Self-Hosted Git Repository Analytics: Hercules vs Git of Theseus vs GitStats

Introduction

Understanding how your codebase evolves over time provides insights that raw commit logs cannot reveal. Which files change most frequently? How has code complexity grown? Who are the key contributors to each subsystem? Git repository analytics tools answer these questions by mining your version history and visualizing patterns in development activity.

This article compares three powerful open-source Git analytics tools: Hercules, Git of Theseus, and GitStats. Each takes a different approach to extracting intelligence from your Git history — from statistical analysis to visualization to narrative storytelling.

Feature Comparison

Hercules: Deep Statistical Analysis

Hercules, developed by source{d} (now part of the Linux Foundation), is the most sophisticated Git analysis tool in this comparison. It goes beyond surface-level statistics to perform structural analysis of your codebase — tracking how files are coupled together, identifying ownership patterns, and measuring developer productivity through multiple lenses.

Key Features

• Burndown analysis: Tracks project velocity over time by measuring when work items were completed
• File coupling (Co-occurrence): Identifies which files tend to be modified together in the same commits — crucial for understanding architectural boundaries
• Developer ownership: Maps which developers “own” each file based on contribution history and knowledge distribution
• Coupling graphs: Generates visual network graphs showing file relationships
• Shotness analysis: Identifies files that receive many small, isolated changes (potential code smells)

Docker Deployment

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# Pull the Hercules image
docker pull srcd/hercules:latest

# Run analysis on a local repository
docker run --rm -v $(pwd):/repo srcd/hercules:latest \
  hercules --burndown --coupling --pb /repo/report.pb /repo

# Generate visualizations with Labours
docker run --rm -v $(pwd):/repo srcd/hercules:latest \
  labours -m burndown-project -o /repo/output /repo/report.pb

Understanding Coupling Analysis

Hercules’s coupling analysis is particularly valuable for refactoring decisions. The tool generates a weighted graph where edges between files represent how often they were modified in the same commit. Dense clusters in this graph often reveal:

• Shared utility modules that many features depend on
• Tightly coupled components that should be consolidated
• Cross-cutting concerns like logging or authentication

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# Generate coupling graph as PNG
hercules --coupling --burndown --first-parent --pb report.pb /path/to/repo
labours -m couples -o coupling_graph.png report.pb

Git of Theseus: Code Survival Analysis

Git of Theseus takes a unique philosophical approach to repository analysis. Inspired by the Ship of Theseus paradox (if you replace every plank of a ship, is it still the same ship?), this tool measures how much of a codebase’s original code survives over time.

Key Features

• Code survival rate: Measures what percentage of original code lines still exist after N months/years
• Stacked area charts: Visualize code composition by age
• Split analysis: Compare two time periods to see what changed
• Language-agnostic: Works with any programming language
• Year-over-year comparison: Track code churn patterns across years

Installation and Usage

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# Clone and set up
git clone https://github.com/erikbern/git-of-theseus
cd git-of-theseus
pip install -r requirements.txt

# Run survival analysis
python git_of_theseus.py /path/to/repo

# Run split analysis (compare two time periods)
python git_of_theseus.py --split 2024-01-01 /path/to/repo

# Generate report with specific file extension filter
python git_of_theseus.py --ext py,java,go /path/to/repo

What Survival Analysis Reveals

The stacked area chart output shows how your codebase is composed of code written in different years. A healthy, actively maintained project should show:

• Recent-year code dominating the top layers (active development)
• Older code shrinking toward the bottom (refactoring and modernization)
• No single year accounting for more than 60% of total lines (balanced maintenance)

If 70%+ of your code is from a single year, it indicates either a rewrite that hasn’t been maintained, or a project where most development happened in one burst and then stopped.

GitStats: Classic Repository Statistics

GitStats is the most straightforward tool of the three — it generates comprehensive HTML reports with charts and tables covering every aspect of your repository’s history. While less analytically sophisticated than Hercules or Git of Theseus, GitStats excels at producing ready-to-share reports that non-technical stakeholders can understand.

Key Features

• Activity timeline: Commits per day/week/month over the entire project history
• Author statistics: Top contributors by commits, lines added/removed
• File statistics: Most changed files, file type distribution, lines of code by extension
• Hour/Day analysis: When does your team commit? (reveals timezone patterns)
• Tag/release tracking: Activity between releases

Installation and Usage

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# Clone GitStats
git clone https://github.com/tomgi/git_stats
cd git_stats
bundle install

# Generate report
./git_stats generate -o /path/to/output /path/to/repo

# Or using Docker
docker run --rm -v $(pwd):/repo -v $(pwd)/output:/output \
  tomgi/git_stats generate -o /output /repo

Report Contents

The generated HTML report includes:

1. General statistics: Total commits, authors, files, lines of code
2. Activity charts: Hour-of-day, day-of-week, and month-of-year commit heatmaps
3. Author breakdowns: Per-author commit counts, insertions, deletions
4. File analysis: File count by extension, lines of code by language
5. Timeline: Commit activity timeline with rolling averages

Use Cases for Each Tool

Why Self-Host Your Git Analytics?

Running your own Git analytics tools keeps your repository data within your network. Many commercial offerings like GitHub Insights, GitLab Analytics, or Bitbucket reports require uploading your data to their cloud — or only work with their specific platform. Self-hosted tools work with any Git repository regardless of where it’s hosted.

These tools also integrate into your existing CI/CD pipeline. For broader CI/CD monitoring, see our self-hosted CI/CD dashboard guide. You can generate reports after every release, track metrics over time, and feed the data into your existing monitoring stack. Organizations handling proprietary or regulated code should never send their entire Git history to third-party services. Self-hosted analytics provide insights without the compliance risk.

For teams practicing code review, our Gerrit vs Review Board comparison covers self-hosted code review platforms that pair well with Git analytics tools. Understanding which files change together (via Hercules) helps reviewers understand the full scope of a pull request’s impact.

FAQ

Do these tools work with large repositories?

GitStats and Git of Theseus work well with repositories up to several hundred MB. Hercules is designed for large repositories but requires more RAM — plan for 2-4 GB for repositories with 50,000+ commits. For repositories with millions of commits (like the Linux kernel), expect analysis to take several hours and consume 8+ GB RAM.

Can I run these on a schedule via cron?

Yes, all three tools are CLI-based and can be scheduled via cron or CI pipeline. GitStats is the most cron-friendly with its deterministic HTML output. Hercules requires managing the intermediate protobuf file. Git of Theseus needs Python dependency management but works reliably in Docker.

How do these compare to GitHub’s built-in insights?

GitHub’s Insights tab provides basic commit frequency, pull request merge time, and contributor stats. GitStats generates comparable visualizations but works with any Git host (GitLab, Bitbucket, Gitea). Hercules and Git of Theseus provide analysis that GitHub Insights does not — coupling analysis and code survival rates respectively.

Can I compare multiple repositories side by side?

None of these tools natively support cross-repository comparison. The typical workflow is to generate reports for each repository separately and compare the output manually. For monorepo environments, you can use GitStats to filter by subdirectory, or Hercules to analyze coupling across the entire monorepo structure.

Which tool is best for a quarterly engineering review presentation?

GitStats produces the most polished, presentation-ready reports out of the box. Its HTML output includes clean charts and tables that can be shared directly or screenshot for slides. Hercules’s coupling graphs provide deeper technical insights but require more explanation for non-technical audiences.

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