Files
markitect-main/markitect/plugins/decorators.py
tegwick b0de32d083 feat: implement comprehensive plugin architecture and extensions system (issue #19)
Complete plugin system implementation providing extensible architecture for MarkiTect:

🏗️ **Core Plugin Architecture**:
- BasePlugin abstract class with lifecycle management (initialize/cleanup)
- Specialized plugin types: ProcessorPlugin, FormatterPlugin, ValidatorPlugin, ExporterPlugin, CommandPlugin
- PluginMetadata system with version, dependencies, and type information
- Plugin initialization and configuration validation

🔍 **Plugin Discovery & Management**:
- PluginManager with automatic discovery from built-in modules and directories
- PluginRegistry for centralized plugin registration and lifecycle management
- Support for plugin loading, unloading, and reloading with configuration
- Plugin discovery from multiple sources (built-in, directories, packages)

🛠️ **CLI Integration**:
- markitect plugin-list: List all available plugins with metadata
- markitect plugin-load: Load plugins with optional configuration
- markitect plugin-unload: Unload plugins and cleanup resources
- markitect plugin-info: Show detailed plugin information
- markitect plugin-discover: Discover and refresh plugin catalog

📦 **Built-in Plugins**:
- JSON/YAML/Table formatters for output formatting
- Markdown/Text processors for content processing
- Auto-registered via @register_plugin decorator
- Comprehensive configuration options

🔧 **Developer Experience**:
- @register_plugin decorator for easy plugin registration
- Plugin configuration validation and error handling
- Comprehensive API documentation with examples
- Plugin development guide and best practices

📋 **Example Plugins**:
- Advanced text processor with case conversion and pattern replacement
- XML/CSV formatters demonstrating custom output formats
- Complete examples showing plugin development patterns

🧪 **Test Coverage**:
- 59 comprehensive tests covering all plugin functionality
- Tests for plugin lifecycle, registration, discovery, and CLI integration
- Error handling and edge case coverage
- Built-in plugin validation

Technical Implementation:
- Plugin types: processor, formatter, validator, exporter, generator, importer, transformer, extension, backend, command
- Configuration-driven plugin management with YAML/JSON support
- Graceful error handling and plugin isolation
- Plugin dependency validation and compatibility checking

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-10-03 11:23:32 +02:00

31 lines
749 B
Python

"""
Decorators for plugin registration and management.
This module provides convenient decorators for registering plugins.
"""
from typing import Type, Optional
from .registry import plugin_registry
from .base import BasePlugin
def register_plugin(name: Optional[str] = None):
"""
Decorator to register a plugin class.
Args:
name: Optional plugin name (uses class name if not provided)
Returns:
Decorator function
Example:
@register_plugin("my_processor")
class MyProcessor(ProcessorPlugin):
pass
"""
def decorator(plugin_class: Type[BasePlugin]) -> Type[BasePlugin]:
plugin_registry.register(plugin_class, name)
return plugin_class
return decorator