code-review-metrics.yml

---
name: Code Review Metrics

on:
  schedule:
    - cron: '0 0 * * 1'  # Weekly on Mondays at midnight UTC
  workflow_dispatch:
    inputs:
      days:
        description: 'Analysis period in days'
        required: false
        default: '30'
        type: string

permissions:
  contents: read
  pull-requests: read
  issues: read

jobs:
  review-metrics:
    runs-on: ubuntu-latest
    name: Generate Code Review Metrics

    steps:
      - name: Checkout
        uses: actions/checkout@v6

      - name: Calculate Date Range
        id: date-range
        run: |
          days="${{ github.event.inputs.days || '30' }}"
          start_date=$(date -d "$days days ago" +%Y-%m-%d)
          echo "start_date=$start_date" >> $GITHUB_OUTPUT

      - name: Collect Code Review Metrics
        run: |
          # Authenticate with GitHub CLI
          echo "${{ secrets.GITHUB_TOKEN }}" | gh auth login --with-token

          # Get PR data for the specified period
          start_date="${{ steps.date-range.outputs.start_date }}"
          days="${{ github.event.inputs.days || '30' }}"
          
          echo "Collecting review data for PRs created since: $start_date"
          
          # Create output files
          mkdir -p review-data
          
          # Get PRs and their reviews (filtering will be done in Python for better control)
          gh pr list \
            --repo "${{ github.repository }}" \
            --state all \
            --limit 1000 \
            --json number,title,author,createdAt,mergedAt,reviews,reviewRequests \
            --jq ".[] | select(.createdAt >= \"$start_date\")" \
            > review-data/prs.json

          # Process review data to generate metrics focused on who is reviewing and review counts
          python3 << 'EOF'
          import json
          import sys
          from collections import defaultdict
          
          # Load PR data from JSONL file (one JSON object per line)
          with open('review-data/prs.json', 'r') as f:
            prs = []
            for line_num, line in enumerate(f, 1):
              if line.strip():
                try:
                  prs.append(json.loads(line))
                except json.JSONDecodeError as e:
                  print(f"Warning: Skipping malformed JSON on line {line_num}: {e}", file=sys.stderr)
          
          print(f"Processing {len(prs)} PRs...")
          
          # Initialize metrics - track both reviewers and contributors
          reviewer_stats = defaultdict(lambda: {
            'reviews_given': 0,
            'prs_reviewed': set()
          })
          
          contributor_stats = defaultdict(lambda: {
            'prs_authored': 0
          })
          
          total_reviews = 0
          
          # Process each PR to count reviews per reviewer and track contributors
          for pr in prs:
            pr_number = pr['number']
            author = pr['author']['login']
            
            # Track PR authors (contributors)
            contributor_stats[author]['prs_authored'] += 1
            
            # Process reviews
            for review in pr.get('reviews', []):
              reviewer = review['author']['login']
              
              total_reviews += 1
              reviewer_stats[reviewer]['reviews_given'] += 1
              reviewer_stats[reviewer]['prs_reviewed'].add(pr_number)
          
          # Convert sets to counts for JSON serialization
          for reviewer in reviewer_stats:
            reviewer_stats[reviewer]['prs_reviewed'] = len(reviewer_stats[reviewer]['prs_reviewed'])
          
          # Find contributors who haven't done reviews
          all_contributors = set(contributor_stats.keys())
          all_reviewers = set(reviewer_stats.keys())
          contributors_not_reviewing = all_contributors - all_reviewers
          
          # Save comprehensive metrics
          metrics = {
            'summary': {
              'total_prs_analyzed': len(prs),
              'total_reviews': total_reviews,
              'total_reviewers': len(reviewer_stats),
              'total_contributors': len(contributor_stats),
              'contributors_not_reviewing': len(contributors_not_reviewing)
            },
            'reviewer_stats': dict(reviewer_stats),
            'contributor_stats': dict(contributor_stats),
            'contributors_not_reviewing': list(contributors_not_reviewing)
          }
          
          with open('review-data/metrics.json', 'w') as f:
            json.dump(metrics, f, indent=2)
          
          print("Review metrics generated successfully")
          print(f"Total reviewers: {len(reviewer_stats)}")
          print(f"Total reviews: {total_reviews}")
          print(f"Total contributors: {len(contributor_stats)}")
          print(f"Contributors not reviewing: {len(contributors_not_reviewing)}")
          EOF

      - name: Generate Report
        run: |
          mkdir -p .github/reports
          report_date=$(date +%Y-%m-%d)
          
          # Create Python script for simplified report generation
          cat > generate_report.py << 'PYTHON_SCRIPT'
          import json
          import os
          import sys
          from datetime import datetime

          try:
            # Load metrics
            with open('review-data/metrics.json', 'r') as f:
              metrics = json.load(f)

            summary = metrics['summary']
            reviewer_stats = metrics['reviewer_stats']
            contributor_stats = metrics['contributor_stats']
            contributors_not_reviewing = metrics['contributors_not_reviewing']

            # Sort reviewers by review count
            sorted_reviewers = sorted(reviewer_stats.items(), key=lambda x: x[1]['reviews_given'], reverse=True)
            
            # Sort contributors by PR count
            sorted_contributors = sorted(contributor_stats.items(), key=lambda x: x[1]['prs_authored'], reverse=True)

            repo_name = os.environ.get('GITHUB_REPOSITORY', 'Unknown')
            analysis_days = os.environ.get('ANALYSIS_DAYS', '30')
            
