# Kaggle Discussion Extractor
[](https://www.python.org/downloads/)
[](https://opensource.org/licenses/MIT)
[](https://playwright.dev/python/)
A professional-grade Python tool for extracting and analyzing discussions and solution writeups from Kaggle competitions. Features hierarchical reply extraction, automatic writeup extraction from leaderboards, and clean markdown output with rich metadata.
## 🚀 Key Features
### Competition Writeup Extraction
- **Leaderboard Scraping**: Automatically extracts writeup URLs from competition leaderboards
- **Private/Public Leaderboards**: Supports both private and public leaderboard tabs
- **Custom Naming**: Files saved as `{contest_name}_{rank}_{team_name}.md`
- **Rich Metadata**: Includes rank, team members, scores, and extraction timestamps
- **Top-N Selection**: Extract only top performers (e.g., top 10)
### Hierarchical Discussion Extraction
- **Complete Thread Preservation**: Maintains the full discussion structure with parent-child relationships
- **Smart Reply Numbering**: Automatic hierarchical numbering (1, 1.1, 1.2, 2, 2.1, etc.)
- **No Content Duplication**: Intelligently separates parent and nested reply content
- **Deep Nesting Support**: Handles multiple levels of nested replies
### Rich Metadata Extraction
- **Author Information**: Names, usernames, profile URLs
- **Competition Rankings**: Extracts "Nth in this Competition" rankings
- **User Badges**: Competition Host, Expert, Master, Grandmaster badges
- **Engagement Metrics**: Upvotes/downvotes for all posts and replies
- **Timestamps**: Full timestamp extraction for temporal analysis
### Advanced Capabilities
- **Pagination Support**: Automatically handles multi-page discussion lists
- **Batch Processing**: Extract all discussions from a competition at once
- **Rate Limiting**: Built-in delays to respect server resources
- **Error Recovery**: Robust error handling with detailed logging
- **Multiple Output Formats**: Clean Markdown export with proper formatting
## 📦 Installation
### Method 1: Install from PyPI (Recommended)
```bash
pip install kaggle-discussion-extractor
playwright install chromium
```
### Method 2: Install from Source
```bash
# Clone the repository
git clone https://github.com/Letemoin/kaggle-discussion-extractor.git
cd kaggle-discussion-extractor
# Install in development mode
pip install -e .
playwright install chromium
```
## 🎯 Quick Start
### Command Line Usage
```bash
# Extract all discussions from a competition
kaggle-discussion-extractor https://www.kaggle.com/competitions/neurips-2025
# Extract only 10 discussions
kaggle-discussion-extractor https://www.kaggle.com/competitions/neurips-2025 --limit 10
# Enable development mode for detailed logging
kaggle-discussion-extractor https://www.kaggle.com/competitions/neurips-2025 --dev-mode
# Run with visible browser (useful for debugging)
kaggle-discussion-extractor https://www.kaggle.com/competitions/neurips-2025 --no-headless
# Extract top 10 writeups from private leaderboard
kaggle-discussion-extractor https://www.kaggle.com/competitions/cmi-detect-behavior --extract-writeups --limit 10
# Extract from public leaderboard with development mode
kaggle-discussion-extractor https://www.kaggle.com/competitions/cmi-detect-behavior --extract-writeups --leaderboard-tab public --dev-mode
```
### Python API Usage
#### Extract Discussions
```python
import asyncio
from kaggle_discussion_extractor import KaggleDiscussionExtractor
async def extract_discussions():
# Initialize extractor
extractor = KaggleDiscussionExtractor(dev_mode=True)
# Extract discussions
success = await extractor.extract_competition_discussions(
competition_url="https://www.kaggle.com/competitions/neurips-2025",
limit=5 # Optional: limit number of discussions
)
if success:
print("Extraction completed successfully!")
else:
print("Extraction failed!")
# Run the extraction
asyncio.run(extract_discussions())
```
#### Extract Writeups
```python
import asyncio
from kaggle_discussion_extractor import KaggleWriteupExtractor
async def extract_writeups():
# Initialize writeup extractor
extractor = KaggleWriteupExtractor(dev_mode=True)
# Extract top 5 writeups from private leaderboard
success = await extractor.extract_writeups(
competition_url="https://www.kaggle.com/competitions/cmi-detect-behavior",
limit=5,
leaderboard_tab="private"
)
if success:
print("Writeup extraction completed successfully!")
else:
print("Writeup extraction failed!")
