m encoder_outputs \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mencoder\u001B[49m\u001B[43m(\u001B[49m\n\u001B[0;32m 1015\u001B[0m \u001B[43m \u001B[49m\u001B[43membedding_output\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 1016\u001B[0m \u001B[43m \u001B[49m\u001B[43mattention_mask\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mextended_attention_mask\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 1017\u001B[0m \u001B[43m \u001B[49m\u001B[43mhead_mask\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mhead_mask\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 1018\u001B[0m \u001B[43m \u001B[49m\u001B[43mencoder_hidden_states\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mencoder_hidden_states\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 1019\u001B[0m \u001B[43m \u001B[49m\u001B[43mencoder_attention_mask\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mencoder_extended_attention_mask\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 1020\u001B[0m \u001B[43m \u001B[49m\u001B[43mpast_key_values\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mpast_key_values\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 1021\u001B[0m \u001B[43m \u001B[49m\u001B[43muse_cache\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43muse_cache\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 1022\u001B[0m \u001B[43m \u001B[49m\u001B[43moutput_attentions\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43moutput_attentions\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 1023\u001B[0m \u001B[43m \u001B[49m\u001B[43moutput_hidden_states\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43moutput_hidden_states\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 1024\u001B[0m \u001B[43m \u001B[49m\u001B[43mreturn_dict\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mreturn_dict\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 1025\u001B[0m \u001B[43m\u001B[49m\u001B[43m)\u001B[49m\n\u001B[0;32m 1026\u001B[0m sequence_output \u001B[38;5;241m=\u001B[39m encoder_outputs[\u001B[38;5;241m0\u001B[39m]\n\u001B[0;32m 1027\u001B[0m pooled_output \u001B[38;5;241m=\u001B[39m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mpooler(sequence_output) \u001B[38;5;28;01mif\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mpooler \u001B[38;5;129;01mis\u001B[39;00m \u001B[38;5;129;01mnot\u001B[39;00m \u001B[38;5;28;01mNone\u001B[39;00m \u001B[38;5;28;01melse\u001B[39;00m \u001B[38;5;28;01mNone\u001B[39;00m\n",
+ "File \u001B[1;32m~\\Documents\\graph4stackoverflow\\venv\\lib\\site-packages\\torch\\nn\\modules\\module.py:1190\u001B[0m, in \u001B[0;36mModule._call_impl\u001B[1;34m(self, *input, **kwargs)\u001B[0m\n\u001B[0;32m 1186\u001B[0m \u001B[38;5;66;03m# If we don't have any hooks, we want to skip the rest of the logic in\u001B[39;00m\n\u001B[0;32m 1187\u001B[0m \u001B[38;5;66;03m# this function, and just call forward.\u001B[39;00m\n\u001B[0;32m 1188\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m \u001B[38;5;129;01mnot\u001B[39;00m (\u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_backward_hooks \u001B[38;5;129;01mor\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_forward_hooks \u001B[38;5;129;01mor\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_forward_pre_hooks \u001B[38;5;129;01mor\u001B[39;00m _global_backward_hooks\n\u001B[0;32m 1189\u001B[0m \u001B[38;5;129;01mor\u001B[39;00m _global_forward_hooks \u001B[38;5;129;01mor\u001B[39;00m _global_forward_pre_hooks):\n\u001B[1;32m-> 1190\u001B[0m \u001B[38;5;28;01mreturn\u001B[39;00m \u001B[43mforward_call\u001B[49m\u001B[43m(\u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[38;5;28;43minput\u001B[39;49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[43mkwargs\u001B[49m\u001B[43m)\u001B[49m\n\u001B[0;32m 1191\u001B[0m \u001B[38;5;66;03m# Do not call functions when jit is used\u001B[39;00m\n\u001B[0;32m 1192\u001B[0m full_backward_hooks, non_full_backward_hooks \u001B[38;5;241m=\u001B[39m [], []\n",
+ "File \u001B[1;32m~\\Documents\\graph4stackoverflow\\venv\\lib\\site-packages\\transformers\\models\\bert\\modeling_bert.py:603\u001B[0m, in \u001B[0;36mBertEncoder.forward\u001B[1;34m(self, hidden_states, attention_mask, head_mask, encoder_hidden_states, encoder_attention_mask, past_key_values, use_cache, output_attentions, output_hidden_states, return_dict)\u001B[0m\n\u001B[0;32m 594\u001B[0m layer_outputs \u001B[38;5;241m=\u001B[39m torch\u001B[38;5;241m.\u001B[39mutils\u001B[38;5;241m.\u001B[39mcheckpoint\u001B[38;5;241m.\u001B[39mcheckpoint(\n\u001B[0;32m 595\u001B[0m create_custom_forward(layer_module),\n\u001B[0;32m 596\u001B[0m hidden_states,\n\u001B[1;32m (...)\u001B[0m\n\u001B[0;32m 600\u001B[0m encoder_attention_mask,\n\u001B[0;32m 601\u001B[0m )\n\u001B[0;32m 602\u001B[0m \u001B[38;5;28;01melse\u001B[39;00m:\n\u001B[1;32m--> 603\u001B[0m layer_outputs \u001B[38;5;241m=\u001B[39m \u001B[43mlayer_module\u001B[49m\u001B[43m(\u001B[49m\n\u001B[0;32m 604\u001B[0m \u001B[43m \u001B[49m\u001B[43mhidden_states\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 605\u001B[0m \u001B[43m \u001B[49m\u001B[43mattention_mask\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 606\u001B[0m \u001B[43m \u001B[49m\u001B[43mlayer_head_mask\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 607\u001B[0m \u001B[43m \u001B[49m\u001B[43mencoder_hidden_states\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 608\u001B[0m \u001B[43m \u001B[49m\u001B[43mencoder_attention_mask\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 609\u001B[0m \u001B[43m \u001B[49m\u001B[43mpast_key_value\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 610\u001B[0m \u001B[43m \u001B[49m\u001B[43moutput_attentions\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 611\u001B[0m \u001B[43m \u001B[49m\u001B[43m)\u001B[49m\n\u001B[0;32m 613\u001B[0m hidden_states \u001B[38;5;241m=\u001B[39m layer_outputs[\u001B[38;5;241m0\u001B[39m]\n\u001B[0;32m 614\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m use_cache:\n",
+ "File \u001B[1;32m~\\Documents\\graph4stackoverflow\\venv\\lib\\site-packages\\torch\\nn\\modules\\module.py:1190\u001B[0m, in \u001B[0;36mModule._call_impl\u001B[1;34m(self, *input, **kwargs)\u001B[0m\n\u001B[0;32m 1186\u001B[0m \u001B[38;5;66;03m# If we don't have any hooks, we want to skip the rest of the logic in\u001B[39;00m\n\u001B[0;32m 1187\u001B[0m \u001B[38;5;66;03m# this function, and just call forward.\u001B[39;00m\n\u001B[0;32m 1188\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m \u001B[38;5;129;01mnot\u001B[39;00m (\u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_backward_hooks \u001B[38;5;129;01mor\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_forward_hooks \u001B[38;5;129;01mor\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_forward_pre_hooks \u001B[38;5;129;01mor\u001B[39;00m _global_backward_hooks\n\u001B[0;32m 1189\u001B[0m \u001B[38;5;129;01mor\u001B[39;00m _global_forward_hooks \u001B[38;5;129;01mor\u001B[39;00m _global_forward_pre_hooks):\n\u001B[1;32m-> 1190\u001B[0m \u001B[38;5;28;01mreturn\u001B[39;00m \u001B[43mforward_call\u001B[49m\u001B[43m(\u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[38;5;28;43minput\u001B[39;49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[43mkwargs\u001B[49m\u001B[43m)\u001B[49m\n\u001B[0;32m 1191\u001B[0m \u001B[38;5;66;03m# Do not call functions when jit is used\u001B[39;00m\n\u001B[0;32m 1192\u001B[0m full_backward_hooks, non_full_backward_hooks \u001B[38;5;241m=\u001B[39m [], []\n",
+ "File \u001B[1;32m~\\Documents\\graph4stackoverflow\\venv\\lib\\site-packages\\transformers\\models\\bert\\modeling_bert.py:489\u001B[0m, in \u001B[0;36mBertLayer.forward\u001B[1;34m(self, hidden_states, attention_mask, head_mask, encoder_hidden_states, encoder_attention_mask, past_key_value, output_attentions)\u001B[0m\n\u001B[0;32m 477\u001B[0m \u001B[38;5;28;01mdef\u001B[39;00m \u001B[38;5;21mforward\u001B[39m(\n\u001B[0;32m 478\u001B[0m \u001B[38;5;28mself\u001B[39m,\n\u001B[0;32m 479\u001B[0m hidden_states: torch\u001B[38;5;241m.\u001B[39mTensor,\n\u001B[1;32m (...)\u001B[0m\n\u001B[0;32m 486\u001B[0m ) \u001B[38;5;241m-\u001B[39m\u001B[38;5;241m>\u001B[39m Tuple[torch\u001B[38;5;241m.\u001B[39mTensor]:\n\u001B[0;32m 487\u001B[0m \u001B[38;5;66;03m# decoder uni-directional self-attention cached key/values tuple is at positions 1,2\u001B[39;00m\n\u001B[0;32m 488\u001B[0m self_attn_past_key_value \u001B[38;5;241m=\u001B[39m past_key_value[:\u001B[38;5;241m2\u001B[39m] \u001B[38;5;28;01mif\u001B[39;00m past_key_value \u001B[38;5;129;01mis\u001B[39;00m \u001B[38;5;129;01mnot\u001B[39;00m \u001B[38;5;28;01mNone\u001B[39;00m \u001B[38;5;28;01melse\u001B[39;00m \u001B[38;5;28;01mNone\u001B[39;00m\n\u001B[1;32m--> 489\u001B[0m self_attention_outputs \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mattention\u001B[49m\u001B[43m(\u001B[49m\n\u001B[0;32m 490\u001B[0m \u001B[43m \u001B[49m\u001B[43mhidden_states\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 491\u001B[0m \u001B[43m \u001B[49m\u001B[43mattention_mask\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 492\u001B[0m \u001B[43m \u001B[49m\u001B[43mhead_mask\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 493\u001B[0m \u001B[43m \u001B[49m\u001B[43moutput_attentions\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43moutput_attentions\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 494\u001B[0m \u001B[43m \u001B[49m\u001B[43mpast_key_value\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[43mself_attn_past_key_value\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 495\u001B[0m \u001B[43m \u001B[49m\u001B[43m)\u001B[49m\n\u001B[0;32m 496\u001B[0m attention_output \u001B[38;5;241m=\u001B[39m self_attention_outputs[\u001B[38;5;241m0\u001B[39m]\n\u001B[0;32m 498\u001B[0m \u001B[38;5;66;03m# if decoder, the last output is tuple of self-attn cache\u001B[39;00m\n",
