ennam-django-apidog 0.1.3

Django integration for APIDOG - Export, sync, and manage OpenAPI schemas

ennam-django-apidog

Django integration for APIDOG - Export, sync, and manage OpenAPI schemas between Django REST Framework and APIDOG Cloud.

Features

• Export OpenAPI Schema - Generate OpenAPI 3.0 schemas from your Django REST Framework APIs
• Sync with APIDOG Cloud - Push and pull schemas to/from APIDOG Cloud
• Compare Schemas - Compare local schemas with cloud versions
• Environment Management - Generate environment configurations for different deployments
• Schema Hooks - Custom drf-spectacular extensions for handling edge cases
• Templates - Ready-to-use Makefile, Docker Compose, and configuration files

Installation

pip install ennam-django-apidog

Quick Start

1. Add to INSTALLED_APPS

# settings.py
INSTALLED_APPS = [
    ...
    'rest_framework',
    'drf_spectacular',
    'ennam_django_apidog',
]

2. Configure DRF Spectacular

# settings.py
REST_FRAMEWORK = {
    'DEFAULT_SCHEMA_CLASS': 'drf_spectacular.openapi.AutoSchema',
}

SPECTACULAR_SETTINGS = {
    'TITLE': 'Your API',
    'DESCRIPTION': 'Your API description',
    'VERSION': '1.0.0',
    'SERVE_INCLUDE_SCHEMA': False,
}

3. Add URL Routes

# urls.py
from drf_spectacular.views import SpectacularAPIView, SpectacularSwaggerView

urlpatterns = [
    ...
    path('api/schema/', SpectacularAPIView.as_view(), name='schema'),
    path('api/schema/swagger-ui/', SpectacularSwaggerView.as_view(url_name='schema'), name='swagger-ui'),
]

4. Initialize APIDOG

python manage.py apidog init

5. Export Schema

python manage.py apidog export

Configuration

Configure APIDOG settings in your Django settings.py:

APIDOG_SETTINGS = {
    # Output directory for schemas (default: apidog/ at project root)
    'OUTPUT_DIR': None,

    # Schema endpoint (default: /api/schema/)
    'SCHEMA_ENDPOINT': '/api/schema/',

    # APIDOG Cloud credentials
    'PROJECT_ID': 'your-project-id',  # or use env var APIDOG_PROJECT_ID
    'TOKEN': 'your-api-token',        # or use env var APIDOG_TOKEN

    # API configuration
    'API_VERSION': '2024-03-28',
    'API_BASE_URL': 'https://api.apidog.com/v1',
    'TIMEOUT': 60,

    # Environment configurations
    'ENVIRONMENTS': {
        'local': {
            'name': 'Local Development',
            'base_url': 'http://localhost:8000',
        },
        'production': {
            'name': 'Production',
            'base_url': 'https://api.yourapp.com',
        },
    },
}

Or use environment variables:

export APIDOG_PROJECT_ID="your-project-id"
export APIDOG_TOKEN="your-api-token"

Commands

Initialize Project

# Create apidog directory and templates
python manage.py apidog init

# Force overwrite existing files
python manage.py apidog init --force

Export Schema

# Export as JSON (default)
python manage.py apidog export

# Export as YAML
python manage.py apidog export --format yaml

# Custom output directory
python manage.py apidog export --output /path/to/output/

Validate Schema

# Validate latest schema
python manage.py apidog validate

# Validate specific file
python manage.py apidog validate --file /path/to/schema.json

Push to APIDOG Cloud

# Push latest schema
python manage.py apidog push

# Push specific file
python manage.py apidog push --file /path/to/schema.json

Pull from APIDOG Cloud

# Pull to default location
python manage.py apidog pull

# Pull to specific file
python manage.py apidog pull --output /path/to/output.json

Compare Schemas

# Compare local with cloud
python manage.py apidog compare

Generate Environment Config

python manage.py apidog env-config

Using Schema Hooks

Add custom schema hooks to handle edge cases:

# settings.py
SPECTACULAR_SETTINGS = {
    ...
    'PREPROCESSING_HOOKS': [
        'ennam_django_apidog.schema_hooks.preprocess_exclude_problematic_views',
    ],
    'EXTENSIONS': [
        'ennam_django_apidog.schema_hooks.BaseSerializerExtension',
    ],
}

Makefile Commands

After running apidog init, use the Makefile for shortcuts:

# Show help
make -f Makefile.apidog help

# Export schema
make -f Makefile.apidog export

# Push to cloud
make -f Makefile.apidog push

# Compare with cloud
make -f Makefile.apidog compare

# Export and push
make -f Makefile.apidog sync

Docker Support

Use the generated Docker Compose file for mock server:

# Start mock server
docker-compose -f docker-compose.apidog.yml up -d apidog-mock

# Mock server available at http://localhost:4010

CI/CD Integration

Example GitHub Actions workflow:

- name: Export OpenAPI Schema
  run: |
    python manage.py apidog export --format json

- name: Push to APIDOG
  env:
    APIDOG_PROJECT_ID: ${{ secrets.APIDOG_PROJECT_ID }}
    APIDOG_TOKEN: ${{ secrets.APIDOG_TOKEN }}
  run: |
    python manage.py apidog push

Documentation

For full documentation, see docs/GUIDE.md.

Testing

Running Tests

# Install test dependencies first
pip install -e ".[dev]"

# Run all tests with coverage
pytest --cov=src --cov-report=term

# Run specific test file
pytest tests/test_commands.py -v

# Run specific test
pytest tests/test_commands.py::TestApidogCommand::test_export_command -v

# Run only HTTP mocking tests
pytest tests/test_commands_http.py -v

# Run only edge case tests
pytest tests/test_commands_errors.py -v

# Generate HTML coverage report
pytest --cov=src --cov-report=html
# Open htmlcov/index.html to view coverage

Test Coverage

Current coverage: 40-50% focusing on critical functionality:

HTTP Mocking Tests (14 tests):

• ✅ Push schema to APIDOG (success, auth, timeout, no credentials)
• ✅ Pull schema from APIDOG (success, auth, 404, 500 errors)
• ✅ Compare local vs cloud schemas

Edge Case Tests (17 tests):

• ✅ Export command: directory creation, formats, indentation
• ✅ Validate command: invalid JSON, missing fields
• ✅ Init command: setup, gitignore, readme, overwrite
• ✅ Environment configuration

Settings & Credentials Tests (7 tests):

• ✅ Configuration hierarchy (settings → env → defaults)
• ✅ Credential resolution with overrides
• ✅ Settings reload and caching

All tests use HTTP mocking via responses library - no real API calls during testing.

Development Setup

# Install development dependencies
pip install -e ".[dev]"

# Install pre-commit hooks
pre-commit install

# Run linting
ruff check src/ tests/
ruff format src/ tests/

# Run type checking
mypy src/

# Run all pre-commit checks
pre-commit run --all-files

Pre-commit Hooks

This project uses pre-commit hooks for quality assurance:

• ruff: Code linting and formatting
• mypy: Static type checking with Django stubs
• Standard checks: YAML/TOML validation, trailing whitespace, etc.

Hooks run automatically on git commit. The same checks run in CI.

Release Checklist

Before publishing to PyPI:

• All tests pass: pytest --cov=src
• Coverage ≥ 40%: pytest --cov=src --cov-report=term
• No mypy errors: mypy src/
• Linting passes: ruff check src/ tests/
• Pre-commit passes: pre-commit run --all-files
• CI passes on all Python/Django versions
• Version bumped in pyproject.toml
• CHANGELOG.md updated
• Test build: python -m build && twine check dist/*

Continuous Integration

Tests run on GitHub Actions with:

• Python versions: 3.8, 3.9, 3.10, 3.11, 3.12
• Django versions: 3.2, 4.0, 4.1, 4.2, 5.0

See .github/workflows/test.yml for details.

Requirements

• Python >= 3.8
• Django >= 3.2
• Django REST Framework >= 3.12
• drf-spectacular >= 0.26

License

MIT License - see LICENSE for details.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

Links

• APIDOG Website
• drf-spectacular Documentation
• Django REST Framework