Implement 5 Critical Improvements: Logging, Cache Expiration Fix, Management Functions, Type Hints, and Flexible Decorator

[Copilot]

This PR addresses critical production issues and adds essential features to make cachecade more robust, maintainable, and flexible. After analyzing the codebase, I identified and implemented the top 5 improvements needed for production readiness.

🔧 1. Proper Logging System (Critical Production Fix)

Replaced all print() statements with a structured logging system:

# Before: Hard-coded print statements
print("Using Redis for caching.")
print(f"Using cached data for {func.__name__} from {cache_backend}.")

# After: Configurable logging with appropriate levels
logger.info("Using Redis for caching.")
logger.debug(f"Using cached data for {func.__name__} from {cache_backend}.")

• Added configurable log levels (DEBUG for cache hits, INFO for initialization, WARNING/ERROR for issues)
• Proper logger configuration with formatters
• Production-ready logging that can be controlled by applications

🐛 2. Fixed Critical Cache Expiration Bug

Major Bug Fix: Replit and memory backends were never actually expiring entries, causing indefinite cache growth:

# Before: Expired entries remained in cache indefinitely
cache_entry = get_cache_entry(cache_key)
if cache_entry:
    timestamp, data = json.loads(cache_entry)
    if (time.time() - timestamp) < ttl:
        return jsonify(data)
    # BUG: Expired entries were never removed!

# After: Proper cleanup of expired entries
if cache_entry:
    try:
        timestamp, data = json.loads(cache_entry)
        if (time.time() - timestamp) < ttl:
            return jsonify(data)
        else:
            # Remove expired entries for non-Redis backends
            if cache_backend == 'replit' and replit_db:
                del replit_db[cache_key]
            elif cache_backend == 'memory':
                memory_store.pop(cache_key, None)

⚡ 3. Essential Cache Management Functions

Added missing cache invalidation and clearing capabilities:

import cachecade

# Clear all cache entries
cachecade.clear_cache()

# Clear entries matching a pattern
cachecade.clear_cache(pattern="user_data_*")

# Invalidate a specific cached function call
cachecade.invalidate_cache_key('get_user_profile', (user_id,), {'include_settings': True})

• Full backend support (Redis with SCAN, Replit iteration, Memory filtering)
• Pattern-based clearing for selective cache management
• Added to public API for easy access

📝 4. Complete Type Annotations

Added comprehensive type hints throughout the codebase for better developer experience:

# Before: No type information
def generate_cache_key(func_name, args, kwargs):
def init_cache(storage_engines=None, prefix=None):

# After: Full type annotations
def generate_cache_key(func_name: str, args: Tuple[Any, ...], kwargs: Dict[str, Any]) -> str:
def init_cache(storage_engines: Optional[List[str]] = None, prefix: Optional[str] = None) -> None:

• Improved IDE support with IntelliSense/autocompletion
• Better static type checking capability
• Enhanced code documentation through types

🔄 5. Flexible Decorator (Removes Flask Hard Dependency)

Added return_json parameter to make the decorator usable outside Flask applications:

# Flask applications (existing behavior)
@cachecaded(ttl=300)  # return_json=True by default
def get_api_data():
    return {"data": "value"}  # Returns Flask Response object

# Non-Flask applications (new capability)
@cachecaded(ttl=300, return_json=False)
def compute_expensive_calculation():
    return {"result": 42}  # Returns raw dict, no Flask dependency

• Enables use in pure Python applications, CLI tools, etc.
• Maintains 100% backward compatibility
• Reduces coupling with Flask framework

🧪 Testing & Verification

• ✅ All 11 existing tests continue to pass
• ✅ Added 3 comprehensive test cases covering new functionality
• ✅ Created demo script showcasing all improvements
• ✅ Verified logging at different levels and cache expiration behavior

📊 Impact Summary

These changes transform cachecade from a basic caching decorator into a production-ready library:

1. Production Ready: Proper logging replaces debug print statements
2. Bug-Free: Fixed cache expiration that wasn't working for 2/3 backends
3. Feature Complete: Essential cache management operations now available
4. Developer Friendly: Type hints dramatically improve development experience
5. More Flexible: Can be used in any Python application, not just Flask

Breaking Changes: None - all changes are fully backward compatible.

Files Changed: 3 files, +250 lines, -28 lines of more robust, well-typed code.

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