+ "File \u001B[1;32m~\\Documents\\graph4stackoverflow\\venv\\lib\\site-packages\\torch\\nn\\modules\\module.py:1190\u001B[0m, in \u001B[0;36mModule._call_impl\u001B[1;34m(self, *input, **kwargs)\u001B[0m\n\u001B[0;32m 1186\u001B[0m \u001B[38;5;66;03m# If we don't have any hooks, we want to skip the rest of the logic in\u001B[39;00m\n\u001B[0;32m 1187\u001B[0m \u001B[38;5;66;03m# this function, and just call forward.\u001B[39;00m\n\u001B[0;32m 1188\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m \u001B[38;5;129;01mnot\u001B[39;00m (\u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_backward_hooks \u001B[38;5;129;01mor\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_forward_hooks \u001B[38;5;129;01mor\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_forward_pre_hooks \u001B[38;5;129;01mor\u001B[39;00m _global_backward_hooks\n\u001B[0;32m 1189\u001B[0m \u001B[38;5;129;01mor\u001B[39;00m _global_forward_hooks \u001B[38;5;129;01mor\u001B[39;00m _global_forward_pre_hooks):\n\u001B[1;32m-> 1190\u001B[0m \u001B[38;5;28;01mreturn\u001B[39;00m \u001B[43mforward_call\u001B[49m\u001B[43m(\u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[38;5;28;43minput\u001B[39;49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[43mkwargs\u001B[49m\u001B[43m)\u001B[49m\n\u001B[0;32m 1191\u001B[0m \u001B[38;5;66;03m# Do not call functions when jit is used\u001B[39;00m\n\u001B[0;32m 1192\u001B[0m full_backward_hooks, non_full_backward_hooks \u001B[38;5;241m=\u001B[39m [], []\n",
+ "File \u001B[1;32m~\\Documents\\graph4stackoverflow\\venv\\lib\\site-packages\\transformers\\models\\bert\\modeling_bert.py:419\u001B[0m, in \u001B[0;36mBertAttention.forward\u001B[1;34m(self, hidden_states, attention_mask, head_mask, encoder_hidden_states, encoder_attention_mask, past_key_value, output_attentions)\u001B[0m\n\u001B[0;32m 409\u001B[0m \u001B[38;5;28;01mdef\u001B[39;00m \u001B[38;5;21mforward\u001B[39m(\n\u001B[0;32m 410\u001B[0m \u001B[38;5;28mself\u001B[39m,\n\u001B[0;32m 411\u001B[0m hidden_states: torch\u001B[38;5;241m.\u001B[39mTensor,\n\u001B[1;32m (...)\u001B[0m\n\u001B[0;32m 417\u001B[0m output_attentions: Optional[\u001B[38;5;28mbool\u001B[39m] \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;01mFalse\u001B[39;00m,\n\u001B[0;32m 418\u001B[0m ) \u001B[38;5;241m-\u001B[39m\u001B[38;5;241m>\u001B[39m Tuple[torch\u001B[38;5;241m.\u001B[39mTensor]:\n\u001B[1;32m--> 419\u001B[0m self_outputs \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;43mself\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mself\u001B[49m\u001B[43m(\u001B[49m\n\u001B[0;32m 420\u001B[0m \u001B[43m \u001B[49m\u001B[43mhidden_states\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 421\u001B[0m \u001B[43m \u001B[49m\u001B[43mattention_mask\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 422\u001B[0m \u001B[43m \u001B[49m\u001B[43mhead_mask\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 423\u001B[0m \u001B[43m \u001B[49m\u001B[43mencoder_hidden_states\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 424\u001B[0m \u001B[43m \u001B[49m\u001B[43mencoder_attention_mask\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 425\u001B[0m \u001B[43m \u001B[49m\u001B[43mpast_key_value\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 426\u001B[0m \u001B[43m \u001B[49m\u001B[43moutput_attentions\u001B[49m\u001B[43m,\u001B[49m\n\u001B[0;32m 427\u001B[0m \u001B[43m \u001B[49m\u001B[43m)\u001B[49m\n\u001B[0;32m 428\u001B[0m attention_output \u001B[38;5;241m=\u001B[39m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39moutput(self_outputs[\u001B[38;5;241m0\u001B[39m], hidden_states)\n\u001B[0;32m 429\u001B[0m outputs \u001B[38;5;241m=\u001B[39m (attention_output,) \u001B[38;5;241m+\u001B[39m self_outputs[\u001B[38;5;241m1\u001B[39m:] \u001B[38;5;66;03m# add attentions if we output them\u001B[39;00m\n",
+ "File \u001B[1;32m~\\Documents\\graph4stackoverflow\\venv\\lib\\site-packages\\torch\\nn\\modules\\module.py:1190\u001B[0m, in \u001B[0;36mModule._call_impl\u001B[1;34m(self, *input, **kwargs)\u001B[0m\n\u001B[0;32m 1186\u001B[0m \u001B[38;5;66;03m# If we don't have any hooks, we want to skip the rest of the logic in\u001B[39;00m\n\u001B[0;32m 1187\u001B[0m \u001B[38;5;66;03m# this function, and just call forward.\u001B[39;00m\n\u001B[0;32m 1188\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m \u001B[38;5;129;01mnot\u001B[39;00m (\u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_backward_hooks \u001B[38;5;129;01mor\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_forward_hooks \u001B[38;5;129;01mor\u001B[39;00m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39m_forward_pre_hooks \u001B[38;5;129;01mor\u001B[39;00m _global_backward_hooks\n\u001B[0;32m 1189\u001B[0m \u001B[38;5;129;01mor\u001B[39;00m _global_forward_hooks \u001B[38;5;129;01mor\u001B[39;00m _global_forward_pre_hooks):\n\u001B[1;32m-> 1190\u001B[0m \u001B[38;5;28;01mreturn\u001B[39;00m \u001B[43mforward_call\u001B[49m\u001B[43m(\u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[38;5;28;43minput\u001B[39;49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[38;5;241;43m*\u001B[39;49m\u001B[43mkwargs\u001B[49m\u001B[43m)\u001B[49m\n\u001B[0;32m 1191\u001B[0m \u001B[38;5;66;03m# Do not call functions when jit is used\u001B[39;00m\n\u001B[0;32m 1192\u001B[0m full_backward_hooks, non_full_backward_hooks \u001B[38;5;241m=\u001B[39m [], []\n",
+ "File \u001B[1;32m~\\Documents\\graph4stackoverflow\\venv\\lib\\site-packages\\transformers\\models\\bert\\modeling_bert.py:347\u001B[0m, in \u001B[0;36mBertSelfAttention.forward\u001B[1;34m(self, hidden_states, attention_mask, head_mask, encoder_hidden_states, encoder_attention_mask, past_key_value, output_attentions)\u001B[0m\n\u001B[0;32m 344\u001B[0m attention_scores \u001B[38;5;241m=\u001B[39m attention_scores \u001B[38;5;241m+\u001B[39m attention_mask\n\u001B[0;32m 346\u001B[0m \u001B[38;5;66;03m# Normalize the attention scores to probabilities.\u001B[39;00m\n\u001B[1;32m--> 347\u001B[0m attention_probs \u001B[38;5;241m=\u001B[39m \u001B[43mnn\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mfunctional\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43msoftmax\u001B[49m\u001B[43m(\u001B[49m\u001B[43mattention_scores\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[43mdim\u001B[49m\u001B[38;5;241;43m=\u001B[39;49m\u001B[38;5;241;43m-\u001B[39;49m\u001B[38;5;241;43m1\u001B[39;49m\u001B[43m)\u001B[49m\n\u001B[0;32m 349\u001B[0m \u001B[38;5;66;03m# This is actually dropping out entire tokens to attend to, which might\u001B[39;00m\n\u001B[0;32m 350\u001B[0m \u001B[38;5;66;03m# seem a bit unusual, but is taken from the original Transformer paper.\u001B[39;00m\n\u001B[0;32m 351\u001B[0m attention_probs \u001B[38;5;241m=\u001B[39m \u001B[38;5;28mself\u001B[39m\u001B[38;5;241m.\u001B[39mdropout(attention_probs)\n",
+ "File \u001B[1;32m~\\Documents\\graph4stackoverflow\\venv\\lib\\site-packages\\torch\\nn\\functional.py:1841\u001B[0m, in \u001B[0;36msoftmax\u001B[1;34m(input, dim, _stacklevel, dtype)\u001B[0m\n\u001B[0;32m 1839\u001B[0m dim \u001B[38;5;241m=\u001B[39m _get_softmax_dim(\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124msoftmax\u001B[39m\u001B[38;5;124m\"\u001B[39m, \u001B[38;5;28minput\u001B[39m\u001B[38;5;241m.\u001B[39mdim(), _stacklevel)\n\u001B[0;32m 1840\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m dtype \u001B[38;5;129;01mis\u001B[39;00m \u001B[38;5;28;01mNone\u001B[39;00m:\n\u001B[1;32m-> 1841\u001B[0m ret \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;43minput\u001B[39;49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43msoftmax\u001B[49m\u001B[43m(\u001B[49m\u001B[43mdim\u001B[49m\u001B[43m)\u001B[49m\n\u001B[0;32m 1842\u001B[0m \u001B[38;5;28;01melse\u001B[39;00m:\n\u001B[0;32m 1843\u001B[0m ret \u001B[38;5;241m=\u001B[39m \u001B[38;5;28minput\u001B[39m\u001B[38;5;241m.\u001B[39msoftmax(dim, dtype\u001B[38;5;241m=\u001B[39mdtype)\n",
+ "\u001B[1;31mKeyboardInterrupt\u001B[0m: "
+ ]
+ }
+ ],
+ "source": [
+ "import torch_geometric.transforms as T\n",
+ "graph_out = graph_constructor.construct(questions_df, answers_df, comments_df)\n",
+ "#graph_out['module'].x = torch.empty(0, 110, dtype=torch.long)\n",
+ "graph_out"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "outputs": [],
+ "source": [
+ "graph_out.__setattr__('question_emb', torch.rand(300))\n",
+ "graph_out.edge_index_dict"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "outputs": [],
+ "source": [
+ "from torch_geometric.utils import to_networkx\n",
+ "\n",
+ "nx_graph = to_networkx(graph_out.to_homogeneous())\n",
+ "pos_ug = nx.spring_layout(nx_graph)#, k=0.15, iterations=20)\n",
+ "plt.figure(figsize=(40,40))\n",
+ "nx.draw(nx_graph, pos_ug, with_labels=True)\n"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "markdown",
+ "source": [
+ "Let's build a GNN"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "outputs": [],
+ "source": [
+ "from torch.nn import Linear\n",
+ "import torch.nn.functional as F\n",
+ "from torch_geometric.nn import GCNConv, MeanAggregation, GATConv\n",
+ "from torch_geometric.nn import global_mean_pool\n",
+ "\n",
+ "\n",
+ "class GAT(torch.nn.Module):\n",
+ " def __init__(self, hidden_channels):\n",
+ " super(GAT, self).__init__()\n",
+ " torch.manual_seed(12345)\n",
+ " self.conv1 = GATConv((-1, -1), hidden_channels, add_self_loops=False)\n",
