python-cache-service

A lightweight, namespaced caching service using Redis.
Supports fast prototyping and production-ready use, with built-in support for Redis and fakeredis for tests.

🚀 Features

• 🔑 Namespaced keys to avoid collisions
• ⏳ Optional TTL for cache expiration
• 🧪 fakeredis support for seamless unit testing
• 🧩 Decorator to cache function results transparently
• 🧼 Cache clearing by namespace

📦 Installation

pip install python-cache-service

Usage

from cache.domain.factories.cache_service_factory import CacheServiceFactory

cache = CacheServiceFactory.create(namespace="my_app")

# Store a value
cache.set("my_key", {"data": 123}, ttl_seconds=3600)

# Retrieve a value
value = cache.get("my_key")

# Delete a value
cache.delete("my_key")

# Clear all keys in the namespace
cache.clear()

Configuration

You can configure the cache service by setting environment variables:

• REDIS_HOST=localhost
• REDIS_PORT=6379
• REDIS_DB=0

🧪 Using in tests

from cache.domain.factories.cache_service_factory import CacheServiceFactory

cache = CacheServiceFactory.createTest()

cache.set("test_key", [1, 2, 3])
assert cache.get("test_key") == [1, 2, 3]

You can also disable caching entirely in test mode:

from cache.domain.factories.cache_service_factory import CacheServiceFactory
cache = CacheServiceFactory.createTest(disabled=True)

🎯 Using the @cache_result decorator

from cache.decorators.cache_result import cache_result
from cache.domain.factories.cache_service_factory import CacheServiceFactory

cache = CacheServiceFactory.create(namespace="my_app")

@cache_result(cache, ttl_seconds=120, key_prefix="my_func", verbose=True)
def heavy_computation(x, y):
    return x + y

# First call: computed and cached
heavy_computation(2, 3)

# Second call: cache hit
heavy_computation(2, 3)

🧾 License

This project is licensed under the MIT License - see the LICENSE file for details.