# Run the extraction
asyncio.run(extract_writeups())
```
## 📋 CLI Options
| Option | Description | Default |
|--------|-------------|---------|
| `competition_url` | URL of the Kaggle competition (required) | - |
| `--limit, -l` | Number of discussions/writeups to extract | All |
| `--dev-mode, -d` | Enable detailed logging | False |
| `--no-headless` | Run browser in visible mode | False (headless) |
| `--date-format` | Include YYMMDD date in filename | False |
| `--date-position` | Position of date (prefix/suffix) | suffix |
| `--extract-writeups` | Extract writeups from leaderboard | False |
| `--leaderboard-tab` | Leaderboard tab (private/public) | private |
| `--version, -v` | Show version information | - |
## 📁 Output Structure
### Writeup Extraction
The writeup extractor creates a `writeups_extracted` directory with:
```
writeups_extracted/
├── contest-name_01_TeamName.md
├── contest-name_02_AnotherTeam.md
├── contest-name_03_ThirdPlace.md
└── ...
```
### Discussion Extraction
The discussion extractor creates a `kaggle_discussions_extracted` directory with:
```
kaggle_discussions_extracted/
├── 01_Discussion_Title.md
├── 02_Another_Discussion.md
├── 03_Third_Discussion.md
└── ...
```
### Sample Output Format
```markdown
# Discussion Title
**URL**: https://www.kaggle.com/competitions/neurips-2025/discussion/123456
**Total Comments**: 15
**Extracted**: 2025-01-15T10:30:00
---
## Main Post
**Author**: username (@username)
**Rank**: 27th in this Competition
**Badges**: Competition Host
**Upvotes**: 36
Main discussion content goes here...
---
## Replies
### Reply 1
- **Author**: user1 (@user1)
- **Rank**: 154th in this Competition
- **Upvotes**: 11
- **Timestamp**: Tue Jun 17 2025 11:54:57 GMT+0300
Content of reply 1...
#### Reply 1.1
- **Author**: user2 (@user2)
- **Upvotes**: 6
- **Timestamp**: Sun Jun 29 2025 04:20:43 GMT+0300
Nested reply content...
#### Reply 1.2
- **Author**: user3 (@user3)
- **Upvotes**: 2
- **Timestamp**: Wed Jul 16 2025 12:50:34 GMT+0300
Another nested reply...
---
### Reply 2
- **Author**: user4 (@user4)
- **Upvotes**: -3
Content of reply 2...
---
```
## ⚙️ Configuration
### Development Mode
Enable development mode to see detailed logs and debugging information:
```python
extractor = KaggleDiscussionExtractor(dev_mode=True)
```
**What dev_mode does:**
- Enables DEBUG level logging
- Shows detailed progress information
- Displays browser automation steps
- Provides error stack traces
- Logs DOM element detection details
### Browser Mode
Run with visible browser for debugging:
```python
extractor = KaggleDiscussionExtractor(headless=False)
```
## 🧪 Examples
### Basic Example
```python
from kaggle_discussion_extractor import KaggleDiscussionExtractor
import asyncio
async def main():
extractor = KaggleDiscussionExtractor()
await extractor.extract_competition_discussions(
"https://www.kaggle.com/competitions/neurips-2025"
)
asyncio.run(main())
```
### Advanced Example with Logging
```python
import asyncio
import logging
from kaggle_discussion_extractor import KaggleDiscussionExtractor
# Setup custom logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)
async def extract_with_monitoring():
extractor = KaggleDiscussionExtractor(
dev_mode=True, # Enable detailed logging
headless=True # Run in background
)
logger.info("Starting extraction...")
success = await extractor.extract_competition_discussions(
competition_url="https://www.kaggle.com/competitions/neurips-2025",
limit=20 # Extract first 20 discussions
)
if success:
logger.info("✅ Extraction completed successfully!")
logger.info("Check 'kaggle_discussions_extracted' directory for results")
else:
logger.error("❌ Extraction failed!")
if __name__ == "__main__":
asyncio.run(extract_with_monitoring())
```
## 🔧 Development
### Setup Development Environment
```bash
# Clone repository
git clone https://github.com/Letemoin/kaggle-discussion-extractor.git
cd kaggle-discussion-extractor
# Install development dependencies
pip install -e ".[dev]"
playwright install chromium
# Run tests
pytest tests/
```
### Project Structure
```
kaggle_discussion_extractor/
├── __init__.py # Package initialization
├── core.py # Main extraction logic
└── cli.py # Command-line interface
```
## 🤝 Contributing
Contributions are welcome! Please read our [Contributing Guidelines](CONTRIBUTING.md) for details on how to submit pull requests, report issues, and contribute to the project.