+ " self.conv2 = GATConv((-1, -1), hidden_channels, add_self_loops=False)\n",
+ " self.conv3 = GATConv((-1, -1), hidden_channels, add_self_loops=False)\n",
+ " self.lin = Linear(hidden_channels, 2)\n",
+ " self.softmax = torch.nn.Softmax(dim=1)\n",
+ " #self.pool = global_mean_pool()#MeanAggregation()\n",
+ "\n",
+ " def forward(self, x, edge_index, batch, post_emb):\n",
+ " # 1. Obtain node embeddings\n",
+ " x = self.conv1(x, edge_index)\n",
+ " x = x.relu()\n",
+ " x = self.conv2(x, edge_index)\n",
+ " x = x.relu()\n",
+ " x = self.conv3(x, edge_index)\n",
+ "\n",
+ " # 2. Readout layer\n",
+ " x = self.pool(x, batch) # [batch_size, hidden_channels]\n",
+ " #x = torch.cat((x, post_emb))\n",
+ " # 3. Apply a final classifier\n",
+ " # x = F.dropout(x, p=0.5, training=self.training)\n",
+ " x = self.lin(x)\n",
+ "\n",
+ " #x = self.softmax(x)\n",
+ " return x\n",
+ "model = GAT(hidden_channels=64)\n",
+ "print(model)"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "outputs": [],
+ "source": [
+ "from torch_geometric.nn.module_dict import ModuleDict\n",
+ "from torch_geometric.nn import HeteroConv\n",
+ "\n",
+ "\n",
+ "class HeteroGNN(torch.nn.Module):\n",
+ " def __init__(self, hidden_channels, out_channels, num_layers):\n",
+ " super().__init__()\n",
+ "\n",
+ " self.convs = torch.nn.ModuleList()\n",
+ " for _ in range(num_layers):\n",
+ " conv = HeteroConv({\n",
+ " ('tag', 'describes', 'question') : GATConv((-1,-1), hidden_channels, add_self_loops=False),\n",
+ " ('tag', 'describes', 'answer') : GATConv((-1,-1), hidden_channels, add_self_loops=False),\n",
+ " ('tag', 'describes', 'comment') : GATConv((-1,-1), hidden_channels, add_self_loops=False),\n",
+ " ('module', 'imported_in', 'question') : GATConv((-1,-1), hidden_channels, add_self_loops=False),\n",
+ " ('module', 'imported_in', 'answer') : GATConv((-1,-1), hidden_channels, add_self_loops=False),\n",
+ " ('question', 'rev_describes', 'tag') : GATConv((-1,-1), hidden_channels, add_self_loops=False),\n",
+ " ('answer', 'rev_describes', 'tag') : GATConv((-1,-1), hidden_channels, add_self_loops=False),\n",
+ " ('comment', 'rev_describes', 'tag') : GATConv((-1,-1), hidden_channels, add_self_loops=False),\n",
+ " ('question', 'rev_imported_in', 'module') : GATConv((-1,-1), hidden_channels, add_self_loops=False),\n",
+ " ('answer', 'rev_imported_in', 'module') : GATConv((-1,-1), hidden_channels, add_self_loops=False),\n",
+ " }, aggr='sum')\n",
+ " self.convs.append(conv)\n",
+ "\n",
+ " self.lin = Linear(hidden_channels, out_channels)\n",
+ " #self.softmax = torch.nn.Softmax(dim=1)\n",
+ "\n",
+ "\n",
+ " def forward(self, x_dict, edge_index_dict, batch_dict, post_emb=2):\n",
+ " for conv in self.convs:\n",
+ " x_dict = conv(x_dict, edge_index_dict)\n",
+ " x_dict = {key: x.relu() for key, x in x_dict.items()}\n",
+ " #return x_dict\n",
+ " outs = []\n",
+ " for x, batch in zip(x_dict.values(), batch_dict.values()):\n",
+ " outs.append(global_mean_pool(x, batch))\n",
+ " out = torch.cat(outs, dim=-1)\n",
+ "\n",
+ " return out\n",
+ "\n",
+ "\n",
+ "hgnn = HeteroGNN(hidden_channels=64, out_channels=2, num_layers=3)\n",
+ "hgnn"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "outputs": [],
+ "source": [
+ "hgnn(graph_out.x_dict, graph_out.edge_index_dict, graph_out.batch_dict, 1)"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "outputs": [],
+ "source": [
+ "from torch_geometric.nn import to_hetero, to_hetero_with_bases\n",
+ "\n",
+ "metadata = (['question', 'answer', 'comment', 'tag', 'module'], [('tag', 'describes', 'question'), ('tag', 'describes', 'answer'), ('tag', 'describes', 'comment'), ('module', 'imported_in', 'question'), ('module', 'imported_in', 'answer'), ('question', 'rev_describes', 'tag'), ('answer', 'rev_describes', 'tag'), ('comment', 'rev_describes', 'tag'), ('question', 'rev_imported_in', 'module'), ('answer', 'rev_imported_in', 'module')])\n",
+ "model = to_hetero(model, metadata)\n",
+ "model"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "outputs": [],
+ "source": [
+ "model(graph_out.x_dict, graph_out.edge_index_dict, graph_out.batch_dict, 1)"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "outputs": [],
+ "source": [
+ "graph_out.batch_dict"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "outputs": [],
+ "source": [
+ "print(\"Question ndim:\", graph_out.x_dict['question'].dim())\n",
+ "print(\"Answer ndim:\", graph_out.x_dict['answer'].dim())\n",
+ "print(\"Comment ndim:\", graph_out.x_dict['comment'].dim())\n",
+ "print(\"Tag ndim:\", graph_out.x_dict['tag'].dim())\n",
+ "print(\"Module ndim:\", graph_out.x_dict['module'].dim())"
+ ],
+ "metadata": {
+ "collapsed": false
+ }
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "outputs": [],
+ "source": [],
+ "metadata": {
+ "collapsed": false
+ }
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.6"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
diff --git a/archived/tag_embedding_trainer.py b/archived/tag_embedding_trainer.py
index e1cc3a625ecc6b5a9e5e89ed8f6a2ad96cad13bb..d6383f0b0331152631163360729ec800316a0086 100644
--- a/archived/tag_embedding_trainer.py
+++ b/archived/tag_embedding_trainer.py
@@ -1,147 +1,147 @@
-import itertools
-import logging
-import sqlite3
-import time
-from typing import *
-import random
-
-from tqdm import tqdm
-import pandas as pd
-import torch
-from torch import nn, optim
-from torch.functional import F
-from torch.utils.tensorboard import SummaryWriter
-
-logging.basicConfig(level=logging.INFO)
-
-
-class TagEmbeddingTrainer:
-
- def __init__(self, database_path: str = None):
- logger = logging.getLogger(self.__class__.__name__)
- self.device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
- logger.info(f"Proceeding with {self.device} . .")
- if database_path is not None:
- self.db = sqlite3.connect(database_path)
- logger.info(f"Connected to {database_path}")
- self.tag_vocab: List[str]
- self.post_tags: List[Tuple]
-
- def from_files(self, post_tags_path: str, tag_vocab: str):
- tag_df = pd.read_csv(tag_vocab, keep_default_na=False)
- self.tag_vocab = list(set(tag_df["TagName"]))
-
- post_tags = pd.read_csv(post_tags_path)
- tag_list_df = post_tags['Tags'].apply(lambda row: self.parse_tag_list(row))
- combinations = tag_list_df.apply(lambda row: list(itertools.combinations(row, 2)))
- combinations = combinations[combinations.astype(str) != '[]']
- # Now concatenate all the lists together
- tag_pairs = []
- for i in combinations:
- tag_pairs += i
- self.post_tags = tag_pairs
-
-
- def from_db(self):
- tag_df = pd.read_sql_query("SELECT * FROM Tag", self.db)
- tag_df.set_index('TagId', inplace=True)
- self.tag_vocab = list(set(tag_df["TagName"]))
-
- post_tags = pd.read_sql_query(f"SELECT Tags FROM Post WHERE PostTypeId=1", self.db)
- tag_list_df = post_tags['Tags'].map(self.parse_tag_list)
- combinations = tag_list_df.apply(lambda row: list(itertools.combinations(row, 2)))
- combinations = combinations[combinations.astype(str) != '[]']
- # Now concatenate all the lists together
- tag_pairs = []
- for i in combinations:
- tag_pairs += i
- self.post_tags = tag_pairs
-
- def parse_tag_list(self, tag_list: str) -> List[str]:
- return tag_list[1:-1].split("><")
-
- def sample_n(self, df, train_size: int):
- return random.sample(df, train_size)
-
- def train(self, train_size: int, epochs: int):
- # Loss
- loss_function = nn.NLLLoss()
- losses = []
- # Model
- self.model = TagEmbedding(vocab_size=len(self.tag_vocab), embedding_dim=20).to(self.device)
- # Optimizer
- optimizer = optim.SGD(self.model.parameters(), lr=0.001)
- # Enumerate the vocabulary, reflects the index of where the 1 is in the one-hot
- self.tag_to_ix = {tag: i for i, tag in enumerate(self.tag_vocab)}
- # Reduce size of training set
- samples = self.sample_n(self.post_tags, train_size)
-
- for epoch in range(epochs):
- total_loss = 0
- for tag_a, tag_b in tqdm(samples):
- tag_a_id = torch.tensor(self.tag_to_ix[tag_a], dtype=torch.long).to(self.device)
- self.model.zero_grad()
- log_probs = self.model(tag_a_id)
- loss = loss_function(log_probs.flatten(), torch.tensor(self.tag_to_ix[tag_b], dtype=torch.long).to(self.device))
- loss.backward()
- optimizer.step()
- total_loss += loss.item()
- losses.append(total_loss)
-
- def get_tag_embedding(self, tag: str):
- return self.model.embedding.weight[self.tag_to_ix[tag]]
-
- def to_tensorboard(self, run_name: str):
- """
- Write embedding to Tensorboard projector
- tensorboard --logdir="runs/run@20221102-173048"
- """
- writer = SummaryWriter(f'runs/{run_name}')
- writer.add_embedding(self.model.embedding.weight,
- metadata=self.tag_vocab,
- tag=f'Tag embedding')
- writer.close()
-
- def load_model(self, model_path: str, vocab_size: int, embedding_dim: int):
- self.model = TagEmbedding(vocab_size, embedding_dim)
- self.model.load_state_dict(torch.load(model_path, map_location=torch.device('cpu')))
-
-
- def save_model(self, model_path: str):
- torch.save(self.model.state_dict(), model_path)
-
-
-
-
-
-class TagEmbedding(nn.Module):
-
- def __init__(self, vocab_size, embedding_dim):
- super(TagEmbedding, self).__init__()
- self.embedding = nn.Embedding(vocab_size, embedding_dim)
- self.linear1 = nn.Linear(embedding_dim, 128)
- self.linear2 = nn.Linear(128, vocab_size)
-
- def forward(self, inputs):
- embeds = self.embedding(inputs).view((1, -1))
- out = F.relu(self.linear1(embeds))
- out = self.linear2(out)
- log_probs = F.log_softmax(out, dim=1)
- return log_probs
-
-
-if __name__ == '__main__':
- #tet = TagEmbeddingTrainer("../stackoverflow.db")
- #tet.from_db()
- tet = TagEmbeddingTrainer()
- tet.from_files("all_tags.csv", "tag_vocab.csv")
- assert len(tet.post_tags) == 84187510, "Incorrect number of post tags!"
