Add Python script and GitHub Actions workflow for user statistics

[Copilot]

Implements automated GitHub user activity tracking using GraphQL API to fetch pull requests, issues, and discussions for configurable time periods.

Core Implementation

• fetch_user_stats.py: GraphQL-based fetcher with configurable lookback period and user

  • Fetches 100 most recent items per type (PRs, issues, discussions) with client-side date filtering
  • Outputs formatted statistics with emoji indicators and activity summaries
  • --output-file flag for file output; status messages routed to stderr for clean stdout
  • GitHub Actions step summary integration: Automatically detects GITHUB_STEP_SUMMARY environment variable and writes output to both console and step summary file for easy viewing in workflow run pages

• .github/workflows/user-stats.yml: Automated execution via workflow_dispatch, scheduled weekly runs, and push triggers

  • Single API call optimization using --output-file
  • 30-day artifact retention for reports
  • Statistics automatically displayed in GitHub Actions step summary

Usage

# Default: user 'rajbos', 30-day lookback
python fetch_user_stats.py

# Custom parameters
python fetch_user_stats.py --username octocat --days 90 --output-file report.txt

Limitations

• 100-item limit per query type due to GitHub GraphQL API constraints
• Client-side date filtering; items beyond 100 most recent may be missed for active users
• Consider shorter lookback periods for comprehensive coverage

Dependencies

• Python 3.7+ (uses datetime.fromisoformat)
• requests>=2.31.0

Original prompt

Got it! I’ll create a new repository called GitHub User Statistics and add the Python script and GitHub Actions workflow into it as requested. Here's the planned implementation:

1. Python Script:

   • Will use GitHub's REST API or GraphQL API to fetch user activity data, including pull requests, issues, and discussions for your GitHub user (rajbos).
   • Script will support configuring the lookback period to specify the number of days to analyze.

2. GitHub Actions Workflow:

   • Automates the execution of the Python script.
   • Validates its functionality and outputs the results directly as part of the GitHub Actions logs or uploads them as an artifact.

3. Repository Setup:

   • A new repository named GitHub User Statistics will be created.
   • The Python script and workflow YAML file will be added to this repo.

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[rajbos]

@copilot update the print commands with a new method. In the new method, detect the GitHub step summary environment variable and if so, use both print as well as a write line to the filename in the variable.

[Copilot]

@copilot update the print commands with a new method. In the new method, detect the GitHub step summary environment variable and if so, use both print as well as a write line to the filename in the va...

Added _print_and_log() method that detects GITHUB_STEP_SUMMARY environment variable and writes to both stdout and the step summary file. All print statements in print_statistics() now use this method.

Commit: f2a4419