"""
Triple Store Module

This module provides comprehensive triple store integration and management
for RDF data storage and querying, supporting multiple triple store backends
with unified interfaces.

Algorithms Used:

Triple Store Management:
    - Store Registration: Store type detection, adapter factory pattern, configuration management, default store selection
    - Adapter Pattern: Unified interface for multiple backends (Blazegraph, Jena, RDF4J, Virtuoso), adapter instantiation, backend-specific operation delegation
    - Store Selection: Default store resolution, store ID lookup, store validation

CRUD Operations:
    - Triple Addition: Single triple insertion, batch triple insertion, triple validation (subject/predicate/object checking, confidence validation), adapter delegation
    - Triple Retrieval: Pattern matching (subject/predicate/object filtering), SPARQL query construction, result binding extraction, triple reconstruction
    - Triple Deletion: Triple matching, deletion operation delegation, result verification
    - Triple Update: Delete-then-add pattern, atomic update operations, conflict detection

Bulk Loading:
    - Batch Processing: Chunking algorithm (fixed-size batch creation), batch size optimization, memory management for large datasets
    - Progress Tracking: Load progress calculation (loaded/total percentage), elapsed time tracking, estimated remaining time calculation (linear projection), throughput calculation (triples/second)
    - Retry Mechanism: Exponential backoff retry (delay = retry_delay * (attempt + 1)), max retry limit, error recovery, stop-on-error option
    - Stream Processing: Iterator-based stream processing, incremental batch collection, memory-efficient loading
    - Validation: Pre-load validation (empty component checking, URI validation, confidence checking), error/warning collection

SPARQL Query Execution:
    - Query Validation: Syntax validation (keyword checking, structure validation), query type detection (SELECT, ASK, CONSTRUCT, DESCRIBE, INSERT, DELETE)
    - Query Optimization: Whitespace normalization, LIMIT addition for SELECT queries, query rewriting, cost estimation
    - Query Planning: Execution step identification (SELECT projection, pattern matching, filtering, sorting, pagination), cost estimation (heuristic-based: COUNT multiplier, join count multiplier, DISTINCT multiplier)
    - Query Caching: Cache key generation (MD5 hash of normalized query), LRU-style cache eviction (oldest entry removal when cache full), cache hit/miss tracking, cache invalidation
    - Result Processing: Binding extraction, variable extraction, result formatting, metadata attachment

Query Optimization:
    - Cost Estimation: Heuristic-based cost calculation (base cost * complexity multipliers), COUNT query detection (2x multiplier), join count estimation (1 + join_count * 0.1 multiplier), DISTINCT detection (1.5x multiplier)
    - Execution Step Identification: Query parsing for step detection, step sequence construction, optimization opportunity detection
    - Query Rewriting: Whitespace normalization, LIMIT injection, query simplification

Store Adapters:
    - Blazegraph Adapter: HTTP-based SPARQL endpoint communication, namespace management, graph management, bulk load via INSERT DATA, authentication handling
    - Jena Adapter: rdflib integration, SPARQLStore for remote endpoints, in-memory graph support, model/dataset management, RDF serialization (Turtle, RDF/XML, N3), inference support
    - RDF4J Adapter: RDF4J repository connection, SPARQL endpoint communication, transaction support, bulk operations
    - Virtuoso Adapter: Virtuoso SPARQL endpoint communication, SQL/SPARQL hybrid queries, bulk loading, transaction support

Data Validation:
    - Triple Validation: Required field checking (subject, predicate, object), confidence range validation (0-1), URI format validation
    - Pre-load Validation: Empty component detection, URI format checking, confidence threshold checking, error/warning categorization

Performance Optimization:
    - Batch Size Optimization: Configurable batch size, memory-aware batching, throughput-based optimization
    - Connection Pooling: Adapter-level connection management, connection reuse, connection lifecycle management
    - Query Caching: Result caching for repeated queries, cache size management, cache hit optimization
    - Parallel Processing: Batch-level parallelization (when supported by adapter), concurrent batch processing

