Python for Documentation Enhancement
Overview
Python is not currently used in our mdBook documentation workflow but represents a significant opportunity for documentation automation, content validation, and workflow enhancement. Our current system is entirely mdBook-based (Rust), with potential for Python tooling integration.
Current Documentation Stack
- Primary Technology: mdBook (Rust-based static site generator)
- Content Format: Markdown files with automated deployment
- Build Process: Pure mdBook workflow via GitHub Actions
- Deployment: GitHub Pages with zero Python dependencies
- Automation: Bash scripts and GitHub Actions workflows
Python Installation & Environment
Homebrew Python Setup
# Install Python via Homebrew (already available on macOS)
brew install python
# Verify installation
python3 --version # Python 3.12+ via Homebrew
pip3 --version # Package manager
which python3 # /opt/homebrew/bin/python3
Virtual Environment for Documentation Tools
# Create documentation tooling environment
python3 -m venv docs-tools
# Activate environment
source docs-tools/bin/activate
# Install documentation enhancement packages
pip install markdown beautifulsoup4 requests pyyaml
# Deactivate when done
deactivate
Potential Python Integration Opportunities
Documentation Validation Scripts
# Link validation for internal documentation
# scripts/validate-links.py (potential implementation)
import re
from pathlib import Path
from urllib.parse import urljoin, urlparse
def validate_internal_links(src_dir="src"):
"""Validate all internal markdown links in documentation."""
markdown_files = Path(src_dir).glob("**/*.md")
broken_links = []
for file_path in markdown_files:
content = file_path.read_text()
links = re.findall(r'\[.*?\]\((.*?)\)', content)
for link in links:
if not link.startswith('http'):
# Check if internal link exists
target_path = file_path.parent / link
if not target_path.exists():
broken_links.append(f"{file_path}: {link}")
return broken_links
if __name__ == "__main__":
broken = validate_internal_links()
if broken:
print("Broken internal links found:")
for link in broken:
print(f" {link}")
else:
print("✅ All internal links valid")
Content Analysis & Metrics
# Documentation metrics and analysis
# scripts/doc-metrics.py (potential implementation)
from pathlib import Path
import re
def analyze_documentation_metrics():
"""Generate comprehensive documentation metrics."""
src_path = Path("src")
stats = {
"total_files": 0,
"total_words": 0,
"total_lines": 0,
"code_blocks": 0,
"images": 0,
"internal_links": 0,
"external_links": 0
}
for md_file in src_path.glob("**/*.md"):
content = md_file.read_text()
lines = content.split('\n')
stats["total_files"] += 1
stats["total_lines"] += len(lines)
stats["total_words"] += len(content.split())
stats["code_blocks"] += len(re.findall(r'```', content))
stats["images"] += len(re.findall(r'!\[.*?\]', content))
# Count links
links = re.findall(r'\[.*?\]\((.*?)\)', content)
for link in links:
if link.startswith('http'):
stats["external_links"] += 1
else:
stats["internal_links"] += 1
return stats
# Usage in GitHub Actions or local scripts
metrics = analyze_documentation_metrics()
print(f"📊 Documentation contains {metrics['total_files']} files")
print(f"📝 Total words: {metrics['total_words']:,}")
print(f"🔗 Internal links: {metrics['internal_links']}")
mdBook Content Generation
# Auto-generate content for repetitive sections
# scripts/generate-content.py (potential implementation)
def generate_tool_readme_template(tool_name, description):
"""Generate standardized README template for tool documentation."""
template = f"""# {tool_name}
## Overview
{description}
## Our {tool_name} Implementation
- **Primary Use Case**: [Describe main usage]
- **Integration**: [How it fits in our workflow]
- **Configuration**: [Key settings and setup]
- **Benefits**: [Why we chose this tool]
## Workflow Integration
### Development Process
[Describe how this tool fits in daily workflow]
### Configuration Details
```bash
# Installation and setup commands
[Tool-specific commands]
Learning Journey
Current Proficiency
- ✅ Basic Setup: [What we've mastered]
- ✅ Core Features: [Primary functionality we use]
Areas for Growth
- 🔄 Advanced Features: [Capabilities to explore]
- 🔄 Optimization: [Performance improvements]
Integration with Development Tools
Primary Integrations
- [Tool 1]: [How they work together]
- [Tool 2]: [Integration benefits]
- [Tool 3]: [Workflow enhancement]
Practical Usage Patterns
[Real-world usage examples and best practices] """ return template
Generate README for new tools
new_tool_content = generate_tool_readme_template( "Example Tool", "Brief description of what this tool does for our workflow" )
## Automation Script Opportunities
### Pre-commit Hooks
```python
# .git/hooks/pre-commit (potential Python implementation)
#!/usr/bin/env python3
import subprocess
import sys
from pathlib import Path
def check_documentation_quality():
"""Run documentation quality checks before commit."""
