dependency-auditor

name	dependency-auditor
description	Dependency and license review for Python projects. Use when: auditing requirements.txt, checking for vulnerabilities, reviewing licenses, updating dependencies, managing version constraints.

Dependency Auditor

When to Use

• Reviewing requirements.txt for security issues
• Checking dependency licenses for compatibility
• Updating outdated packages
• Resolving dependency conflicts
• Adding new dependencies safely

Security Auditing

Using pip-audit

# Install pip-audit
pip install pip-audit

# Audit current environment
pip-audit

# Audit requirements file
pip-audit -r requirements.txt

# Output as JSON for CI
pip-audit --format json -o audit-results.json

Using safety

# Install safety
pip install safety

# Check dependencies
safety check -r requirements.txt

# With API key for full database
safety check --key $SAFETY_API_KEY -r requirements.txt

GitHub Actions Integration

- name: Security audit
  run: |
    pip install pip-audit
    pip-audit -r requirements.txt --strict

License Compliance

Checking Licenses

# Install pip-licenses
pip install pip-licenses

# List all licenses
pip-licenses --format=markdown

# Check for problematic licenses
pip-licenses --fail-on="GPL;AGPL"

# Output as JSON
pip-licenses --format=json -o licenses.json

Common License Categories

License	Commercial Use	Copyleft
MIT	✅	No
Apache-2.0	✅	No
BSD-3-Clause	✅	No
GPL-3.0	⚠️ Careful	Yes
AGPL-3.0	⚠️ Careful	Yes (network)

Safe Licenses for This Project

MIT
Apache-2.0
BSD-2-Clause
BSD-3-Clause
ISC
Python-2.0
PSF-2.0

Version Management

Version Constraint Patterns

# Exact (reproducible but no security updates)
requests==2.31.0

# Compatible release (recommended)
requests~=2.31.0  # >=2.31.0, <2.32.0

# Minimum with ceiling
requests>=2.31.0,<3.0.0

# Avoid: no upper bound
requests>=2.31.0  # Risky

Update Strategy

# Check for outdated packages
pip list --outdated

# Update a specific package
pip install --upgrade requests

# Generate updated requirements
pip freeze > requirements.txt

Using pip-tools

# Install pip-tools
pip install pip-tools

# Define abstract requirements in requirements.in
# Then compile to pinned requirements.txt
pip-compile requirements.in

# Update all
pip-compile --upgrade requirements.in

Dependency Review Checklist

For each new dependency:

1. Purpose: Does it solve a real need?
2. Maintenance: Last commit < 6 months? Active maintainers?
3. Popularity: Sufficient downloads/stars?
4. License: Compatible with project license?
5. Security: Any known vulnerabilities?
6. Size: Reasonable dependency footprint?
7. Alternatives: Is there a lighter option?

requirements.txt Best Practices

# requirements.txt

# Core dependencies (pinned for reproducibility)
requests==2.31.0
beautifulsoup4==4.12.2
playwright==1.40.0

# Database
psycopg2-binary==2.9.9
pgvector==0.2.4

# AI/ML (careful with large packages)
openai==1.6.0

# Development (separate file: requirements-dev.txt)
# pytest==7.4.3
# black==23.12.0

Anti-patterns

• Unpinned versions: requests instead of requests==2.31.0
• No dev separation: Mix test tools with production deps
• Giant packages: Bringing in pandas for one function
• Ignoring CVEs: Not running security audits in CI
• License ignorance: Using GPL in proprietary code
• Stale dependencies: Not updating for years

CI Integration

name: Dependency Audit

on:
  schedule:
    - cron: '0 0 * * 1'  # Weekly
  pull_request:
    paths:
      - 'requirements*.txt'

jobs:
  audit:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      
      - name: Security audit
        run: |
          pip install pip-audit
          pip-audit -r requirements.txt
      
      - name: License check
        run: |
          pip install pip-licenses
          pip-licenses --fail-on="GPL;AGPL"