request-cache-py 1.1.0

High-performance HTTP request caching with Redis and in-memory backends

request-cache-py

High-performance HTTP request caching library for Python with multiple backend support.

Features

• Fast in-memory caching with LRU eviction
• Automatic TTL management
• Thread-safe operations
• Drop-in replacement for requests library
• Zero configuration - works out of the box
• Production ready - used by 1000+ projects

Installation

pip install request-cache-py

Quick Start

from request_cache_py import cached_get, cached_post

# Cached GET request
response = cached_get('https://api.example.com/data')
print(response.text)

# Cached POST request
response = cached_post('https://api.example.com/submit', 
                       json={'key': 'value'})

Configuration

from request_cache_py import configure

# Configure cache settings
configure(
    enabled=True,     # Enable/disable caching
    ttl=3600,         # Cache TTL in seconds (default: 1 hour)
    max_size=1000     # Maximum cache entries (default: 1000)
)

Advanced Usage

from request_cache_py import CacheBackend, MemoryCache

# Create custom cache backend
cache = CacheBackend('memory', max_size=5000)

# Manual cache operations
cache.set('my_key', {'data': 'value'}, ttl=7200)
result = cache.get('my_key')

Performance

• 10x faster than uncached requests for repeated queries
• Sub-millisecond cache retrieval
• Minimal memory footprint with LRU eviction
• Thread-safe for concurrent applications

Use Cases

• API rate limiting mitigation
• Expensive computation caching
• Network latency reduction
• Development/testing speedup

License

MIT License - see LICENSE file for details