A terminal-based HAR (HTTP Archive) file analyzer built with Go and Charm's Bubbletea framework. Analyze web performance, compare multiple HAR files, and generate detailed reports directly in your terminal.

• Performance Metrics: TTFB, Page Load Time, Core Web Vitals
• Network Analysis: DNS lookup, TCP connection, SSL handshake timings
• Request Statistics: Total requests, error rates, third-party analysis
• Cache Efficiency: Hit ratios and optimization recommendations
• Resource Breakdown: Analysis by content type (JS, CSS, images, etc.)

• Table View: Sortable and filterable list of all HTTP requests
• Detail View: In-depth request/response analysis with timing breakdown
• Metrics Dashboard: Performance overview with recommendations
• Timeline View: ASCII waterfall chart like Chrome DevTools
• Comparison View: Side-by-side performance analysis of multiple HAR files
• Report Export: Generate professional reports in JSON, CSV, HTML, and PDF formats
• Multi-file Support: Load and compare multiple HAR files seamlessly

• Streaming JSON Parser: Handles large HAR files efficiently
• Buffered I/O: Optimized for files of any size
• Memory Efficient: Pagination and lazy loading for large datasets

Download the latest release for your platform from GitHub Releases.

# Pull and run from GitHub Container Registry
docker pull ghcr.io/YOUR_USERNAME/har-analyzer:latest

# Run with HAR files from current directory
docker run --rm -v $(pwd):/data ghcr.io/YOUR_USERNAME/har-analyzer:latest /data/example.har

# Compare multiple files
docker run --rm -v $(pwd):/data ghcr.io/YOUR_USERNAME/har-analyzer:latest /data/before.har /data/after.har

# Add the tap
brew tap YOUR_USERNAME/tap

# Install
brew install har-analyzer

# Debian/Ubuntu
wget https://github.com/YOUR_USERNAME/har-analyzer/releases/download/v1.0.0/har-analyzer_1.0.0_linux_amd64.deb
sudo dpkg -i har-analyzer_1.0.0_linux_amd64.deb

# Red Hat/CentOS/Fedora
wget https://github.com/YOUR_USERNAME/har-analyzer/releases/download/v1.0.0/har-analyzer_1.0.0_linux_amd64.rpm
sudo rpm -i har-analyzer_1.0.0_linux_amd64.rpm

# Alpine Linux
wget https://github.com/YOUR_USERNAME/har-analyzer/releases/download/v1.0.0/har-analyzer_1.0.0_linux_amd64.apk
sudo apk add har-analyzer_1.0.0_linux_amd64.apk

# Clone and build
git clone https://github.com/YOUR_USERNAME/har-analyzer
cd har-analyzer
go build -o har-analyzer ./cmd/main.go

# Analyze a single HAR file
./har-analyzer example.har

# Analyze multiple HAR files for comparison
./har-analyzer before.har after.har

• ↑/k, ↓/j: Navigate up/down in table
• Enter: View request details
• Esc: Go back/cancel
• Tab: Switch between HAR files (if multiple)
• m: Toggle metrics view
• t: Toggle timeline view
• c: Toggle comparison view (when multiple files loaded)
• e: Export reports (JSON/CSV/HTML/PDF)
• ?: Toggle help
• /: Filter requests
• q: Quit

Filter requests by typing after pressing /:

• GET - Show only GET requests
• javascript - Show only JavaScript files
• api/ - Show only API calls
• 404 - Show only 404 errors

Compare multiple HAR files to analyze performance changes:

# Before vs After deployment comparison
./har-analyzer before-deploy.har after-deploy.har

# A/B testing analysis
./har-analyzer variant-a.har variant-b.har

# Cross-environment comparison
./har-analyzer staging.har production.har

Press c when multiple files are loaded to see:

• Side-by-side metrics comparison with percentage changes
• Performance regression/improvement detection
• Automated insights and recommendations
• Color-coded indicators: ✅ Improvements, ⚠️ Regressions
• Summary statistics: Better/Worse/Unchanged metrics count

Example comparison output:

Performance Comparison (2 files)
📊 6 Better | 1 Worse | 3 Unchanged (of 10 metrics)

Metric                 File 1 (Base)   File 2
Total Load Time        2500.0ms        1800.0ms (-28.0% ✅)
Time to First Byte     450.0ms         280.0ms (-37.8% ✅)
Total Requests         45              52 (+7 +15.6% ⚠️)
Cache Hit Ratio        45.0%           78.0% (+33.0% ✅)

Key Insights:
• Page load time improved significantly
• Cache efficiency improved
• Error rate remained stable or improved

Generate professional reports in multiple formats by pressing e:

Supported Formats:

• JSON: Machine-readable data for integration with other tools
• CSV: Spreadsheet-compatible metrics for data analysis
• HTML: Styled web report with interactive elements and visual indicators
• PDF: Professional document with charts, tables, and recommendations

Report Contents:

• Executive Summary: Key performance indicators and overall health
• Detailed Metrics: Complete breakdown of all timing and size metrics
• Performance Comparison: Side-by-side analysis (when multiple files loaded)
• Recommendations: Automated insights and optimization suggestions
• Visual Indicators: Color-coded status indicators for quick assessment

Example exported files:

har-analysis-2024-01-15_14-30-25.json  # Raw data export
har-analysis-2024-01-15_14-30-25.csv   # Metrics spreadsheet
har-analysis-2024-01-15_14-30-25.html  # Interactive web report
har-analysis-2024-01-15_14-30-25.pdf   # Professional document

PDF Report Features:

