"""
Cache package for MCP Server.
Provides comprehensive caching functionality with multiple backends,
query result caching, and intelligent invalidation strategies.
Example usage:
from mcp_server.cache import CacheManagerFactory, QueryResultCache, QueryCacheConfig
# Create a memory cache
cache_manager = CacheManagerFactory.create_memory_cache()
await cache_manager.initialize()
# Create query cache
query_config = QueryCacheConfig(enabled=True, default_ttl=600)
query_cache = QueryResultCache(cache_manager, query_config)
# Use in application
result = await query_cache.get_cached_result(QueryType.SEARCH, q="test")
"""
from .backends import (
CacheBackend,
CacheEntry,
HybridCacheBackend,
MemoryCacheBackend,
RedisCacheBackend,
)
from .cache_manager import (
CacheBackendType,
CacheConfig,
CacheManager,
CacheManagerFactory,
CacheMetrics,
ICacheManager,
)
from .query_cache import (
CachedQuery,
InvalidationStrategy,
QueryCacheConfig,
QueryCacheDecorator,
QueryResultCache,
QueryType,
cache_file_symbols,
cache_project_status,
cache_search,
cache_semantic_search,
cache_symbol_lookup,
)
__all__ = [
# Backend classes
"CacheBackend",
"MemoryCacheBackend",
"RedisCacheBackend",
"HybridCacheBackend",
"CacheEntry",
# Cache manager
"ICacheManager",
"CacheManager",
"CacheManagerFactory",
"CacheConfig",
"CacheBackendType",
"CacheMetrics",
# Query cache
"QueryResultCache",
"QueryCacheConfig",
"QueryType",
"InvalidationStrategy",
"CachedQuery",
"QueryCacheDecorator",
"cache_symbol_lookup",
"cache_search",
"cache_semantic_search",
"cache_file_symbols",
"cache_project_status",
]
__version__ = "1.0.0"