## 🙏 Acknowledgments
- Built with [Playwright](https://playwright.dev/) for reliable browser automation
- Inspired by the need for better Kaggle competition analysis tools
- Thanks to the open-source community for continuous support
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"description": "# Kaggle Discussion Extractor\r\n\r\n[](https://www.python.org/downloads/)\r\n[](https://opensource.org/licenses/MIT)\r\n[](https://playwright.dev/python/)\r\n\r\nA professional-grade Python tool for extracting and analyzing discussions and solution writeups from Kaggle competitions. Features hierarchical reply extraction, automatic writeup extraction from leaderboards, and clean markdown output with rich metadata.\r\n\r\n## \ud83d\ude80 Key Features\r\n\r\n### Competition Writeup Extraction\r\n- **Leaderboard Scraping**: Automatically extracts writeup URLs from competition leaderboards\r\n- **Private/Public Leaderboards**: Supports both private and public leaderboard tabs\r\n- **Custom Naming**: Files saved as `{contest_name}_{rank}_{team_name}.md`\r\n- **Rich Metadata**: Includes rank, team members, scores, and extraction timestamps\r\n- **Top-N Selection**: Extract only top performers (e.g., top 10)\r\n\r\n### Hierarchical Discussion Extraction\r\n- **Complete Thread Preservation**: Maintains the full discussion structure with parent-child relationships\r\n- **Smart Reply Numbering**: Automatic hierarchical numbering (1, 1.1, 1.2, 2, 2.1, etc.)\r\n- **No Content Duplication**: Intelligently separates parent and nested reply content\r\n- **Deep Nesting Support**: Handles multiple levels of nested replies\r\n\r\n### Rich Metadata Extraction\r\n- **Author Information**: Names, usernames, profile URLs\r\n- **Competition Rankings**: Extracts \"Nth in this Competition\" rankings\r\n- **User Badges**: Competition Host, Expert, Master, Grandmaster badges\r\n- **Engagement Metrics**: Upvotes/downvotes for all posts and replies\r\n- **Timestamps**: Full timestamp extraction for temporal analysis\r\n\r\n### Advanced Capabilities\r\n- **Pagination Support**: Automatically handles multi-page discussion lists\r\n- **Batch Processing**: Extract all discussions from a competition at once\r\n- **Rate Limiting**: Built-in delays to respect server resources\r\n- **Error Recovery**: Robust error handling with detailed logging\r\n- **Multiple Output Formats**: Clean Markdown export with proper formatting\r\n\r\n## \ud83d\udce6 Installation\r\n\r\n### Method 1: Install from PyPI (Recommended)\r\n\r\n```bash\r\npip install kaggle-discussion-extractor\r\nplaywright install chromium\r\n```\r\n\r\n### Method 2: Install from Source\r\n\r\n```bash\r\n# Clone the repository\r\ngit clone https://github.com/Letemoin/kaggle-discussion-extractor.git\r\ncd kaggle-discussion-extractor\r\n\r\n# Install in development mode\r\npip install -e .\r\nplaywright install chromium\r\n```\r\n\r\n## \ud83c\udfaf Quick Start\r\n\r\n### Command Line Usage\r\n\r\n```bash\r\n# Extract all discussions from a competition\r\nkaggle-discussion-extractor https://www.kaggle.com/competitions/neurips-2025\r\n\r\n# Extract only 10 discussions\r\nkaggle-discussion-extractor https://www.kaggle.com/competitions/neurips-2025 --limit 10\r\n\r\n# Enable development mode for detailed logging\r\nkaggle-discussion-extractor https://www.kaggle.com/competitions/neurips-2025 --dev-mode\r\n\r\n# Run with visible browser (useful for debugging)\r\nkaggle-discussion-extractor https://www.kaggle.com/competitions/neurips-2025 --no-headless\r\n\r\n# Extract top 10 writeups from private leaderboard\r\nkaggle-discussion-extractor https://www.kaggle.com/competitions/cmi-detect-behavior --extract-writeups --limit 10\r\n\r\n# Extract from public leaderboard with development mode\r\nkaggle-discussion-extractor https://www.kaggle.com/competitions/cmi-detect-behavior --extract-writeups --leaderboard-tab public --dev-mode\r\n```\r\n\r\n### Python API Usage\r\n\r\n#### Extract Discussions\r\n```python\r\nimport asyncio\r\nfrom kaggle_discussion_extractor import KaggleDiscussionExtractor\r\n\r\nasync def extract_discussions():\r\n # Initialize extractor\r\n extractor = KaggleDiscussionExtractor(dev_mode=True)\r\n \r\n # Extract discussions\r\n success = await extractor.extract_competition_discussions(\r\n competition_url=\"https://www.kaggle.com/competitions/neurips-2025\",\r\n limit=5 # Optional: limit number of discussions\r\n )\r\n \r\n if success:\r\n print(\"Extraction completed successfully!\")\r\n else:\r\n print(\"Extraction failed!\")\r\n\r\n# Run the extraction\r\nasyncio.run(extract_discussions())\r\n```\r\n\r\n#### Extract Writeups\r\n```python\r\nimport asyncio\r\nfrom kaggle_discussion_extractor import KaggleWriteupExtractor\r\n\r\nasync def extract_writeups():\r\n # Initialize writeup extractor\r\n extractor = KaggleWriteupExtractor(dev_mode=True)\r\n \r\n # Extract top 5 writeups from private leaderboard\r\n success = await extractor.extract_writeups(\r\n competition_url=\"https://www.kaggle.com/competitions/cmi-detect-behavior\",\r\n limit=5,\r\n leaderboard_tab=\"private\"\r\n )\r\n \r\n if success:\r\n print(\"Writeup extraction completed successfully!\")\r\n else:\r\n print(\"Writeup extraction failed!\")\r\n\r\n# Run the extraction\r\nasyncio.run(extract_writeups())\r\n```\r\n\r\n## \ud83d\udccb CLI Options\r\n\r\n| Option | Description | Default |\r\n|--------|-------------|---------|\r\n| `competition_url` | URL of the Kaggle competition (required) | - |\r\n| `--limit, -l` | Number of discussions/writeups to extract | All |\r\n| `--dev-mode, -d` | Enable detailed logging | False |\r\n| `--no-headless` | Run browser in visible mode | False (headless) |\r\n| `--date-format` | Include YYMMDD date in filename | False |\r\n| `--date-position` | Position of date (prefix/suffix) | suffix |\r\n| `--extract-writeups` | Extract writeups from leaderboard | False |\r\n| `--leaderboard-tab` | Leaderboard tab (private/public) | private |\r\n| `--version, -v` | Show version information | - |\r\n\r\n## \ud83d\udcc1 Output Structure\r\n\r\n### Writeup Extraction\r\nThe writeup extractor creates a `writeups_extracted` directory with:\r\n\r\n```\r\nwriteups_extracted/\r\n\u251c\u2500\u2500 contest-name_01_TeamName.md\r\n\u251c\u2500\u2500 contest-name_02_AnotherTeam.md \r\n\u251c\u2500\u2500 contest-name_03_ThirdPlace.md\r\n\u2514\u2500\u2500 ...\r\n```\r\n\r\n### Discussion Extraction\r\nThe discussion extractor creates a `kaggle_discussions_extracted` directory with:\r\n\r\n```\r\nkaggle_discussions_extracted/\r\n\u251c\u2500\u2500 01_Discussion_Title.md\r\n\u251c\u2500\u2500 02_Another_Discussion.md\r\n\u251c\u2500\u2500 03_Third_Discussion.md\r\n\u2514\u2500\u2500 ...\r\n```\r\n\r\n### Sample Output Format\r\n\r\n```markdown\r\n# Discussion Title\r\n\r\n**URL**: https://www.kaggle.com/competitions/neurips-2025/discussion/123456\r\n**Total Comments**: 15\r\n**Extracted**: 2025-01-15T10:30:00\r\n\r\n---\r\n\r\n## Main Post\r\n\r\n**Author**: username (@username)\r\n**Rank**: 27th in this Competition\r\n**Badges**: Competition Host\r\n**Upvotes**: 36\r\n\r\nMain discussion content goes here...\r\n\r\n---\r\n\r\n## Replies\r\n\r\n### Reply 1\r\n\r\n- **Author**: user1 (@user1)\r\n- **Rank**: 154th in this Competition\r\n- **Upvotes**: 11\r\n- **Timestamp**: Tue Jun 17 2025 11:54:57 GMT+0300\r\n\r\nContent of reply 1...