- assert len(tet.tag_vocab) == 63653, "Incorrect vocab size!"
-
- # tet.train(25000000, 1)
- # tet.to_tensorboard(f"run@{time.strftime('%Y%m%d-%H%M%S')}")
-
- #tet.save_model("25mil.pt")
- tet.load_model("10mil_500d_embd.pt", 63653, 500)
- tet.to_tensorboard(f"run@{time.strftime('%Y%m%d-%H%M%S')}")
-
+import itertools
+import logging
+import sqlite3
+import time
+from typing import *
+import random
+
+from tqdm import tqdm
+import pandas as pd
+import torch
+from torch import nn, optim
+from torch.functional import F
+from torch.utils.tensorboard import SummaryWriter
+
+logging.basicConfig(level=logging.INFO)
+
+
+class TagEmbeddingTrainer:
+
+ def __init__(self, database_path: str = None):
+ logger = logging.getLogger(self.__class__.__name__)
+ self.device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+ logger.info(f"Proceeding with {self.device} . .")
+ if database_path is not None:
+ self.db = sqlite3.connect(database_path)
+ logger.info(f"Connected to {database_path}")
+ self.tag_vocab: List[str]
+ self.post_tags: List[Tuple]
+
+ def from_files(self, post_tags_path: str, tag_vocab: str):
+ tag_df = pd.read_csv(tag_vocab, keep_default_na=False)
+ self.tag_vocab = list(set(tag_df["TagName"]))
+
+ post_tags = pd.read_csv(post_tags_path)
+ tag_list_df = post_tags['Tags'].apply(lambda row: self.parse_tag_list(row))
+ combinations = tag_list_df.apply(lambda row: list(itertools.combinations(row, 2)))
+ combinations = combinations[combinations.astype(str) != '[]']
+ # Now concatenate all the lists together
+ tag_pairs = []
+ for i in combinations:
+ tag_pairs += i
+ self.post_tags = tag_pairs
+
+
+ def from_db(self):
+ tag_df = pd.read_sql_query("SELECT * FROM Tag", self.db)
+ tag_df.set_index('TagId', inplace=True)
+ self.tag_vocab = list(set(tag_df["TagName"]))
+
+ post_tags = pd.read_sql_query(f"SELECT Tags FROM Post WHERE PostTypeId=1", self.db)
+ tag_list_df = post_tags['Tags'].map(self.parse_tag_list)
+ combinations = tag_list_df.apply(lambda row: list(itertools.combinations(row, 2)))
+ combinations = combinations[combinations.astype(str) != '[]']
+ # Now concatenate all the lists together
+ tag_pairs = []
+ for i in combinations:
+ tag_pairs += i
+ self.post_tags = tag_pairs
+
+ def parse_tag_list(self, tag_list: str) -> List[str]:
+ return tag_list[1:-1].split("><")
+
+ def sample_n(self, df, train_size: int):
+ return random.sample(df, train_size)
+
+ def train(self, train_size: int, epochs: int):
+ # Loss
+ loss_function = nn.NLLLoss()
+ losses = []
+ # Model
+ self.model = TagEmbedding(vocab_size=len(self.tag_vocab), embedding_dim=20).to(self.device)
+ # Optimizer
+ optimizer = optim.SGD(self.model.parameters(), lr=0.001)
+ # Enumerate the vocabulary, reflects the index of where the 1 is in the one-hot
+ self.tag_to_ix = {tag: i for i, tag in enumerate(self.tag_vocab)}
+ # Reduce size of training set
+ samples = self.sample_n(self.post_tags, train_size)
+
+ for epoch in range(epochs):
+ total_loss = 0
+ for tag_a, tag_b in tqdm(samples):
+ tag_a_id = torch.tensor(self.tag_to_ix[tag_a], dtype=torch.long).to(self.device)
+ self.model.zero_grad()
+ log_probs = self.model(tag_a_id)
+ loss = loss_function(log_probs.flatten(), torch.tensor(self.tag_to_ix[tag_b], dtype=torch.long).to(self.device))
+ loss.backward()
+ optimizer.step()
+ total_loss += loss.item()
+ losses.append(total_loss)
+
+ def get_tag_embedding(self, tag: str):
+ return self.model.embedding.weight[self.tag_to_ix[tag]]
+
+ def to_tensorboard(self, run_name: str):
+ """
+ Write embedding to Tensorboard projector
+ tensorboard --logdir="runs/run@20221102-173048"
+ """
+ writer = SummaryWriter(f'runs/{run_name}')
+ writer.add_embedding(self.model.embedding.weight,
+ metadata=self.tag_vocab,
+ tag=f'Tag embedding')
+ writer.close()
+
+ def load_model(self, model_path: str, vocab_size: int, embedding_dim: int):
+ self.model = TagEmbedding(vocab_size, embedding_dim)
+ self.model.load_state_dict(torch.load(model_path, map_location=torch.device('cpu')))
+
+
+ def save_model(self, model_path: str):
+ torch.save(self.model.state_dict(), model_path)
+
+
+
+
+
+class TagEmbedding(nn.Module):
+
+ def __init__(self, vocab_size, embedding_dim):
+ super(TagEmbedding, self).__init__()
+ self.embedding = nn.Embedding(vocab_size, embedding_dim)
+ self.linear1 = nn.Linear(embedding_dim, 128)
+ self.linear2 = nn.Linear(128, vocab_size)
+
+ def forward(self, inputs):
+ embeds = self.embedding(inputs).view((1, -1))
+ out = F.relu(self.linear1(embeds))
+ out = self.linear2(out)
+ log_probs = F.log_softmax(out, dim=1)
+ return log_probs
+
+
+if __name__ == '__main__':
+ #tet = TagEmbeddingTrainer("../stackoverflow.db")
+ #tet.from_db()
+ tet = TagEmbeddingTrainer()
+ tet.from_files("all_tags.csv", "tag_vocab.csv")
+ assert len(tet.post_tags) == 84187510, "Incorrect number of post tags!"
+ assert len(tet.tag_vocab) == 63653, "Incorrect vocab size!"
