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- Refactor code into testable bot.py module with MastodonRSSBot class - Create 20+ unit tests covering core functionality and edge cases - Create 10+ integration tests for RSS parsing and Mastodon posting - Add GitHub Actions workflow for automated testing - Unit tests on Python 3.10, 3.11, 3.12 - Integration tests with mocked external services - Code quality checks (flake8, black, mypy) - Docker build validation - Configure pytest with 80% minimum coverage requirement - Add test dependencies in requirements-test.txt - Update .gitignore to exclude test artifacts - Add comprehensive TESTING.md documentation - Add test status badge to README - Maintain full backward compatibility with existing setup
215 lines
6.1 KiB
Markdown
215 lines
6.1 KiB
Markdown
# Test Implementation Summary
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## Overview
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Comprehensive test suite designed for the Masto-RSS bot with unit tests, integration tests, and automated CI/CD testing via GitHub Actions.
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## Files Created
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### 1. Core Refactoring
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- **[bot.py](bot.py)** - Refactored core functionality into testable `MastodonRSSBot` class
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- Separated concerns (parsing, posting, state management)
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- Dependency injection for easier testing
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- Error handling and logging
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- Type hints for better code clarity
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- **[main.py](main.py)** - Simplified entry point
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- Loads configuration from environment
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- Instantiates and runs the bot
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- Clean separation from core logic
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### 2. Test Files
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#### [test_bot.py](test_bot.py) - Unit Tests
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Contains **20+ unit tests** covering:
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- Bot initialization with configuration
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- Loading/saving processed entries (with and without existing files)
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- Directory creation for state files
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- Status formatting from feed entries
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- Mastodon posting (success and failure cases)
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- Feed parsing (success, errors, malformed data)
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- Processing new entries (all new, partially processed, no entries)
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- Handling entries without URLs
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- Failed posts don't get marked as processed
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- Main entry point configuration loading
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**Coverage:** Core business logic, edge cases, error handling
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#### [test_integration.py](test_integration.py) - Integration Tests
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Contains **10+ integration tests** covering:
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- End-to-end RSS to Mastodon flow
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- Real RSS 2.0 feed parsing
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- Real Atom feed parsing
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- State persistence across bot runs
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- Incremental feed updates (new entries added over time)
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- Network error handling (500 errors, timeouts)
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- Malformed XML handling
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- Different visibility levels (public, unlisted, private, direct)
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- Rate limiting error handling
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- Retry mechanisms
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**Coverage:** Component integration, external service mocking, data flow
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### 3. Configuration Files
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#### [pytest.ini](pytest.ini)
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- Test discovery patterns
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- Coverage settings (80% minimum)
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- Output formatting
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- Test markers (unit, integration, slow)
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- Coverage exclusions
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#### [requirements-test.txt](requirements-test.txt)
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Test dependencies:
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- `pytest` - Testing framework
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- `pytest-cov` - Coverage plugin
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- `pytest-mock` - Mocking utilities
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- `responses` - HTTP mocking for integration tests
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- `flake8` - Linting
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- `black` - Code formatting
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- `mypy` - Type checking
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- `coverage` - Coverage reporting
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#### [.gitignore](.gitignore)
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Updated to exclude:
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- Test artifacts (`.pytest_cache/`, `htmlcov/`, `coverage.xml`)
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- Python cache files
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- Virtual environments
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- IDE configurations
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### 4. CI/CD Pipeline
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#### [.github/workflows/test.yml](.github/workflows/test.yml)
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Comprehensive GitHub Actions workflow with **5 jobs**:
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1. **Unit Tests**
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- Runs on Python 3.10, 3.11, 3.12 (matrix)
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- Executes unit tests with coverage
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- Uploads coverage to Codecov
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2. **Integration Tests**
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- Runs on Python 3.10, 3.11, 3.12 (matrix)
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- Executes integration tests
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- Uploads coverage to Codecov
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3. **Code Quality**
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- Flake8 linting (error detection + complexity)
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- Black formatting verification
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- Mypy type checking
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4. **Docker Build Test**
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- Builds Docker image
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- Verifies Python installation
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- Checks dependencies are installed
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5. **All Tests Pass**
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- Requires all previous jobs to succeed
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- Provides single status check for PRs
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### 5. Documentation
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#### [TESTING.md](TESTING.md)
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Comprehensive testing guide covering:
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- Test architecture explanation
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- Running tests locally (all, specific, by marker)
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- Coverage report generation
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- GitHub Actions CI/CD workflow details
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- Test coverage requirements (80% minimum)
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- Code quality standards
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- Writing new tests (templates provided)
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- Troubleshooting common issues
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- Best practices
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#### [README.md](README.md)
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Updated with:
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- Test status badge
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- Link to testing documentation
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## Test Statistics
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### Coverage Targets
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- **Minimum:** 80% code coverage
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- **Measured:** `bot.py` and `main.py`
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- **Excluded:** Test files, virtual environments
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### Test Count
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- **Unit Tests:** 20+ tests
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- **Integration Tests:** 10+ tests
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- **Total:** 30+ tests
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### Python Versions Tested
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- Python 3.10
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- Python 3.11
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- Python 3.12
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## Key Testing Features
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### Mocking Strategy
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- **Mastodon API:** Mocked using `unittest.mock` to avoid real API calls
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- **RSS Feeds:** Mocked using `responses` library with realistic XML
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- **File System:** Uses temporary files that are cleaned up automatically
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### Test Data
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- Realistic RSS 2.0 and Atom feed examples
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- Multiple entry scenarios (new, processed, malformed)
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- Error conditions (network failures, API errors, rate limits)
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### Continuous Integration
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- Runs on every push to `main`
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- Runs on all pull requests
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- Parallel test execution across Python versions
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- Automatic coverage reporting
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- Docker image validation
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## Running Tests
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### Locally
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```bash
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# Install dependencies
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pip install -r requirements-test.txt
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# Run all tests
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pytest
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# Run with coverage
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pytest --cov=bot --cov=main --cov-report=html
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# Run specific tests
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pytest test_bot.py # Unit tests only
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pytest test_integration.py # Integration tests only
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```
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### In CI/CD
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Tests run automatically via GitHub Actions:
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- **Trigger:** Push to main or pull request
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- **Duration:** ~5-10 minutes
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- **Matrix:** 3 Python versions × 2 test types = 6 parallel jobs
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- **Plus:** Code quality and Docker build validation
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## Benefits
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1. **Code Quality:** Ensures all changes are tested before merging
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2. **Regression Prevention:** Catches bugs before they reach production
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3. **Documentation:** Tests serve as executable documentation
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4. **Confidence:** Safe to refactor with comprehensive test coverage
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5. **Type Safety:** Mypy catches type-related bugs early
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6. **Code Style:** Black and flake8 enforce consistency
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## Future Enhancements
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Potential additions:
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- Performance/load testing
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- End-to-end tests with real Mastodon test instance
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- Security scanning (Bandit, Safety)
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- Mutation testing (mutmut)
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- Property-based testing (Hypothesis)
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- Contract testing for API interactions
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## Maintenance
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- **Add tests** for all new features
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- **Update tests** when changing behavior
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- **Keep coverage above 80%**
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- **Run tests before committing**
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- **Review test failures** in CI before merging
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