            # Generate comprehensive markdown report
            report_lines = [
              "# Code Review Metrics Report",
              "",
              f"**Repository:** {repo_name}",
              f"**Generated:** {datetime.now().strftime('%Y-%m-%d %H:%M:%S UTC')}",
              f"**Period:** Last {analysis_days} days",
              "",
              "## Summary",
              "",
              f"- **Total PRs Analyzed:** {summary['total_prs_analyzed']}",
              f"- **Total Reviews Given:** {summary['total_reviews']}",
              f"- **Active Reviewers:** {summary['total_reviewers']}",
              f"- **Total Contributors:** {summary['total_contributors']}",
              f"- **Contributors Not Reviewing:** {summary['contributors_not_reviewing']}",
              "",
              "## Who Is Reviewing Code",
              "",
              "| Reviewer | Reviews Given | PRs Reviewed |",
              "|----------|---------------|--------------|"
            ]

            # Add all reviewers to table (focused on who and how many)
            for reviewer, stats in sorted_reviewers:
              report_lines.append(f"| {reviewer} | {stats['reviews_given']} | {stats['prs_reviewed']} |")

            # Add section for contributors who haven't done reviews
            report_lines.extend([
              "",
              "## Contributors Who Have Not Done Reviews",
              ""
            ])
            
            if contributors_not_reviewing:
              report_lines.extend([
                "| Contributor | PRs Authored |",
                "|-------------|--------------|"
              ])
              
              for contributor in contributors_not_reviewing:
                prs_authored = contributor_stats[contributor]['prs_authored']
                report_lines.append(f"| {contributor} | {prs_authored} |")
            else:
              report_lines.append("*All contributors are also participating in code reviews* ✅")

            # Add insights focused on reviewer activity
            most_active = sorted_reviewers[0] if sorted_reviewers else ('N/A', {'reviews_given': 0})
            avg_reviews = summary['total_reviews'] / summary['total_reviewers'] if summary['total_reviewers'] > 0 else 0
            review_participation = (summary['total_reviewers'] / summary['total_contributors'] * 100) if summary['total_contributors'] > 0 else 0

            report_lines.extend([
              "",
              "## Key Insights",
              "",
              f"- **Most Active Reviewer:** {most_active[0]} ({most_active[1]['reviews_given']} reviews)",
              f"- **Average Reviews per Reviewer:** {avg_reviews:.1f} reviews",
              f"- **Review Participation Rate:** {review_participation:.1f}% of contributors are also reviewing",
              f"- **Review Distribution:** {summary['total_reviews']} total reviews across {summary['total_prs_analyzed']} PRs",
              "",
              "---",
              "*Report shows who is reviewing code, review volume per person, and contributors who could participate more in reviews*"
            ])

            # Save report
            report_content = "\n".join(report_lines)
            output_file = f'.github/reports/code-review-metrics-{os.environ.get("GITHUB_RUN_NUMBER", "test")}.md'
            with open(output_file, 'w') as f:
              f.write(report_content)
            
            print("Report generated successfully")
            print(f"Output file: {output_file}")

          except Exception as e:
            print(f"Error generating report: {e}")
            sys.exit(1)
          PYTHON_SCRIPT

          # Run the report generation
          python3 generate_report.py
        env:
          GITHUB_REPOSITORY: ${{ github.repository }}
          ANALYSIS_DAYS: ${{ github.event.inputs.days || '30' }}
          GITHUB_RUN_NUMBER: ${{ github.run_number }}

      - name: Upload Artifacts
        uses: actions/upload-artifact@v7
        with:
          name: code-review-metrics-${{ github.run_number }}
          path: |
            .github/reports/code-review-metrics-*.md
            review-data/metrics.json
          retention-days: 90

      - name: Job Summary
        run: |
          echo "# Code Review Metrics Generated 📊" >> $GITHUB_STEP_SUMMARY
          days="${{ github.event.inputs.days || '30' }}"
          echo "Period: ${days} days" >> $GITHUB_STEP_SUMMARY
          echo "Focus: Who is reviewing code and review volume per reviewer" >> $GITHUB_STEP_SUMMARY
          echo "Report artifacts uploaded with 90-day retention" >> $GITHUB_STEP_SUMMARY
          
          # Add summary stats to GitHub Actions summary
          if [ -f review-data/metrics.json ]; then
            python3 << 'EOF'
          import json
          import os
          
          with open('review-data/metrics.json', 'r') as f:
            metrics = json.load(f)
          
          summary = metrics['summary']
          reviewer_stats = metrics['reviewer_stats']
          
          # Find most active reviewer
          if reviewer_stats:
            top_reviewer = max(reviewer_stats.items(), key=lambda x: x[1]['reviews_given'])
            top_reviewer_name, top_reviewer_stats = top_reviewer
          else:
            top_reviewer_name, top_reviewer_stats = 'N/A', {'reviews_given': 0}
          
          with open(os.environ['GITHUB_STEP_SUMMARY'], 'a') as f:
            f.write(f"\n## Key Metrics\n")
            f.write(f"- **Active Reviewers:** {summary['total_reviewers']}\n")
            f.write(f"- **Total Reviews:** {summary['total_reviews']}\n") 
            f.write(f"- **PRs Analyzed:** {summary['total_prs_analyzed']}\n")
            f.write(f"- **Total Contributors:** {summary['total_contributors']}\n")
            f.write(f"- **Contributors Not Reviewing:** {summary['contributors_not_reviewing']}\n")
            f.write(f"- **Most Active Reviewer:** {top_reviewer_name} ({top_reviewer_stats['reviews_given']} reviews)\n")
          EOF
          fi