+
+ # tet.train(25000000, 1)
+ # tet.to_tensorboard(f"run@{time.strftime('%Y%m%d-%H%M%S')}")
+
+ #tet.save_model("25mil.pt")
+ tet.load_model("10mil_500d_embd.pt", 63653, 500)
+ tet.to_tensorboard(f"run@{time.strftime('%Y%m%d-%H%M%S')}")
+
diff --git a/data-collection/SQLiteSession.java b/data-collection/SQLiteSession.java
index ba8ecca8fd78ab981d84e69c95866c4258c2b495..de00275ebe7a9a2ce095fe6e9bb0e85cb1283dcc 100644
--- a/data-collection/SQLiteSession.java
+++ b/data-collection/SQLiteSession.java
@@ -1,81 +1,81 @@
-import org.apache.logging.log4j.Level;
-import org.apache.logging.log4j.LogManager;
-import org.apache.logging.log4j.Logger;
-import org.apache.logging.log4j.core.config.Configurator;
-
-import java.io.IOException;
-import java.nio.file.Files;
-import java.nio.file.Path;
-import java.sql.*;
-
-public class SQLiteSession {
- private final Logger logger = LogManager.getLogger(SQLiteSession.class);
- private Connection conn;
-
- private PreparedStatement ps;
-
- private int maxBatchSize;
- private int currentBatchsize = 0;
-
- public SQLiteSession(String url) {
- Configurator.setLevel(logger.getName(), Level.WARN);
- try {
- // create a connection to the database
- conn = DriverManager.getConnection(url);
- conn.setAutoCommit(false);
- logger.info("Connection to SQLite has been established.");
- } catch (SQLException e) {
- logger.error(e.getMessage());
- }
- }
-
- public void endSession() {
- try {
- if (conn != null) {
- conn.close();
- }
- } catch (SQLException ex) {
- logger.error(ex.getMessage());
- }
- }
-
- public void createTables() throws SQLException, IOException {
- /**
- * Create tables using the `create.sql` file in the directory
- */
- Statement stmt = conn.createStatement();
- String query = Files.readString(Path.of("create.sql"));
- stmt.executeUpdate(query);
- conn.commit();
- }
-
- public void setPreparedStatement(String baseQuery, int batchSize) throws SQLException {
- this.ps = conn.prepareStatement(baseQuery);
- this.maxBatchSize = batchSize;
- }
-
- public PreparedStatement getPreparedStatement() {
- return ps;
- }
-
- public void processBatch() throws SQLException {
- ps.addBatch();
- if (++currentBatchsize > maxBatchSize) {
- ps.executeBatch();
- currentBatchsize = 0;
- logger.info("Executed batch insert.");
- }
- }
-
- public void commitChanges() throws SQLException {
- conn.commit();
- }
-
- public static void main(String[] args) throws SQLException, IOException {
- SQLiteSession s = new SQLiteSession(
- "jdbc:sqlite:..\\stackoverflow.db"
- );
- s.createTables();
- s.endSession();
- }
+import org.apache.logging.log4j.Level;
+import org.apache.logging.log4j.LogManager;
+import org.apache.logging.log4j.Logger;
+import org.apache.logging.log4j.core.config.Configurator;
+
+import java.io.IOException;
+import java.nio.file.Files;
+import java.nio.file.Path;
+import java.sql.*;
+
+public class SQLiteSession {
+ private final Logger logger = LogManager.getLogger(SQLiteSession.class);
+ private Connection conn;
+
+ private PreparedStatement ps;
+
+ private int maxBatchSize;
+ private int currentBatchsize = 0;
+
+ public SQLiteSession(String url) {
+ Configurator.setLevel(logger.getName(), Level.WARN);
+ try {
+ // create a connection to the database
+ conn = DriverManager.getConnection(url);
+ conn.setAutoCommit(false);
+ logger.info("Connection to SQLite has been established.");
+ } catch (SQLException e) {
+ logger.error(e.getMessage());
+ }
+ }
+
+ public void endSession() {
+ try {
+ if (conn != null) {
+ conn.close();
+ }
+ } catch (SQLException ex) {
+ logger.error(ex.getMessage());
+ }
+ }
+
+ public void createTables() throws SQLException, IOException {
+ /**
+ * Create tables using the `create.sql` file in the directory
+ */
+ Statement stmt = conn.createStatement();
+ String query = Files.readString(Path.of("create.sql"));
+ stmt.executeUpdate(query);
+ conn.commit();
+ }
+
+ public void setPreparedStatement(String baseQuery, int batchSize) throws SQLException {
+ this.ps = conn.prepareStatement(baseQuery);
+ this.maxBatchSize = batchSize;
+ }
+
+ public PreparedStatement getPreparedStatement() {
+ return ps;
+ }
+
+ public void processBatch() throws SQLException {
+ ps.addBatch();
+ if (++currentBatchsize > maxBatchSize) {
+ ps.executeBatch();
+ currentBatchsize = 0;
+ logger.info("Executed batch insert.");
+ }
+ }
+
+ public void commitChanges() throws SQLException {
+ conn.commit();
+ }
+
+ public static void main(String[] args) throws SQLException, IOException {
+ SQLiteSession s = new SQLiteSession(
+ "jdbc:sqlite:..\\stackoverflow.db"
+ );
+ s.createTables();
+ s.endSession();
+ }
}
\ No newline at end of file
diff --git a/data-collection/StackOverflowHandler.java b/data-collection/StackOverflowHandler.java
index 7e9caa989270e0da988c239aa5b5f4637362a08f..2d2c3b6e3ef6cfc8cb6a6cb025409a9d39ccd76a 100644
--- a/data-collection/StackOverflowHandler.java
+++ b/data-collection/StackOverflowHandler.java
@@ -1,124 +1,124 @@
-import org.apache.logging.log4j.Level;
-import org.apache.logging.log4j.LogManager;
-import org.apache.logging.log4j.Logger;
-import org.apache.logging.log4j.core.config.Configurator;
-import org.xml.sax.Attributes;
-import org.xml.sax.SAXException;
-import org.xml.sax.helpers.DefaultHandler;
-
-import javax.xml.XMLConstants;
-import javax.xml.parsers.ParserConfigurationException;
-import javax.xml.parsers.SAXParser;
-import javax.xml.parsers.SAXParserFactory;
-import java.io.IOException;
-import java.sql.SQLException;
-
-public class StackOverflowHandler extends DefaultHandler {
- private final SQLiteSession session;
- private final String baseInsertQuery;
-
- private final String[] attributeNames;
-
- private final Logger logger = LogManager.getLogger(StackOverflowHandler.class);
-
- public StackOverflowHandler(String pathToDB, String baseInsertQuery, String[] attributeNames) {
- Configurator.setLevel(logger.getName(), Level.INFO);
- this.session = new SQLiteSession(pathToDB);
- this.baseInsertQuery = baseInsertQuery;
- this.attributeNames = attributeNames;
- }
-
- public Logger getLogger() {
- return logger;
- }
-
- public SQLiteSession getSession() {
- return session;
- }
-
- @Override
- public void startDocument() {
- try {
- session.setPreparedStatement(baseInsertQuery, 500);
- } catch (SQLException e) {
- throw new RuntimeException(e);
- }
- }
-
- @Override
- public void startElement(String uri, String lName, String qName, Attributes attr) {
- if (qName.equals("row")) {
- try {
- for (int i = 0; i < attributeNames.length; i++) {
- getSession().getPreparedStatement().setString(i+1, attr.getValue(attributeNames[i]));
- }
- getSession().processBatch();
-
- } catch (SQLException e) {
- getLogger().error(String.format("SQL Error! %s", e));
- }
-
- } else {
- getLogger().error(String.format("Non-row encountered: %s", qName));
- }
- }
-
- @Override
- public void endDocument() {
- try {
- session.getPreparedStatement().executeBatch();
- session.commitChanges();
- } catch (SQLException e) {
- throw new RuntimeException(e);
- }
- }
-}
-
-
-
-class Main {
- public static void main(String[] args) throws ParserConfigurationException, SAXException, IOException {
- final long start = System.currentTimeMillis();
- String PATH_TO_DB = "jdbc:sqlite:..\\stackoverflow.db";
-
- // New SAXParser
- SAXParserFactory factory = SAXParserFactory.newInstance();
- factory.setFeature(XMLConstants.FEATURE_SECURE_PROCESSING,false);
- SAXParser saxParser = factory.newSAXParser();
-
- /*// Tags
- String[] tagAttributeNames = {"Id", "TagName", "Count"};
- StackOverflowHandler tagsHandler = new StackOverflowHandler(PATH_TO_DB, "INSERT INTO Tag VALUES (?, ?, ?)", tagAttributeNames);
- saxParser.parse("..\\data\\raw\\stackoverflow.com-Tags\\tags.xml", tagsHandler);
-
- // Users
- String[] userAttributeNames = {"Id", "Reputation", "CreationDate", "DisplayName", "LastAccessDate", "WebsiteUrl", "Location", "AboutMe", "Views", "UpVotes", "DownVotes", "ProfileImageUrl", "AccountId"};
- StackOverflowHandler usersHandler = new StackOverflowHandler(PATH_TO_DB, "INSERT INTO User VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)", userAttributeNames);
- saxParser.parse("..\\data\\raw\\stackoverflow.com-Users\\users.xml", usersHandler);
-*/
- // Posts
- String[] postAttributeNames = {"Id", "PostTypeId", "AcceptedAnswerId", "CreationDate", "Score", "ViewCount", "Body", "OwnerUserId", "LastEditorUserId", "LastEditorDisplayName", "LastEditDate", "Title", "Tags", "AnswerCount", "CommentCount", "FavoriteCount", "CommunityOwnedDate", "ContentLicense", "ParentId"};
- StackOverflowHandler postsHandler = new StackOverflowHandler(PATH_TO_DB, "INSERT INTO Post VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)", postAttributeNames);
- saxParser.parse("..\\data\\raw\\stackoverflow.com-Posts\\posts.xml", postsHandler);
-
- // Comments
- String[] commentAttributeNames = {"Id", "PostId", "Score", "Text", "CreationDate", "UserId", "ContentLicense"};
- StackOverflowHandler commentsHandler = new StackOverflowHandler(PATH_TO_DB, "INSERT INTO Comment VALUES (?, ?, ?, ?, ?, ?, ?)", commentAttributeNames);
- saxParser.parse("..\\data\\raw\\stackoverflow.com-Comments\\comments.xml", commentsHandler);
-
- // Badges
- String[] badgeAttributeNames = {"Id", "UserId", "Name", "Date", "Class", "TagBased"};
- StackOverflowHandler badgesHandler = new StackOverflowHandler(PATH_TO_DB, "INSERT INTO Badge VALUES (?, ?, ?, ?, ?, ?)", badgeAttributeNames);
- saxParser.parse("..\\data\\raw\\stackoverflow.com-Badges\\badges.xml", badgesHandler);
-
- // Votes
- String[] voteAttributeNames = {"Id", "PostId", "VoteTypeId", "CreationDate"};
- StackOverflowHandler votesHandler = new StackOverflowHandler(PATH_TO_DB, "INSERT INTO Vote VALUES (?, ?, ?, ?)", voteAttributeNames);
- saxParser.parse("..\\data\\raw\\stackoverflow.com-Votes\\votes.xml", votesHandler);
-
-
- // time end
- final long durationInMilliseconds = System.currentTimeMillis()-start;
