FastAPI-DynCache 🚀

A FastAPI-based application with dynamic caching support using Memcached.
This project allows enabling/disabling caching dynamically using environment variables, improving API performance and flexibility.

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📌 Features

✅ Dynamic Caching – Enable/Disable caching via .env configuration
✅ Memcached Integration – Uses Memcached for efficient request caching
✅ Custom Decorator (@cache_if_enabled) – Simplifies caching in endpoints
✅ Environment-Controlled Initialization – Prevents unnecessary cache setup
✅ Manual Cache Clearing Support

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🛠️ Installation

1️⃣ Clone the Repository

git clone https://github.com/your-username/FastAPI-DynCache.git
cd FastAPI-DynCache

2️⃣ Create & Activate Virtual Environment

python -m venv venv
source venv/bin/activate  # On macOS/Linux
venv\Scripts\activate     # On Windows

3️⃣ Install Dependencies

pip install -r requirements.txt

4️⃣ Start Memcached

Using Docker (Recommended)

docker run -d --name memcached -p 11211:11211 memcached

Without Docker (Native Installation)

• Ubuntu: sudo apt install memcached
• Mac (Homebrew): brew install memcached
• Windows: Use Memurai or Docker.

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⚙️ Configuration (.env File)

Create a .env file in the project root:

ENABLE_CACHE=True
MEMCACHED_HOST=localhost
MEMCACHED_PORT=11211

• Set ENABLE_CACHE=False to disable caching dynamically.

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🚀 Running the Application

uvicorn main:app --reload

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📌 API Endpoints

Method	Endpoint	Description
GET	/nocache	Returns a response without caching
GET	/cache	Returns a cached response (if enabled)
GET	/custom/{item_id}	Caches response per item_id
GET	/clear-cache	Clears the cache manually

🛠️ Testing API

curl http://127.0.0.1:8000/cache

• First call takes ~2s (Simulated expensive computation).
• Subsequent calls return instantly (cached for 10s).

curl http://127.0.0.1:8000/clear-cache

• Clears the cache.

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🛠️ Code Overview

🔹 Project Structure

FastAPI-DynCache/
│── main.py         # FastAPI app & endpoints
│── caching.py      # Cache initialization & custom decorators
│── config.py       # Environment-based configuration
│── .env            # Environment variables
│── requirements.txt # Dependencies

🔹 Caching Initialization (caching.py)

from fastapi_cache2 import FastAPICache
from fastapi_cache2.backends.memcached import MemcachedBackend
from pymemcache.client.base import Client as MemcacheClient
from fastapi_cache2.decorator import cache
from config import settings
import functools

def init_cache():
    """Initialize Memcached if caching is enabled."""
    if settings.ENABLE_CACHE:
        memcached_client = MemcacheClient((settings.MEMCACHED_HOST, settings.MEMCACHED_PORT))
        FastAPICache.init(MemcachedBackend(memcached_client), prefix="fastapi-cache")
    else:
        print("⚠️ Caching is DISABLED.")

def cache_if_enabled(expire: int):
    """Decorator to apply caching only when enabled."""
    def decorator(func):
        if settings.ENABLE_CACHE:
            return cache(expire=expire)(func)
        return functools.wraps(func)(func)  # Return the original function if caching is disabled
    return decorator

🔹 Usage in main.py

from fastapi import FastAPI
import time
from caching import init_cache, cache_if_enabled

app = FastAPI()

@app.on_event("startup")
def startup():
    init_cache()

@app.get("/cache")
@cache_if_enabled(expire=10)
async def cached_endpoint():
    time.sleep(2)
    return {"message": "Cached response", "timestamp": time.time()}

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📌 Best Practices

✅ Use environment variables for flexible caching control
✅ Avoid stale data – Set cache expiration (expire=10)
✅ Use Memcached for high-speed caching
✅ Manual cache clearing for better control

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📜 License

This project is open-source under the MIT License.

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👨‍💻 Contributing

Pull requests are welcome! Feel free to contribute by:

• Adding new features
• Fixing bugs
• Improving documentation