Multi-Layer Caching Service

This repository provides a flexible and robust Multi-Layer Caching solution built for Django. It is designed to significantly reduce latency and load on backend services by sequentially checking multiple, increasingly persistent cache layers before resorting to the original data source (e.g., a database or external API).

The entire system, including the caching services (Memcached and Redis), is fully Dockerized for easy setup and deployment.

---

Features

• Configurable multi-layer caching
• Pluggable fetch function for any API or data source
• Per-layer TTLs
• Dockerized with Redis and Memcached
• Layer order can be changed via .env
• New cache layers can be added

Requirements

• Python 3.10+
• Django 4+
• Docker
• Docker Compose

Setup

1. Clone the repository

git clone <repo_url>
cd <repo_folder>

2. Create a .env file

sample .env file:

# ----------------------------------------------------------------------
# CACHE LAYER CONFIGURATION
# ----------------------------------------------------------------------

# Define the order of cache layers, separated by commas.
# The system checks the layers in the order specified here.
# Available layers: inapp, memcache, redis
CACHE_LAYERS=inapp,memcache,redis

# ----------------------------------------------------------------------
# TIME-TO-LIVE (TTL) IN SECONDS
# ----------------------------------------------------------------------

# Define how long (in seconds) data should persist in each layer.
# Note: Typically, the layers further down the hierarchy (Redis/Memcached) 
# have longer TTLs than the local In-Memory cache (InApp).

INAPP_TTL=10
MEMCACHE_TTL=30
REDIS_TTL=60

# ----------------------------------------------------------------------
# APPLICATION/API CONFIGURATION
# ----------------------------------------------------------------------

# This URL is used by the fetch function to retrieve the actual data 
# when a cache miss occurs across all layers.
API_URL_TO_CACHE=[https://get.taaghche.com/v2/book/](https://get.taaghche.com/v2/book/)

# ----------------------------------------------------------------------
# SERVICE CONNECTION CONFIGURATION (Defined in docker-compose.yml)
# ----------------------------------------------------------------------

REDIS_URL=redis://redis:6379/1

MEMCACHE_HOST=memcached
MEMCACHE_PORT=11211

Adjust TTLs, layer order, and API url as needed.

3. Install Python requirements (for local development)

pip install -r requirements.txt

4. Run with Docker Compose

docker-compose build
docker-compose up

Starts Django, Redis, and Memcached containers. Restart containers to apply .env changes:

docker-compose down
docker-compose up

Customization

• Add new layers: Create a class inheriting CacheBase and implement get and set.
• Change layer order: Edit CACHE_LAYERS in .env.
• Adjust TTLs: Edit INAPP_TTL, MEMCACHE_TTL, REDIS_TTL in .env.
• Use any API: Provide a custom fetch function in build_cache_manager(fetch_func).