- System.out.println("SAX parse took " + durationInMilliseconds + "ms.");
- }
+import org.apache.logging.log4j.Level;
+import org.apache.logging.log4j.LogManager;
+import org.apache.logging.log4j.Logger;
+import org.apache.logging.log4j.core.config.Configurator;
+import org.xml.sax.Attributes;
+import org.xml.sax.SAXException;
+import org.xml.sax.helpers.DefaultHandler;
+
+import javax.xml.XMLConstants;
+import javax.xml.parsers.ParserConfigurationException;
+import javax.xml.parsers.SAXParser;
+import javax.xml.parsers.SAXParserFactory;
+import java.io.IOException;
+import java.sql.SQLException;
+
+public class StackOverflowHandler extends DefaultHandler {
+ private final SQLiteSession session;
+ private final String baseInsertQuery;
+
+ private final String[] attributeNames;
+
+ private final Logger logger = LogManager.getLogger(StackOverflowHandler.class);
+
+ public StackOverflowHandler(String pathToDB, String baseInsertQuery, String[] attributeNames) {
+ Configurator.setLevel(logger.getName(), Level.INFO);
+ this.session = new SQLiteSession(pathToDB);
+ this.baseInsertQuery = baseInsertQuery;
+ this.attributeNames = attributeNames;
+ }
+
+ public Logger getLogger() {
+ return logger;
+ }
+
+ public SQLiteSession getSession() {
+ return session;
+ }
+
+ @Override
+ public void startDocument() {
+ try {
+ session.setPreparedStatement(baseInsertQuery, 500);
+ } catch (SQLException e) {
+ throw new RuntimeException(e);
+ }
+ }
+
+ @Override
+ public void startElement(String uri, String lName, String qName, Attributes attr) {
+ if (qName.equals("row")) {
+ try {
+ for (int i = 0; i < attributeNames.length; i++) {
+ getSession().getPreparedStatement().setString(i+1, attr.getValue(attributeNames[i]));
+ }
+ getSession().processBatch();
+
+ } catch (SQLException e) {
+ getLogger().error(String.format("SQL Error! %s", e));
+ }
+
+ } else {
+ getLogger().error(String.format("Non-row encountered: %s", qName));
+ }
+ }
+
+ @Override
+ public void endDocument() {
+ try {
+ session.getPreparedStatement().executeBatch();
+ session.commitChanges();
+ } catch (SQLException e) {
+ throw new RuntimeException(e);
+ }
+ }
+}
+
+
+
+class Main {
+ public static void main(String[] args) throws ParserConfigurationException, SAXException, IOException {
+ final long start = System.currentTimeMillis();
+ String PATH_TO_DB = "jdbc:sqlite:..\\stackoverflow.db";
+
+ // New SAXParser
+ SAXParserFactory factory = SAXParserFactory.newInstance();
+ factory.setFeature(XMLConstants.FEATURE_SECURE_PROCESSING,false);
+ SAXParser saxParser = factory.newSAXParser();
+
+ /*// Tags
+ String[] tagAttributeNames = {"Id", "TagName", "Count"};
+ StackOverflowHandler tagsHandler = new StackOverflowHandler(PATH_TO_DB, "INSERT INTO Tag VALUES (?, ?, ?)", tagAttributeNames);
+ saxParser.parse("..\\data\\raw\\stackoverflow.com-Tags\\tags.xml", tagsHandler);
+
+ // Users
+ String[] userAttributeNames = {"Id", "Reputation", "CreationDate", "DisplayName", "LastAccessDate", "WebsiteUrl", "Location", "AboutMe", "Views", "UpVotes", "DownVotes", "ProfileImageUrl", "AccountId"};
+ StackOverflowHandler usersHandler = new StackOverflowHandler(PATH_TO_DB, "INSERT INTO User VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)", userAttributeNames);
+ saxParser.parse("..\\data\\raw\\stackoverflow.com-Users\\users.xml", usersHandler);
+*/
+ // Posts
+ String[] postAttributeNames = {"Id", "PostTypeId", "AcceptedAnswerId", "CreationDate", "Score", "ViewCount", "Body", "OwnerUserId", "LastEditorUserId", "LastEditorDisplayName", "LastEditDate", "Title", "Tags", "AnswerCount", "CommentCount", "FavoriteCount", "CommunityOwnedDate", "ContentLicense", "ParentId"};
+ StackOverflowHandler postsHandler = new StackOverflowHandler(PATH_TO_DB, "INSERT INTO Post VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)", postAttributeNames);
+ saxParser.parse("..\\data\\raw\\stackoverflow.com-Posts\\posts.xml", postsHandler);
+
+ // Comments
+ String[] commentAttributeNames = {"Id", "PostId", "Score", "Text", "CreationDate", "UserId", "ContentLicense"};
+ StackOverflowHandler commentsHandler = new StackOverflowHandler(PATH_TO_DB, "INSERT INTO Comment VALUES (?, ?, ?, ?, ?, ?, ?)", commentAttributeNames);
+ saxParser.parse("..\\data\\raw\\stackoverflow.com-Comments\\comments.xml", commentsHandler);
+
+ // Badges
+ String[] badgeAttributeNames = {"Id", "UserId", "Name", "Date", "Class", "TagBased"};
+ StackOverflowHandler badgesHandler = new StackOverflowHandler(PATH_TO_DB, "INSERT INTO Badge VALUES (?, ?, ?, ?, ?, ?)", badgeAttributeNames);
+ saxParser.parse("..\\data\\raw\\stackoverflow.com-Badges\\badges.xml", badgesHandler);
+
+ // Votes
+ String[] voteAttributeNames = {"Id", "PostId", "VoteTypeId", "CreationDate"};
+ StackOverflowHandler votesHandler = new StackOverflowHandler(PATH_TO_DB, "INSERT INTO Vote VALUES (?, ?, ?, ?)", voteAttributeNames);
+ saxParser.parse("..\\data\\raw\\stackoverflow.com-Votes\\votes.xml", votesHandler);
+
+
+ // time end
+ final long durationInMilliseconds = System.currentTimeMillis()-start;
+ System.out.println("SAX parse took " + durationInMilliseconds + "ms.");
+ }
}
\ No newline at end of file
diff --git a/data-collection/create.sql b/data-collection/create.sql
index 533ff610dbb54702eb8b54a9240c67da03d0158f..81a3ab8ec698a9cca68c9c8b58db64417fa544d9 100644
--- a/data-collection/create.sql
+++ b/data-collection/create.sql
@@ -1,82 +1,82 @@
-CREATE TABLE IF NOT EXISTS User (
- UserId INTEGER PRIMARY KEY,
- Reputation INTEGER,
- CreationDate TEXT,
- DisplayName TEXT,
- LastAccessDate TEXT,
- WebsiteUrl TEXT,
- Location Text,
- AboutMe Text,
- Views INTEGER,
- UpVotes INTEGER,
- DownVotes INTEGER,
- ProfileImageUrl TEXT,
- AccountId INTEGER
-);
-
-CREATE TABLE IF NOT EXISTS Post (
- PostId INTEGER PRIMARY KEY,
- PostTypeId INTEGER,
- AcceptedAnswerId INTEGER,
- CreationDate TEXT,
- Score INTEGER,
- ViewCount INTEGER,
- Body TEXT,
- OwnerUserId INTEGER,
- LastEditorUserId INTEGER,
- LastEditorDisplayName TEXT,
- LastEditDate TEXT,
- Title TEXT,
- Tags TEXT,
- AnswerCount INTEGER,
- CommentCount INTEGER,
- FavoriteCount INTEGER,
- CommunityOwnedDate TEXT,
- ContentLicense TEXT,
- ParentId INTEGER,
- FOREIGN KEY (OwnerUserId) REFERENCES User (UserId),
- FOREIGN KEY (LastEditorUserId) REFERENCES User (UserId)
-);
-
-CREATE TABLE IF NOT EXISTS Comment (
- CommentId INTEGER PRIMARY KEY,
- PostId INTEGER,
- Score INTEGER,
- Body TEXT,
- CreationDate TEXT,
- UserId INTEGER,
- ContentLicense TEXT,
- FOREIGN KEY (PostId) REFERENCES Post (PostId),
- FOREIGN KEY (UserId) REFERENCES User (UserId)
-
-);
-
-CREATE TABLE IF NOT EXISTS Badge (
- BadgeId INTEGER PRIMARY KEY,
- UserId INTEGER,
- Name TEXT,
- CreationDate TEXT,
- Class INTEGER,
- TagBased TEXT,
- FOREIGN KEY (UserId) REFERENCES User (UserId)
-);
-
-
-CREATE TABLE IF NOT EXISTS Tag (
- TagId INTEGER PRIMARY KEY,
- TagName TEXT,
- Count INTEGER
-);
-
-
-CREATE TABLE IF NOT EXISTS Vote (
- VoteId INTEGER PRIMARY KEY,
- PostId INTEGER,
- VoteTypeId INTEGER,
- CreationDate TEXT,
- FOREIGN KEY (PostId) REFERENCES Post (PostId)
-);
-
-
-CREATE INDEX owner_index ON Post (OwnerUserId);
+CREATE TABLE IF NOT EXISTS User (
+ UserId INTEGER PRIMARY KEY,
+ Reputation INTEGER,
+ CreationDate TEXT,
+ DisplayName TEXT,
+ LastAccessDate TEXT,
+ WebsiteUrl TEXT,
+ Location Text,
+ AboutMe Text,
+ Views INTEGER,
+ UpVotes INTEGER,
+ DownVotes INTEGER,
+ ProfileImageUrl TEXT,
+ AccountId INTEGER
+);
+
+CREATE TABLE IF NOT EXISTS Post (
+ PostId INTEGER PRIMARY KEY,
+ PostTypeId INTEGER,
+ AcceptedAnswerId INTEGER,
+ CreationDate TEXT,
+ Score INTEGER,
+ ViewCount INTEGER,
+ Body TEXT,
+ OwnerUserId INTEGER,
+ LastEditorUserId INTEGER,
+ LastEditorDisplayName TEXT,
+ LastEditDate TEXT,
+ Title TEXT,
+ Tags TEXT,
+ AnswerCount INTEGER,
+ CommentCount INTEGER,
+ FavoriteCount INTEGER,
+ CommunityOwnedDate TEXT,
+ ContentLicense TEXT,
+ ParentId INTEGER,
+ FOREIGN KEY (OwnerUserId) REFERENCES User (UserId),
+ FOREIGN KEY (LastEditorUserId) REFERENCES User (UserId)
+);
+
+CREATE TABLE IF NOT EXISTS Comment (
+ CommentId INTEGER PRIMARY KEY,
+ PostId INTEGER,
+ Score INTEGER,
+ Body TEXT,
+ CreationDate TEXT,
+ UserId INTEGER,
+ ContentLicense TEXT,
+ FOREIGN KEY (PostId) REFERENCES Post (PostId),
+ FOREIGN KEY (UserId) REFERENCES User (UserId)
+
+);
+
+CREATE TABLE IF NOT EXISTS Badge (
+ BadgeId INTEGER PRIMARY KEY,
+ UserId INTEGER,
+ Name TEXT,
+ CreationDate TEXT,
+ Class INTEGER,
+ TagBased TEXT,
+ FOREIGN KEY (UserId) REFERENCES User (UserId)
+);
+
+
+CREATE TABLE IF NOT EXISTS Tag (
+ TagId INTEGER PRIMARY KEY,
+ TagName TEXT,
+ Count INTEGER
+);
+
+
+CREATE TABLE IF NOT EXISTS Vote (
+ VoteId INTEGER PRIMARY KEY,
+ PostId INTEGER,
+ VoteTypeId INTEGER,
+ CreationDate TEXT,
+ FOREIGN KEY (PostId) REFERENCES Post (PostId)
+);
+
+
+CREATE INDEX owner_index ON Post (OwnerUserId);
CREATE INDEX commenter ON Comment (UserId);
\ No newline at end of file
diff --git a/data-collection/stack_exchange_api.py b/data-collection/stack_exchange_api.py
index c720caad1830b1ec1e4887aee0e332851e6b131b..4d281369471465568f3a2c8c824f40266813886a 100644
--- a/data-collection/stack_exchange_api.py
+++ b/data-collection/stack_exchange_api.py
@@ -1,67 +1,67 @@
-from stackapi import StackAPI, StackAPIError
-import logging
-from typing import List
-
-logging.basicConfig(level=logging.INFO)
-
-
-class StackExchangeAPI:
- def __init__(self, max_pages: int, page_size: int):
- try:
- self._SITE = StackAPI('stackoverflow')
- self._SITE.max_pages = max_pages
- self._SITE.page_size = page_size
- except StackAPIError as e:
- logging.error(" Error URL: {}".format(e.url))
- logging.error(" Error Code: {}".format(e.code))
- logging.error(" Error Error: {}".format(e.error))
- logging.error(" Error Message: {}".format(e.message))
-
- """
- The following methods will be used for data collection in Iteration 1:
- User-expertise graph
- """
-
- def get_user_ids(self) -> List[int]:
- """
- Request a set of users and return their ids.