\r\n\r\n #### Reply 1.1\r\n\r\n - **Author**: user2 (@user2)\r\n - **Upvotes**: 6\r\n - **Timestamp**: Sun Jun 29 2025 04:20:43 GMT+0300\r\n\r\n Nested reply content...\r\n\r\n #### Reply 1.2\r\n\r\n - **Author**: user3 (@user3)\r\n - **Upvotes**: 2\r\n - **Timestamp**: Wed Jul 16 2025 12:50:34 GMT+0300\r\n\r\n Another nested reply...\r\n\r\n---\r\n\r\n### Reply 2\r\n\r\n- **Author**: user4 (@user4)\r\n- **Upvotes**: -3\r\n\r\nContent of reply 2...\r\n\r\n---\r\n```\r\n\r\n## \u2699\ufe0f Configuration\r\n\r\n### Development Mode\r\n\r\nEnable development mode to see detailed logs and debugging information:\r\n\r\n```python\r\nextractor = KaggleDiscussionExtractor(dev_mode=True)\r\n```\r\n\r\n**What dev_mode does:**\r\n- Enables DEBUG level logging\r\n- Shows detailed progress information\r\n- Displays browser automation steps\r\n- Provides error stack traces\r\n- Logs DOM element detection details\r\n\r\n### Browser Mode\r\n\r\nRun with visible browser for debugging:\r\n\r\n```python\r\nextractor = KaggleDiscussionExtractor(headless=False)\r\n```\r\n\r\n## \ud83e\uddea Examples\r\n\r\n### Basic Example\r\n\r\n```python\r\nfrom kaggle_discussion_extractor import KaggleDiscussionExtractor\r\nimport asyncio\r\n\r\nasync def main():\r\n extractor = KaggleDiscussionExtractor()\r\n \r\n await extractor.extract_competition_discussions(\r\n \"https://www.kaggle.com/competitions/neurips-2025\"\r\n )\r\n\r\nasyncio.run(main())\r\n```\r\n\r\n### Advanced Example with Logging\r\n\r\n```python\r\nimport asyncio\r\nimport logging\r\nfrom kaggle_discussion_extractor import KaggleDiscussionExtractor\r\n\r\n# Setup custom logging\r\nlogging.basicConfig(level=logging.INFO)\r\nlogger = logging.getLogger(__name__)\r\n\r\nasync def extract_with_monitoring():\r\n extractor = KaggleDiscussionExtractor(\r\n dev_mode=True, # Enable detailed logging\r\n headless=True # Run in background\r\n )\r\n \r\n logger.info(\"Starting extraction...\")\r\n \r\n success = await extractor.extract_competition_discussions(\r\n competition_url=\"https://www.kaggle.com/competitions/neurips-2025\",\r\n limit=20 # Extract first 20 discussions\r\n )\r\n \r\n if success:\r\n logger.info(\"\u2705 Extraction completed successfully!\")\r\n logger.info(\"Check 'kaggle_discussions_extracted' directory for results\")\r\n else:\r\n logger.error(\"\u274c Extraction failed!\")\r\n\r\nif __name__ == \"__main__\":\r\n asyncio.run(extract_with_monitoring())\r\n```\r\n\r\n## \ud83d\udd27 Development\r\n\r\n### Setup Development Environment\r\n\r\n```bash\r\n# Clone repository\r\ngit clone https://github.com/Letemoin/kaggle-discussion-extractor.git\r\ncd kaggle-discussion-extractor\r\n\r\n# Install development dependencies\r\npip install -e \".[dev]\"\r\nplaywright install chromium\r\n\r\n# Run tests\r\npytest tests/\r\n```\r\n\r\n### Project Structure\r\n\r\n```\r\nkaggle_discussion_extractor/\r\n\u251c\u2500\u2500 __init__.py # Package initialization\r\n\u251c\u2500\u2500 core.py # Main extraction logic\r\n\u2514\u2500\u2500 cli.py # Command-line interface\r\n```\r\n\r\n## \ud83e\udd1d Contributing\r\n\r\nContributions are welcome! Please read our [Contributing Guidelines](CONTRIBUTING.md) for details on how to submit pull requests, report issues, and contribute to the project.\r\n\r\n\r\n## \ud83d\ude4f Acknowledgments\r\n\r\n- Built with [Playwright](https://playwright.dev/) for reliable browser automation\r\n- Inspired by the need for better Kaggle competition analysis tools\r\n- Thanks to the open-source community for continuous support\r\n\r\n",
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}
JSON