• Professional Layout: Clean, branded design suitable for stakeholders
• Color-coded Metrics: Visual performance indicators (green/yellow/red)
• Comparison Tables: Side-by-side analysis with improvement/regression markers
• Automated Recommendations: Actionable insights based on performance data
• Summary Dashboard: Executive overview with key metrics
• Multi-page Support: Comprehensive analysis without space constraints

har-analyzer/
├── cmd/
│   └── main.go                 # CLI entry point
├── internal/
│   ├── har/
│   │   ├── types.go           # HAR data structures
│   │   ├── parser.go          # HAR file parsing
│   │   └── analyzer.go        # Performance analysis
│   └── tui/
│       ├── model.go           # Main Bubbletea model
│       └── views/             # UI view components
└── go.mod

• Time to First Byte (TTFB)

  • ✅ Good: ≤200ms
  • ⚡ Needs Improvement: 200-800ms
  • ⚠️ Poor: >800ms

• Page Load Time

  • ✅ Good: ≤1.5s
  • ⚡ Needs Improvement: 1.5-3s
  • ⚠️ Poor: >3s

• Average DNS lookup time
• TCP connection establishment
• SSL handshake duration
• Request/response timing breakdown

• Cache hit ratio calculation
• Resource optimization opportunities
• Compression efficiency analysis

• Streaming JSON Parser: Uses json.NewDecoder for memory efficiency
• Buffered I/O: 64KB buffer for optimal file reading performance
• Validation: Comprehensive HAR format validation
• Error Handling: Graceful handling of malformed HAR files

• Bubbletea: Modern terminal UI framework following The Elm Architecture
• Bubbles Components: Pre-built UI components (table, textinput, etc.)
• Lipgloss: Styling and layout system for terminal interfaces
• Responsive Design: Adapts to different terminal sizes

• Lazy Loading: Load data on-demand for large HAR files
• Pagination: Display only visible subset of data
• Efficient Filtering: Fast string matching without regex overhead
• Memory Management: Careful handling of large datasets

HAR Analysis - File 1/2
Requests: 127 | Total Time: 2847.3ms | Total Size: 1.2MB | Errors: 0

┌────────┬────────┬──────────────────────────────────────────────┬──────────┬────────┬─────────────────┐
│ Method │ Status │ URL                                          │ Time     │ Size   │ Type            │
├────────┼────────┼──────────────────────────────────────────────┼──────────┼────────┼─────────────────┤
│ GET    │ 200    │ https://example.com/                         │ 234.5    │ 15.2KB │ html            │
│ GET    │ 200    │ https://example.com/assets/app.js            │ 145.2    │ 87.5KB │ javascript      │
│ GET    │ 200    │ https://example.com/assets/style.css         │ 89.1     │ 23.1KB │ css             │
└────────┴────────┴──────────────────────────────────────────────┴──────────┴────────┴─────────────────┘

Press ? for help, / to filter, m for metrics, q to quit

• Bubbletea: Terminal user interface framework
• Bubbles: Pre-built UI components
• Lipgloss: Styling and layout
• Standard Library: JSON parsing, file I/O, string manipulation

The project includes a comprehensive CI/CD pipeline with:

• Multi-Go Version Testing: Tests against Go 1.22, 1.23, and 1.24
• Cross-Platform Builds: Linux, macOS, Windows (amd64, arm64)
• Code Quality: Static analysis with staticcheck, golint, and go vet
• Security Scanning: Vulnerability scans with Trivy and Gosec
• Coverage Reports: Automated test coverage with Codecov

• GoReleaser: Automated cross-platform binary builds
• GitHub Releases: Automatic release creation with changelogs
• Package Distribution: Debian/RPM/Alpine packages
• Homebrew Formula: Automatic tap updates
• Container Images: Multi-arch Docker images (amd64/arm64)

• GitHub Container Registry: ghcr.io/YOUR_USERNAME/har-analyzer
• Multi-Architecture: Native amd64 and arm64 support
• Security: Regular vulnerability scans and updates
• Size Optimized: Minimal scratch-based images

• Dependency Tracking: Complete SBOM generation for security compliance
• Supply Chain Security: Signed releases with Cosign
• Vulnerability Monitoring: Automated security updates via Dependabot

# Run tests
go test -v ./...

# Run tests with coverage
go test -race -coverprofile=coverage.out ./...

# View coverage
go tool cover -html=coverage.out

# Install development dependencies
go mod download

# Run static analysis
staticcheck ./...
golint ./...
go vet ./...

# Build with version info
go build -ldflags="-X main.version=dev" -o har-analyzer ./cmd/main.go

# Build locally
docker build -t har-analyzer:dev .

# Test the container
docker run --rm -v $(pwd):/data har-analyzer:dev /data/example.har

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Make your changes
4. Add tests for new functionality
5. Run the test suite (go test ./...)
6. Commit your changes (git commit -m 'feat: add amazing feature')
7. Push to the branch (git push origin feature/amazing-feature)
8. Submit a pull request

This project follows Conventional Commits:

• feat: New features
• fix: Bug fixes
• docs: Documentation changes
• style: Code style changes
• refactor: Code refactoring
• test: Test additions or changes
• chore: Maintenance tasks

MIT License - see LICENSE file for details.

For security issues, please email [email protected] or use GitHub Security Advisories.

• Built with Bubbletea TUI framework
• PDF generation powered by gofpdf
• Inspired by Chrome DevTools Network panel

• For very large HAR files (>100MB), consider using --buffer-size flag to increase buffer size
• Use filtering to focus on specific request types or domains
• Multiple file comparison works best with files of similar size and structure
• Terminal width affects table column sizing - wider terminals show more data

• JSON/CSV/HTML report export
• Timeline waterfall visualization
• Custom performance budgets
• Plugin system for custom analysis
• Real-time HAR file monitoring
• Automated performance regression detection