- :return: List of ids
- """
- response = self._SITE.fetch(
- 'users', min=1000
- )
- user_ids = [user['account_id'] for user in response['items']]
- return user_ids
-
- def get_user_activity(self, account_ids: List[int]):
- """
- Get questions, answers, comments asked by the users
- :param account_ids: List of user ids
- :return:
- """
- if len(account_ids) > 100:
- logging.error("get_user_activity: account_ids should not have more than 100 ids.")
- return None
- response_answers = self._SITE.fetch(
- 'users/{ids}/answers', ids=account_ids, body=True
- )
- print(response_answers)
-
- response_questions = self._SITE.fetch(
- 'users/{ids}/questions', ids=account_ids, body=True
- )
-
- print(response_questions)
-
- response_comments = self._SITE.fetch(
- 'users/{ids}/comments', ids=account_ids
- )
-
- print(response_comments)
-
-
-if __name__ == '__main__':
- a = StackExchangeAPI(1, 100)
- ids = a.get_user_ids()
- print(len(ids))
- a.get_user_activity(ids)
+from stackapi import StackAPI, StackAPIError
+import logging
+from typing import List
+
+logging.basicConfig(level=logging.INFO)
+
+
+class StackExchangeAPI:
+ def __init__(self, max_pages: int, page_size: int):
+ try:
+ self._SITE = StackAPI('stackoverflow')
+ self._SITE.max_pages = max_pages
+ self._SITE.page_size = page_size
+ except StackAPIError as e:
+ logging.error(" Error URL: {}".format(e.url))
+ logging.error(" Error Code: {}".format(e.code))
+ logging.error(" Error Error: {}".format(e.error))
+ logging.error(" Error Message: {}".format(e.message))
+
+ """
+ The following methods will be used for data collection in Iteration 1:
+ User-expertise graph
+ """
+
+ def get_user_ids(self) -> List[int]:
+ """
+ Request a set of users and return their ids.
+ :return: List of ids
+ """
+ response = self._SITE.fetch(
+ 'users', min=1000
+ )
+ user_ids = [user['account_id'] for user in response['items']]
+ return user_ids
+
+ def get_user_activity(self, account_ids: List[int]):
+ """
+ Get questions, answers, comments asked by the users
+ :param account_ids: List of user ids
+ :return:
+ """
+ if len(account_ids) > 100:
+ logging.error("get_user_activity: account_ids should not have more than 100 ids.")
+ return None
+ response_answers = self._SITE.fetch(
+ 'users/{ids}/answers', ids=account_ids, body=True
+ )
+ print(response_answers)
+
+ response_questions = self._SITE.fetch(
+ 'users/{ids}/questions', ids=account_ids, body=True
+ )
+
+ print(response_questions)
+
+ response_comments = self._SITE.fetch(
+ 'users/{ids}/comments', ids=account_ids
+ )
+
+ print(response_comments)
+
+
+if __name__ == '__main__':
+ a = StackExchangeAPI(1, 100)
+ ids = a.get_user_ids()
+ print(len(ids))
+ a.get_user_activity(ids)
diff --git a/embeddings/__pycache__/dataset_in_memory.cpython-39.pyc b/embeddings/__pycache__/dataset_in_memory.cpython-39.pyc
index 7b5680a08ba3da9769d0355f247721d87c640624..9b83a4765e9795f43b60b3366d7e703ea97591b5 100644
Binary files a/embeddings/__pycache__/dataset_in_memory.cpython-39.pyc and b/embeddings/__pycache__/dataset_in_memory.cpython-39.pyc differ
diff --git a/embeddings/__pycache__/helper_functions.cpython-39.pyc b/embeddings/__pycache__/helper_functions.cpython-39.pyc
new file mode 100644
index 0000000000000000000000000000000000000000..e9aedf9cfa6437b126da423911d484bebcfbfec9
Binary files /dev/null and b/embeddings/__pycache__/helper_functions.cpython-39.pyc differ
diff --git a/embeddings/__pycache__/hetero_GAT_constants.cpython-39.pyc b/embeddings/__pycache__/hetero_GAT_constants.cpython-39.pyc
new file mode 100644
index 0000000000000000000000000000000000000000..0e65d91c024cfebce9a45eb473a69058684cf459
Binary files /dev/null and b/embeddings/__pycache__/hetero_GAT_constants.cpython-39.pyc differ
diff --git a/embeddings/dataset_in_memory.py b/embeddings/dataset_in_memory.py
index 1ecbf6a7b6ca609b0c1c604fbb5d643d5ea79cee..10016e3b41f9e51b24a95ecca49af320e14aaf2e 100644
--- a/embeddings/dataset_in_memory.py
+++ b/embeddings/dataset_in_memory.py
@@ -16,6 +16,7 @@ class UserGraphDatasetInMemory(InMemoryDataset):
self._question_ids = question_ids
super().__init__(root, transform, pre_transform, pre_filter)
self.data, self.slices = torch.load(self.processed_paths[0])
+ # Remove gradient requirements
self.data = self.data.apply(lambda x: x.detach())
@property
diff --git a/embeddings/helper_functions.py b/embeddings/helper_functions.py
new file mode 100644
index 0000000000000000000000000000000000000000..a9b539f3b8dd344ec3865739448acf8820251f0a
--- /dev/null
+++ b/embeddings/helper_functions.py
@@ -0,0 +1,93 @@
+import torch
+import wandb
+import os
+
+from custom_logger import setup_custom_logger
+import logging
+
+log = setup_custom_logger("heterogenous_GAT_model", logging.INFO)
+
+
+def create_graph_vis(graph):
+ g = to_networkx(graph.to_homogeneous())
+ pos = nx.spring_layout(g)
+ vis = GraphVisualization(
+ g, pos, node_text_position='top left', node_size=20,
+ )
+ fig = vis.create_figure()
+ return fig
+
+
+"""
+Weights & Biases dashboard
+"""
+
+def init_wandb(project_name: str, dataset, data_details):
+ wandb.init(project=project_name, name="setup")
+
+ # Log all the details about the data to W&B.
+ wandb.log(data_details)
+
+ # Log exploratory visualizations for each data point to W&B
+ table = wandb.Table(columns=["Graph", "Number of Nodes", "Number of Edges", "Label"])
+ for graph in dataset:
+ fig = create_graph_vis(graph)
+ n_nodes = graph.num_nodes
+ n_edges = graph.num_edges
+ label = graph.label.item()
+
+ # graph_vis = plotly.io.to_html(fig, full_html=False)
+
+ table.add_data(wandb.Plotly(fig), n_nodes, n_edges, label)
+ wandb.log({"data": table})
+
+ # Log the dataset to W&B as an artifact.
+ dataset_artifact = wandb.Artifact(name="static-graphs", type="dataset", metadata=data_details)
+ dataset_artifact.add_dir("../data/")
+ wandb.log_artifact(dataset_artifact)
+
+ # End the W&B run
+ wandb.finish()
+
+def start_wandb_for_training(wandb_project_name: str, wandb_run_name: str):
+ wandb.init(project=wandb_project_name, name=wandb_run_name)
+ # wandb.use_artifact("static-graphs:latest")
+
+
+def add_cm_to_wandb(test_info):
+ wandb.log({"test/cm": wandb.plot.confusion_matrix(probs=None, y_true=test_info["trues"], preds=test_info["preds"], class_names=["neutral", "upvoted"])})
+
+def log_results_to_wandb(results_map, results_name: str):
+ wandb.log({
+ f"{results_name}/loss": results_map["loss"],
+ f"{results_name}/accuracy": results_map["accuracy"],
+ f"{results_name}/f1": results_map["f1-score"],
+ f"{results_name}/table": results_map["table"]
+ })
+
+"""
+PyTorch helpers
+"""
+
+
+def save_model(model, model_name: str):
+ torch.save(model.state_dict(), os.path.join("..", "models", model_name))
+
+
+def split_test_train_pytorch(dataset, train_split):
+ train_size = int(0.7 * len(dataset))
+ test_size = len(dataset) - (train_size)
+
+ train_dataset, test_dataset = torch.utils.data.random_split(dataset, [train_size, test_size])
+ return train_dataset, test_dataset
+
+def calculate_class_weights(dataset):
+ # Class weights
+ log.info(f"Calculating class weights")
+ train_labels = [x.label for x in dataset]
+ counts = [train_labels.count(x) for x in [0, 1]]
+ log.info(counts)
+ class_weights = [1 - (x / sum(counts)) for x in counts]
+ log.info(class_weights)
+ sampler = torch.utils.data.WeightedRandomSampler([class_weights[x] for x in train_labels], len(train_labels))
+ return sampler
diff --git a/embeddings/hetero_GAT.py b/embeddings/hetero_GAT.py
index e217f08a38a8d62fc6f33cc35ce5aaf7e6101bc1..4b5c2919427d1e867334d3d0406084e681f33c62 100644
--- a/embeddings/hetero_GAT.py
+++ b/embeddings/hetero_GAT.py
@@ -10,16 +10,17 @@ import torch
from sklearn.metrics import f1_score, accuracy_score
from torch_geometric.loader import DataLoader
from torch_geometric.nn import HeteroConv, GATConv, Linear, global_mean_pool
-from embeddings.helper_functions import calculate_class_weights, split_test_train_pytorch
+from helper_functions import calculate_class_weights, split_test_train_pytorch
import wandb
from torch_geometric.utils import to_networkx
+from sklearn.model_selection import KFold
from custom_logger import setup_custom_logger
from dataset import UserGraphDataset
from dataset_in_memory import UserGraphDatasetInMemory
from Visualize import GraphVisualization
import helper_functions
-from hetero_GAT_constants import TRAIN_BATCH_SIZE, TEST_BATCH_SIZE, IN_MEMORY_DATASET, INCLUDE_ANSWER, USE_WANDB, WANDB_PROJECT_NAME, NUM_WORKERS, EPOCHS, NUM_LAYERS, HIDDEN_CHANNELS, FINAL_MODEL_OUT_PATH, SAVE_CHECKPOINTS
+from hetero_GAT_constants import TRAIN_BATCH_SIZE, TEST_BATCH_SIZE, IN_MEMORY_DATASET, INCLUDE_ANSWER, USE_WANDB, WANDB_PROJECT_NAME, NUM_WORKERS, EPOCHS, NUM_LAYERS, HIDDEN_CHANNELS, FINAL_MODEL_OUT_PATH, SAVE_CHECKPOINTS, WANDB_RUN_NAME
log = setup_custom_logger("heterogenous_GAT_model", logging.INFO)
torch.multiprocessing.set_sharing_strategy('file_system')
@@ -28,7 +29,6 @@ rlimit = resource.getrlimit(resource.RLIMIT_NOFILE)
resource.setrlimit(resource.RLIMIT_NOFILE, (2048, rlimit[1]))
-
class HeteroGNN(torch.nn.Module):
"""
Heterogenous Graph Attentional Network (GAT)
@@ -134,15 +134,22 @@ def test(loader):
loss = criterion(out, torch.squeeze(data.label, -1)) # Compute the loss.
cumulative_loss += loss.item()
- pred = out.argmax(dim=1) # Use the class with highest probability.