Key Features:
    - Multi-backend support (Blazegraph, Jena, RDF4J, Virtuoso)
    - CRUD operations for RDF triples
    - SPARQL query execution and optimization
    - Bulk data loading with progress tracking
    - Query caching and optimization
    - Transaction support
    - Store adapter pattern
    - Method registry for extensibility
    - Configuration management with environment variables and config files

Main Classes:
    - TripleManager: Main triple store management coordinator
    - QueryEngine: SPARQL query execution and optimization
    - BulkLoader: High-volume data loading
    - BlazegraphAdapter: Blazegraph integration adapter
    - JenaAdapter: Apache Jena integration adapter
    - RDF4JAdapter: Eclipse RDF4J integration adapter
    - VirtuosoAdapter: Virtuoso RDF store integration adapter
    - TripleStore: Triple store configuration dataclass
    - QueryResult: Query result representation dataclass
    - QueryPlan: Query execution plan dataclass
    - LoadProgress: Bulk loading progress dataclass

Convenience Functions:
    - register_store: Register triple store wrapper
    - add_triple: Add single triple wrapper
    - add_triples: Add multiple triples wrapper
    - get_triples: Get triples matching pattern wrapper
    - delete_triple: Delete triple wrapper
    - execute_query: Execute SPARQL query wrapper
    - optimize_query: Optimize SPARQL query wrapper
    - bulk_load: Bulk load triples wrapper
    - get_triple_store_method: Get triple store method by task and name
    - list_available_methods: List registered triple store methods

Example Usage:
    >>> from semantica.triple_store import TripleManager, register_store, add_triple, execute_query
    >>> # Using convenience functions
    >>> store = register_store("main", "blazegraph", "http://localhost:9999/blazegraph")
    >>> result = add_triple(triple, store_id="main")
    >>> query_result = execute_query(sparql_query, store_adapter)
    >>> # Using classes directly
    >>> manager = TripleManager()
    >>> store = manager.register_store("main", "blazegraph", "http://localhost:9999/blazegraph")
    >>> result = manager.add_triple(triple, store_id="main")
    >>> from semantica.triple_store import QueryEngine
    >>> engine = QueryEngine()
    >>> query_result = engine.execute_query(sparql_query, store_adapter)

Author: Semantica Contributors
License: MIT
"""

from .triple_manager import (
    TripleManager,
    TripleStore
)
from .blazegraph_adapter import (
    BlazegraphAdapter
)
from .jena_adapter import (
    JenaAdapter
)
from .rdf4j_adapter import (
    RDF4JAdapter
)
from .virtuoso_adapter import (
    VirtuosoAdapter
)
from .query_engine import (
    QueryEngine,
    QueryResult,
    QueryPlan
)
from .bulk_loader import (
    BulkLoader,
    LoadProgress
)
from .methods import (
    register_store,
    add_triple,
    add_triples,
    get_triples,
    delete_triple,
    update_triple,
    execute_query,
    optimize_query,
    plan_query,
    bulk_load,
    validate_triples,
    get_triple_store_method,
    list_available_methods,
)
from .config import (
    TripleStoreConfig,
    triple_store_config,
)
from .registry import (
    MethodRegistry,
    method_registry,
)

__all__ = [
    # Triple management
    "TripleManager",
    "TripleStore",
    
    # Store adapters
    "BlazegraphAdapter",
    "JenaAdapter",
    "RDF4JAdapter",
    "VirtuosoAdapter",
    
    # Query engine
    "QueryEngine",
    "QueryResult",
    "QueryPlan",
    
    # Bulk loading
    "BulkLoader",
    "LoadProgress",
    
    # Convenience functions
    "register_store",
    "add_triple",
    "add_triples",
    "get_triples",
    "delete_triple",
    "update_triple",
    "execute_query",
    "optimize_query",
    "plan_query",
    "bulk_load",
    "validate_triples",
    "get_triple_store_method",
    "list_available_methods",
    
    # Configuration and registry
    "TripleStoreConfig",
    "triple_store_config",
    "MethodRegistry",
    "method_registry",
]
