A comprehensive analytics and reporting system for tracking GitHub repository contributions, generating insights, and creating static contributor profile pages.
elizaos/eliza permalinks:
- https://elizaos.github.io/data/daily/contributors.json
- https://elizaos.github.io/data/weekly/contributors.json
- https://elizaos.github.io/data/monthly/contributors.json
older versions are backed up in data/*/history
folders with timestamps
-
Daily, Weekly, and Monthly Reports
- Automated data collection via GitHub Actions
- Detailed activity summaries with metrics and trends
- Smart contributor scoring system
- AI-powered activity summaries
-
Contributor Profiles
- Interactive profile pages for each contributor
- Activity visualization with charts and metrics
- Contribution history and engagement tracking
- Responsive design with dark mode support
-
Activity Tracking
- Pull request analysis with file-level changes
- Issue tracking with label analytics
- Commit history and impact measurement
- Engagement metrics (comments, reviews, etc.)
- Configure GitHub Authentication:
# Set your GitHub access token
export GH_ACCESS_TOKEN="your_token"
# For AI-powered summaries (optional)
export OPENAI_API_KEY="your_key"
- Install Dependencies:
# Install Python dependencies
pip install openai langchain-core langchain-ollama
# Install Node.js dependencies
npm install
- Configure Repository Settings:
# Update repository details in fetch_github.sh
owner="your_org"
repo="your_repo"
# Fetch recent activity
./scripts/fetch_github.sh owner repo --type prs --days 7
./scripts/fetch_github.sh owner repo --type issues --days 7
./scripts/fetch_github.sh owner repo --type commits --days 7
# Process and combine data
python scripts/combine.py -p data/prs.json -i data/issues.json -c data/commits.json -o data/combined.json
# Calculate contributor scores
python scripts/calculate_scores.py data/combined.json data/scored.json
# Generate summaries
python scripts/summarize.py data/scored.json data/contributors.json --model openai
The included GitHub Actions workflow (weekly-summaries.yml
) automatically:
- Runs daily at 5:00 PM EST
- Generates weekly reports on Fridays
- Creates monthly summaries on the 4th of each month
# Build and generate contributor profile pages
npm run build
npm run generate
# View the site
open profiles/index.html
The system generates structured JSON data for contributors:
{
"contributor": "username",
"score": number,
"avatar_url": "string",
"summary": "string",
"activity": {
"code": {
"total_commits": number,
"total_prs": number,
"commits": array,
"pull_requests": array
},
"issues": {
"total_opened": number,
"opened": array
},
"engagement": {
"total_comments": number,
"comments": array
}
}
}
- Modify scoring algorithms in
calculate_scores.py
- Adjust summary generation in
summarize.py
- Customize profile pages in
ContributorProfile.js
- Configure report schedules in
weekly-summaries.yml
.
├── data/ # Generated data and reports
├── scripts/ # Core processing scripts
│ ├── combine.py # Data aggregation
│ ├── calculate_scores.py # Scoring system
│ └── summarize.py # Summary generation
├── profiles/ # Generated static site
└── .github/workflows # Automation workflows
- Python 3.11+
- Node.js 18+
- GitHub Personal Access Token
- OpenAI API Key (optional, for AI summaries)