Weekly - Project Quality Analyzer

AI Cost Tracking

✨ Features

🔍 Git Repository Scanning

Basic Usage

# Scan all Git repositories in ~/github
weekly scan ~/github

# Only show repositories with changes in the last 7 days (default)
weekly scan ~/github --since "7 days ago"

# Specify a custom output directory
weekly scan ~/github -o ./weekly-reports

# Run with 8 parallel jobs for faster scanning
weekly scan ~/github -j 8

# Generate JSON reports instead of HTML
weekly scan ~/github --format json

Recent Changes + changelog.md

cargo install git-cliff

Example Output

🔍 Scanning Git repositories in /Users/username/github...
✅ Scan complete! Generated reports for 3 repositories.
📊 Summary report: weekly-reports/summary.html

✅ org1/repo1: 5 checks
   ✓ style: Passed
   ✓ code_quality: Passed
   ✓ dependencies: 2 outdated packages found
   ✓ docs: Documentation is 85% complete
   ✓ tests: 92% test coverage

Command Options

Usage: weekly scan [OPTIONS] [ROOT_DIR]

  Scan multiple Git repositories and generate reports.

  ROOT_DIR: Directory containing Git repositories (default: current directory)

Options:
  -o, --output PATH      Output directory for reports (default: ./weekly-reports)
  -s, --since TEXT        Only include repositories with changes since this date (e.g., "7 days ago", "2023-01-01")
  --recursive / --no-recursive  Scan directories recursively (default: True)
  -j, --jobs INTEGER      Number of parallel jobs (default: 4)
  -f, --format [html|json|markdown]  Output format (default: html)
  --summary-only          Only generate a summary report, not individual reports
  -v, --verbose           Show detailed output
  --help                  Show this message and exit.

Programmatic Usage

from pathlib import Path
from datetime import datetime, timedelta
from weekly import GitScanner

# Create a scanner instance
scanner = GitScanner(
    root_dir=Path.home() / "github",
    output_dir="weekly-reports",
    since=datetime.now() - timedelta(days=7),
    recursive=True,
    jobs=4
)

# Run the scan
results = scanner.scan_all()

# Process results
for result in results:
    print(f"{result.repo.org}/{result.repo.name}:")
    for name, check in result.results.items():
        status = "✓" if check.is_ok else "✗"
        print(f"  {status} {name}: {check.message}")

🚀 Installation

Using pip

pip install weekly

Using Poetry (recommended)

poetry add weekly

For Development

# Clone the repository
git clone https://github.com/wronai/weekly.git
cd weekly

# Install with Poetry
poetry install --with dev

# Install pre-commit hooks
pre-commit install

# Activate the virtual environment
poetry shell

Usage

Basic Usage

weekly analyze /path/to/your/project

Command Line Options

Usage: weekly analyze [OPTIONS] PROJECT_PATH

  Analyze a Python project and provide quality insights.

  PROJECT_PATH: Path to the project directory (default: current directory)

Options:
  -f, --format [text|json|markdown]  Output format (default: text)
  -o, --output FILE                  Output file (default: stdout)
  --show-suggestions / --no-suggestions
                                      Show improvement suggestions (default: true)
  -v, --verbose                      Show detailed output
  --help                             Show this message and exit.

Examples

Output Example

Text Output

📊 Weekly Project Analysis Report
================================================================================
Project: example-project
Generated: 2025-06-07 12:34:56

Summary:
--------------------------------------------------------------------------------
✅ 5 passed
⚠️  3 warnings
❌ 1 errors

Detailed Results:
--------------------------------------------------------------------------------
✅ Project Structure
  Found Python project with proper structure

✅ Dependencies
  All dependencies are properly specified
  
⚠️  Test Coverage
  Test coverage is below 80% (currently 65%)
  
  Suggestions:
    • Add more test cases to improve coverage
    • Consider using pytest-cov for coverage reporting

❌ Documentation
  Missing API documentation
  
  Suggestions:
    • Add docstrings to all public functions and classes
    • Consider using Sphinx or MkDocs for API documentation

Recommended Actions:
--------------------------------------------------------------------------------
1. Improve Test Coverage
   • Add unit tests for untested modules
   • Add integration tests for critical paths
   • Set up code coverage reporting in CI

2. Enhance Documentation
   • Add docstrings to all public APIs
   • Create API documentation using Sphinx or MkDocs
   • Add examples to the README

Programmatic Usage

from pathlib import Path
from weekly import analyze_project
from weekly.core.report import Report

# Analyze a project
report = analyze_project(Path("/path/to/your/project"))

# Get report as dictionary
report_data = report.to_dict()

# Get markdown report
markdown = report.to_markdown()

# Print summary
print(f"✅ {report.summary['success']} passed")
print(f"⚠️  {report.summary['warnings']} warnings")
print(f"❌ {report.summary['errors']} errors")

# Get suggestions
for suggestion in report.get_suggestions():
    print(f"\n{suggestion['title']}:")
    for item in suggestion['suggestions']:
        print(f"  • {item}")

### Most Active Files

- `src/main.py`: 12 changes
- `tests/test_main.py`: 8 changes
- `README.md`: 5 changes

### Languages Used

- `.py`: 15 files
- `.md`: 3 files
- `.json`: 2 files

## 📋 Next Steps

- [ ] Add tests for recent changes
- [ ] Refactor large files: src/utils.py, src/processor.py...

## 📜 Recent Commits

- `a1b2c3d` Fix bug in data processing (2023-05-15)
- `f4e5d6a` Add new feature X (2023-05-14)
- `b3c4d5e` Update documentation (2023-05-13)
- `c6d7e8f` Refactor module Y (2023-05-12)
- `d9e0f1a` Initial commit (2023-05-10)

*[View full history in the JSON file]*

Development

Setup

Running Tests

poetry run pytest

Code Style

black .
isort .
flake8
mypy .

Contributing

License

Author

Acknowledgments

Status