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YokedCache - Python Caching Library for FastAPI

High-Performance Redis Caching with Auto-Invalidation for Modern Python Applications

YokedCache is a powerful, async-first Python caching library that brings enterprise-grade Redis caching capabilities to FastAPI applications. With multi-backend support, intelligent auto-invalidation, and production-ready monitoring, it's designed to scale from development to enterprise deployment.

Why Choose YokedCache for Python FastAPI Development?

  • 🚀 Performance: Async-first design with Redis connection pooling and batch operations
  • 🔧 Flexible: Multiple backends (Memory, Redis, Memcached) with unified Python API
  • 🧠 Intelligent: Auto-invalidation, vector search caching, and fuzzy matching
  • 📊 Observable: Built-in metrics, monitoring, and comprehensive CLI tools
  • 🛡️ Production-Ready: Health checks, error handling, and security features
  • 🔐 Resilient: Circuit breaker, retry logic, and graceful fallbacks (v0.2.1)
  • ⚡ Enhanced: Smart async/sync context handling and performance optimizations (v0.2.1)

Quick Start - Python FastAPI Redis Caching

# Install with all features
pip install yokedcache[full]

from fastapi import FastAPI, Depends
from yokedcache import YokedCache, cached_dependency

app = FastAPI()
cache = YokedCache()  # Uses Redis by default

# Cache database dependencies automatically
cached_get_db = cached_dependency(get_db, cache=cache, ttl=300)

@app.get("/users/{user_id}")
async def get_user(user_id: int, db=Depends(cached_get_db)):
    # Database queries are automatically cached and invalidated
    return db.query(User).filter(User.id == user_id).first()

Documentation Guide

📚 Start Here

Perfect for newcomers and quick setups:

💻 Usage Guide

Learn different ways to use YokedCache:

🔍 Advanced Features

Powerful capabilities for complex use cases:

📖 Reference

Detailed technical documentation:

Key Features

Multi-Backend Architecture

Switch between backends without changing your code: - Memory: Fast in-memory caching with LRU eviction - Redis: Distributed caching with clustering and persistence - Memcached: Lightweight distributed caching

Intelligent Caching

  • Auto-Invalidation: Automatically invalidate cache on database writes
  • Tag-Based Grouping: Group related cache entries for bulk operations
  • Pattern Matching: Wildcard-based key operations and cleanup
  • TTL with Jitter: Prevent thundering herd problems
  • Vector Similarity: Semantic search using TF-IDF and multiple distance metrics
  • Fuzzy Matching: Find approximate matches across cached keys
  • Real-time Indexing: Automatic search index maintenance

Production Features

  • Metrics & Monitoring: Prometheus, StatsD, and custom collectors
  • Health Checks: Monitor cache and backend health
  • Security: TLS support, input validation, and access controls
  • CLI Tools: Comprehensive command-line interface

Installation Options

# Basic installation
pip install yokedcache

# Full installation (recommended)
pip install yokedcache[full]

# Specific features
pip install yokedcache[vector]      # Vector search
pip install yokedcache[monitoring]  # Prometheus & StatsD
pip install yokedcache[memcached]   # Memcached backend
pip install yokedcache[fuzzy]       # Fuzzy search

What's New in 0.2.0

  • 🆕 Multi-Backend Support: Memory, Redis, and Memcached backends
  • 🔍 Vector Search: Semantic similarity search capabilities
  • 📊 Production Monitoring: Prometheus and StatsD integration
  • 🛠️ Enhanced CLI: CSV export, file output, and improved UX
  • ✅ Comprehensive Testing: 200+ tests with complete coverage

Ready to get started? Begin with our Getting Started Guide for a step-by-step introduction.