Performance optimizations for Neo4j server info caching

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Description

Following the code review for PR #57, implement performance optimizations for Neo4j server information retrieval, particularly caching mechanisms to avoid repeated server queries.

Current Behavior

The get_server_info() method in Neo4jManager currently executes a CALL dbms.components() query every time it's called, which can impact performance when called frequently during health checks or diagnostics.

Proposed Improvements

1. Server Info Caching

• Cache server information after first successful retrieval
• Use configurable TTL (time-to-live) for cache entries
• Implement cache invalidation strategies

2. Intelligent Cache Management

class Neo4jManager:
    def __init__(self, ...):
        self._server_info_cache = None
        self._server_info_cache_time = None
        self._server_info_cache_ttl = 300  # 5 minutes default
    
    def get_server_info(self, use_cache: bool = True, cache_ttl: int = None):
        # Check cache validity and return cached info if available
        # Otherwise fetch fresh info and update cache

3. Configuration Options

• Configurable cache TTL through constructor or environment variables
• Option to disable caching entirely for real-time scenarios
• Cache warming during connection establishment

4. Memory Management

• Implement cache size limits
• LRU eviction for multiple server connections
• Memory-efficient storage of server info

Technical Implementation

Cache Strategy

• TTL-based expiration: Default 5-minute TTL, configurable
• Lazy loading: Cache populated on first access
• Thread-safe: Use appropriate locking for concurrent access
• Memory efficient: Store only essential server information

Configuration

# Constructor options
Neo4jManager(
    server_info_cache_ttl=300,  # seconds
    enable_server_info_cache=True
)

# Environment variables
NEO4J_SERVER_INFO_CACHE_TTL=300
NEO4J_ENABLE_SERVER_INFO_CACHE=true

Health Check Integration

• Health checks should optionally use cached server info
• Provide option for health checks to force fresh server info retrieval
• Balance between performance and accuracy

Performance Benefits

• Reduced query load on Neo4j server
• Faster health check execution
• Lower network overhead for repeated diagnostics
• Improved application responsiveness

Backward Compatibility

• All changes should be backward compatible
• Default behavior maintains current functionality
• New caching features are optional and configurable

Acceptance Criteria

• Server info caching with configurable TTL
• Thread-safe cache implementation
• Memory management with size limits
• Configuration through constructor and environment variables
• Integration with health check system
• Performance benchmarks showing improvement
• Comprehensive unit tests for cache behavior
• Documentation of caching behavior and configuration

Future Considerations

• Extend caching to other expensive queries
• Implement distributed caching for multi-instance deployments
• Add cache metrics and monitoring
• Consider cache warming strategies

This optimization will improve overall application performance while maintaining the reliability of server diagnostics.

Generated following code review feedback for PR #57.