71-redis-caching

71 - Redis Caching & Invalidation API

What It Does

Demonstrates advanced server-side caching using Redis to dramatically speed up repeated API queries. When a client requests data, the server first checks Redis. If a cached result exists (cache HIT), it returns instantly. If not (cache MISS), it simulates a slow database query, stores the result in Redis with a TTL, and returns it. Write operations (POST) automatically invalidate the relevant cache keys.

Project Structure

71-redis-caching/
  main.py            # FastAPI entry point with cached endpoints
  database.py        # Simulated slow database layer
  redis_client.py    # Redis connection and cache helper functions
  config.py          # Configuration constants (TTL, Redis URL)
  requirements.txt   # Dependencies
  index.html         # Unified frontend dashboard
  README.md          # This file

Setup and Run

Prerequisites

• Redis server running locally on port 6379 (default)

1. Install dependencies

pip install -r requirements.txt

2. Start Redis (if not running)

redis-server

3. Start the FastAPI server

uvicorn main:app --reload

4. Open the Frontend

Open index.html in your browser to test cached vs uncached queries.

Example Output

// First request (CACHE MISS) - takes ~2 seconds
{
  "source": "database",
  "response_time_ms": 2003,
  "data": [
    {"id": 1, "name": "Laptop", "price": 999.99},
    {"id": 2, "name": "Phone", "price": 699.99}
  ]
}

// Second request (CACHE HIT) - returns instantly
{
  "source": "redis_cache",
  "response_time_ms": 2,
  "data": [
    {"id": 1, "name": "Laptop", "price": 999.99},
    {"id": 2, "name": "Phone", "price": 699.99}
  ]
}

Core Concepts

• Cache-Aside Pattern: Application checks cache before querying the database.
• TTL (Time-To-Live): Cached data automatically expires after a configurable duration.
• Cache Invalidation: Write operations flush stale cache keys to maintain data consistency.
• Serialization: Python dicts are serialized to JSON strings for Redis storage.