Configuration Management
Overview
The config.py module implements a robust configuration management system using Pydantic for validation and YAML for storage. It provides a centralized, type-safe configuration with environment variable overrides and dynamic reloading capabilities.
Key Features
Type-Safe Configuration
-
Pydantic Integration
- Strong type validation with custom model classes
- Automatic type coercion for settings values
- Schema validation with frozen models
- Custom validators support for complex types
- LRU caching for performance optimization
-
Configuration Inheritance
- Base settings models with FrozenModel
- Specialized settings classes (AppSettings, LoggingSettings)
- Immutable configuration objects with frozen=True
- Hierarchical settings structure
Multiple Configuration Sources
-
YAML Configuration Files
- Human-readable format with comments
- Hierarchical structure for complex settings
- Comments support for documentation
- Multiple environment configurations
- Automatic file modification detection
- Support for large configuration files
-
Environment Variables
- Override any setting using APP_ prefix
- Nested setting support using double underscores
- Automatic type conversion for values
- Example:
APP_LOGGING__LEVEL=DEBUG - Case-insensitive matching
-
Runtime Updates
- Dynamic configuration reloading with reload()
- File modification detection with _needs_reload
- LRU cache management for settings
- Thread-safe operations for concurrent access
- Singleton pattern implementation
Advanced Features
-
Performance Optimizations
- LRU caching for frequently accessed settings
- Efficient nested setting access
- Lazy loading of configuration
- Buffered file operations
-
Error Handling
- Validation for missing config files
- YAML format verification
- Type validation for all settings
- Default value support
- Clear error messages