+
+ # Use the class with highest probability.
+ pred = out.argmax(dim=1)
+
+ # Cache the predictions for calculating metrics
predictions += list([x.item() for x in pred])
true_labels += list([x.item() for x in data.label])
+
+ # Log table of predictions to WandB
if USE_WANDB:
#graph_html = wandb.Html(plotly.io.to_html(create_graph_vis(data)))
for pred, label in zip(pred, torch.squeeze(data.label, -1)):
table.add_data(label, pred)
-
+
+ # Collate results into a single dictionary
test_results = {
"accuracy": accuracy_score(true_labels, predictions),
"f1-score": f1_score(true_labels, predictions),
@@ -163,6 +170,10 @@ if __name__ == '__main__':
if IN_MEMORY_DATASET:
train_dataset = UserGraphDatasetInMemory(root="../data", file_name_out='train-4175-qs.pt')
test_dataset = UserGraphDatasetInMemory(root="../data", file_name_out='test-1790-qs.pt')
+
+ ## TEST
+ split1, split2 = helper_functions.split_test_train_pytorch(train_dataset, 0.7)
+
else:
dataset = UserGraphDataset(root="../data", skip_processing=True)
train_dataset, test_dataset = split_test_train_pytorch(dataset)
@@ -179,8 +190,9 @@ if __name__ == '__main__':
log.info(f"Data Details:\n{data_details}")
if USE_WANDB:
- wandb_run_name = f"run@{time.strftime('%Y%m%d-%H%M%S')}"
- helper_functions.start_wandb_for_training(WANDB_PROJECT_NAME, wandb_run_name)
+ if WANDB_RUN_NAME is None:
+ run_name = f"run@{time.strftime('%Y%m%d-%H%M%S')}"
+ helper_functions.start_wandb_for_training(WANDB_PROJECT_NAME, run_name)
# Class weights
@@ -218,24 +230,16 @@ if __name__ == '__main__':
if SAVE_CHECKPOINTS:
checkpoint_file_name = f"../models/model-{epoch}.pt"
torch.save(model.state_dict(), checkpoint_file_name)
-
+
+ # log evaluation results to wandb
if USE_WANDB:
- wandb.log({
- "train/loss": train_info["loss"],
- "train/accuracy": train_info["accuracy"],
- "train/f1": train_info["f1-score"],
- "train/table": train_info["table"],
- "test/loss": test_info["loss"],
- "test/accuracy": test_info["accuracy"],
- "test/f1": test_info["f1-score"],
- "test/table": test_info["table"]
- })
+ helper_functions.log_results_to_wandb(train_info, "train")
+ helper_functions.log_results_to_wandb(test_info, "test")
log.info(f'Test F1: {train_info["f1-score"]:.4f}')
helper_functions.save_model(model, FINAL_MODEL_OUT_PATH)
# Plot confusion matrix
if USE_WANDB:
- wandb.log({"test/cm": wandb.plot.confusion_matrix(probs=None, y_true=test_info["trues"], preds=test_info["preds"], class_names=["neutral", "upvoted"])})
+ helper_functions.add_cm_to_wandb(test_info)
wandb.finish()
-
diff --git a/embeddings/hetero_GAT_constants.py b/embeddings/hetero_GAT_constants.py
index e69de29bb2d1d6434b8b29ae775ad8c2e48c5391..df58a591afaa5e10f13e60e33d96131e60e7b749 100644
--- a/embeddings/hetero_GAT_constants.py
+++ b/embeddings/hetero_GAT_constants.py
@@ -0,0 +1,23 @@
+# Batch sizes
+TRAIN_BATCH_SIZE = 512
+TEST_BATCH_SIZE = 512
+
+# Data config
+IN_MEMORY_DATASET = True
+INCLUDE_ANSWER = True
+
+# W&B dashboard logging
+USE_WANDB = True
+WANDB_PROJECT_NAME = "heterogeneous-GAT-model"
+WANDB_RUN_NAME = None # None for timestamp
+
+NUM_WORKERS = 14
+
+# Training parameters
+EPOCHS = 2
+
+# Model architecture
+NUM_LAYERS = 3
+HIDDEN_CHANNELS = 64
+FINAL_MODEL_OUT_PATH = "model.pt"
+SAVE_CHECKPOINTS = False
\ No newline at end of file
diff --git a/figures/user-graph.svg b/figures/user-graph.svg
index cbae063b4713260bd3d8e0f8a5efb885fe0c6509..7a2c3f3938784198b2f140527a9587ffb1842818 100644
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diff --git a/requirements.txt b/requirements.txt
index c3be34b9f39070854305afb241baa29af243348c..29963bbd754bdf7f64b498872f6897307cba21e4 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,149 +1,30 @@
-absl-py==1.3.0
-anyio==3.6.2
-argon2-cffi==21.3.0
-argon2-cffi-bindings==21.2.0
-asttokens==2.1.0
-attrs==22.1.0
-backcall==0.2.0
-beautifulsoup4==4.11.1
-bleach==5.0.1
-blis==0.7.9
-bs4==0.0.1
-cachetools==5.2.0
-catalogue==2.0.8
-certifi==2022.9.24
-cffi==1.15.1
-charset-normalizer==2.1.1
-click==8.1.3
-colorama==0.4.6
-confection==0.0.3
-contourpy==1.0.6
-cycler==0.11.0
-cymem==2.0.7
-debugpy==1.6.3
-decorator==5.1.1
-defusedxml==0.7.1
-dgl==0.9.1
-en-core-web-sm @ https://github.com/explosion/spacy-models/releases/download/en_core_web_sm-3.4.1/en_core_web_sm-3.4.1-py3-none-any.whl
-entrypoints==0.4
-executing==1.2.0
-fastjsonschema==2.16.2
-filelock==3.8.0
-fonttools==4.38.0
-google-auth==2.14.0
-google-auth-oauthlib==0.4.6
-graph4nlp==0.5.5
-grpcio==1.50.0
-huggingface-hub==0.10.1
+certifi==2022.12.7
+charset-normalizer==2.0.12
+dataclasses==0.8
+decorator==4.4.2
+googledrivedownloader==0.4
idna==3.4
-importlib-metadata==5.0.0
-importlib-resources==5.10.0
-ipykernel==6.16.2
-ipython==8.6.0
-ipython-genutils==0.2.0
-ipywidgets==8.0.2
-jedi==0.18.1
-Jinja2==3.1.2
-joblib==1.2.0
-jsonschema==4.16.0
-jupyter==1.0.0
-jupyter-console==6.4.4
-jupyter-server==1.21.0
-jupyter_client==7.4.4
-jupyter_core==4.11.2
-jupyterlab-pygments==0.2.2
-jupyterlab-widgets==3.0.3
-kiwisolver==1.4.4
-langcodes==3.3.0
-littleutils==0.2.2
-lxml==4.9.1
-Markdown==3.4.1
-MarkupSafe==2.1.1
-matplotlib==3.6.2
-matplotlib-inline==0.1.6
-mistune==2.0.4
-murmurhash==1.0.9
-nbclassic==0.4.7
-nbclient==0.7.0
-nbconvert==7.2.3
-nbformat==5.7.0
-nest-asyncio==1.5.6
-networkx==2.8.8
-nltk==3.7
-notebook==6.5.2
-notebook_shim==0.2.0
-numpy==1.23.5
-oauthlib==3.2.2
-ogb==1.3.5
-outdated==0.2.2
-packaging==21.3
-pandas==1.5.1
-pandocfilters==1.5.0
-parso==0.8.3
-pathy==0.6.2
-pickleshare==0.7.5
-Pillow==9.3.0
-pkgutil_resolve_name==1.3.10
-preshed==3.0.8
-prometheus-client==0.15.0
-prompt-toolkit==3.0.31
-protobuf==3.19.6
-psutil==5.9.3
-pure-eval==0.2.2
-pyasn1==0.4.8
-pyasn1-modules==0.2.8
-pycparser==2.21
-pydantic==1.10.2
-Pygments==2.13.0
+importlib-resources==5.4.0
+isodate==0.6.1
+Jinja2==3.0.3
+joblib==1.1.1
+MarkupSafe==2.0.1
+networkx==2.5.1
+numpy==1.19.5
+pandas==1.1.5
+Pillow==8.4.0
pyparsing==3.0.9
-pyrsistent==0.18.1
python-dateutil==2.8.2
-pythonds==1.2.1
-pytz==2022.5
-pywin32==304
-pywinpty==2.0.9
+pytz==2022.7.1
PyYAML==6.0
-pyzmq==24.0.1
-qtconsole==5.3.2
-QtPy==2.2.1
-regex==2022.10.31
-requests==2.28.1
-requests-oauthlib==1.3.1
-rsa==4.9
-scikit-learn==1.1.3
-scipy==1.9.3
-Send2Trash==1.8.0
+rdflib==5.0.0
+requests==2.27.1
+scikit-learn==0.24.2
+scipy==1.5.4
six==1.16.0
-smart-open==5.2.1
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-soupsieve==2.3.2.post1
-spacy==3.4.2
-spacy-legacy==3.0.10
-spacy-loggers==1.0.3
-srsly==2.4.5
-stack-data==0.6.0
-stanfordcorenlp==3.9.1.1
-tensorboard==2.10.1
-tensorboard-data-server==0.6.1
-tensorboard-plugin-wit==1.8.1
-terminado==0.17.0
-thinc==8.1.5
threadpoolctl==3.1.0
-tinycss2==1.2.1
-tokenizers==0.13.2
-torch==1.13.0
-torchtext==0.14.0
-tornado==6.2
tqdm==4.64.1
-traitlets==5.5.0
-transformers==4.24.0
-typer==0.4.2
-typing_extensions==4.4.0
-urllib3==1.26.12
-wasabi==0.10.1
-wcwidth==0.2.5
-webencodings==0.5.1
-websocket-client==1.4.1
-Werkzeug==2.2.2
-widgetsnbextension==4.0.3
-zipp==3.10.0
+typing_extensions==4.1.1
+urllib3==1.26.14
+yacs==0.1.8
+zipp==3.6.0