Improve test coverage from 38% to 53% with comprehensive unit tests

[Copilot]

This PR significantly improves the project's test coverage by adding comprehensive unit tests for critical modules, increasing overall coverage from 38% to 53% (a 15 percentage point improvement).

Key Improvements

Coverage Achievements

• utils.py: 98% coverage (up from 61%)
• configuration.py: 100% coverage (up from 86%)
• model.py: 100% coverage (up from 83%)
• action/utils.py: 98% coverage (up from 64%)
• API models: 100% coverage across all model files
• job/model.py: 100% coverage

New Test Files Added

• tests/ktoolbox/test_utils.py - 20 tests covering utility functions, URL parsing, logger initialization, and external link extraction
• tests/ktoolbox/test_configuration.py - 21 tests covering configuration validation, bucket path validation, and settings management
• tests/ktoolbox/test_model.py - 13 tests covering base data models and search result serialization
• tests/ktoolbox/test_api_models.py - 24 tests covering API data models for posts, creators, attachments, and announcements
• tests/ktoolbox/test_action_utils.py - 32 tests covering post filtering, path generation, keyword matching, and date handling

Test Quality Features

Fast and Reliable

All new tests use mocking to avoid external dependencies, ensuring they run quickly and reliably in CI environments without network calls.

Comprehensive Edge Case Coverage

Tests cover various scenarios including:

• Invalid configuration values and validation errors
• Empty/null data handling
• Date parsing and formatting edge cases
• URL parsing for different services and revision URLs
• Keyword filtering with case-insensitive matching
• File path generation with custom formatting

Error Handling

Tests verify proper error handling for:

• Invalid format strings in configuration
• Missing required fields in models
• Malformed URLs and data
• System exits on configuration errors

Impact

This improvement establishes a solid foundation for future development by ensuring core functionality is well-tested. The tests focus on business logic, utility functions, and data models that are critical to the application's reliability.

The increased coverage helps catch regressions early and provides confidence when refactoring or adding new features. All tests are designed to be maintainable and follow consistent patterns established in the existing test suite.

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