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A comprehensive pipeline combining linters, security scanning, AI validation, and testing with auto-fix and ticket creation.
Overview
This example demonstrates a production-grade pyqual pipeline that:
Analyzes code complexity with code2llm
Runs 5 linters in sequence (ruff, pylint, flake8, mypy, interrogate)
Scans for security issues (bandit, pip-audit, trufflehog)
Validates with AI (vallm)
Auto-fixes on failure (llx)
Runs tests with coverage
Checks maintainability index (radon)
Creates TODO.md tickets for remaining failures
Quality Gates (21 gates)
Complexity
Metric
Gate
Tool
cc
≤ 15
code2llm
maintainability_index
≥ 65
radon
Coverage
Metric
Gate
Tool
coverage
≥ 85%
pytest-cov
Linters
Metric
Gate
Tool
ruff_errors
≤ 5
ruff
ruff_fatal
≤ 0
ruff
pylint_score
≥ 8.0
pylint
flake8_violations
≤ 10
flake8
mypy_errors
≤ 0
mypy
docstring_coverage
≥ 85%
interrogate
Security
Metric
Gate
Tool
bandit_high
≤ 0
bandit
bandit_medium
≤ 3
bandit
vuln_critical
≤ 0
pip-audit
vuln_high
≤ 0
pip-audit
secrets_found
≤ 0
trufflehog/gitleaks
AI Validation
Metric
Gate
Tool
vallm_pass
≥ 90%
vallm
Quick Start
# Install all tools
pip install pyqual[all] ruff pylint flake8 mypy interrogate bandit radon
# Copy config
cp pyqual.yaml /path/to/your/project/
cd /path/to/your/project
# Run the full pipeline
pyqual run
# Or check gates only
pyqual gates