checks = []
# Check for broken internal links
# Check for consistent formatting
# Validate YAML frontmatter if used
# Ensure all images exist
return all(checks)
if __name__ == "__main__":
if not check_documentation_quality():
print("❌ Documentation quality checks failed")
sys.exit(1)
print("✅ Documentation quality checks passed")
GitHub Actions Integration
# Potential Python integration in .github/workflows/
name: Documentation Quality
on:
pull_request:
branches: [ main ]
jobs:
python-checks:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- name: Setup Python
uses: actions/setup-python@v4
with:
python-version: '3.12'
- name: Install dependencies
run: |
pip install markdown beautifulsoup4 requests pyyaml
- name: Validate documentation
run: |
python scripts/validate-links.py
python scripts/doc-metrics.py
Real Documentation Enhancement Patterns
Content Validation Scripts
# Current manual workflow that could be Python-automated:
# 1. Check all internal links work
# 2. Validate SUMMARY.md matches actual files
# 3. Ensure consistent README.md structure
# 4. Verify all images are referenced and exist
# 5. Generate content metrics and reports
Workflow Integration Points
# Where Python could enhance our mdBook workflow:
Development Process:
1. Content Creation (Markdown) ← Python validation
2. Local Testing (mdbook serve) ← Python pre-checks
3. Git Commit ← Python pre-commit hooks
4. GitHub Actions ← Python quality checks
5. mdBook Build (Rust) ← Python post-processing
6. GitHub Pages Deploy ← Python verification
Current vs. Potential Workflow
Current Reality (100% mdBook/Rust)
# Our actual workflow - no Python involved
git add src/ # Add markdown changes
git commit -m "Update docs" # Commit to repository
git push origin main # Trigger GitHub Actions
# → GitHub Actions runs mdBook build
# → Deploys to GitHub Pages
Enhanced Workflow (mdBook + Python)
# Potential enhanced workflow with Python tooling
python scripts/validate-docs.py # Pre-commit validation
git add src/ # Add markdown changes
git commit -m "Update docs" # Triggers pre-commit hooks
git push origin main # Trigger enhanced GitHub Actions
# → GitHub Actions runs Python checks + mdBook build
# → Python generates metrics report
# → Deploys to GitHub Pages with validation report
Learning Journey & Implementation Plan
Current Status
- ✅ mdBook Mastery: Complete documentation workflow
- ✅ Markdown Proficiency: 28-file structured documentation system
- ✅ GitHub Actions: Automated deployment pipeline
- ✅ Python Environment: Available via Homebrew installation
Immediate Python Integration Opportunities
- 🔄 Link Validation: Automated broken link detection
- 🔄 Content Metrics: Documentation analytics and reporting
- 🔄 Quality Checks: Pre-commit validation scripts
- 🔄 Template Generation: Standardized content creation
Advanced Integration Goals
- 🔄 SEO Optimization: Meta tag and content optimization
- 🔄 Accessibility Checks: Documentation accessibility validation
- 🔄 Performance Monitoring: Site performance analysis
- 🔄 Content Migration: Automated content transformation tools
Integration with Development Tools
Primary Tool Stack (Current)
- mdBook: Static site generation and live preview
- Cursor IDE: Markdown editing with AI assistance
- GitHub Actions: Automated testing and deployment
- Git: Version control for all documentation changes
Enhanced Tool Stack (With Python)
- Python Scripts: Documentation validation and automation
- Pre-commit Hooks: Quality assurance before commits
- GitHub Actions: Enhanced CI/CD with Python checks
- Monitoring Tools: Python-based analytics and reporting
Practical Implementation Steps
Phase 1: Basic Validation
# Create Python tooling directory
mkdir scripts
cd scripts
# Create virtual environment for tools
python3 -m venv venv
source venv/bin/activate
# Install basic dependencies
pip install markdown beautifulsoup4 requests
pip freeze > requirements.txt
# Create first validation script
touch validate-links.py
Phase 2: CI/CD Integration
# Add Python checks to GitHub Actions
# Update .github/workflows/deploy.yml
# Add pre-commit hook configuration
# Create documentation metrics dashboard
Phase 3: Advanced Automation
# Content generation scripts
# SEO optimization tools
# Performance monitoring
# Automated content migration tools
This approach acknowledges the current mdBook-based reality while providing a clear path for Python integration where it would add genuine value to our documentation workflow.