aiocache
multi backend asyncio cache
Decision gist · record as of 2026-08-14
Yes. aiocache is actively maintained, has no install friction, and provides a clean abstraction over multiple cache backends—valuable for async Python applications that may need to scale from development to production. The main caveat is the unclear license status; verify the actual license before committing to production use. No known vulnerabilities.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Optional backends (Redis, memcached) need separate installation via pip install aiocache[redis] or aiocache[memcached].
- Low install friction with no runtime dependencies.
- Actively maintained with recent commits and 1437 repository stars.
License · maintenance · safety
(unclear) — License status is unclear—no SPDX identifier or raw license text is available in the package metadata. Verify the actual license before using in proprietary or restricted contexts.
last release 2024-09-25 (688 days) · last repo commit 2026-06-28 · 1,437 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 8,847,386 downloads/mo, #1,587 on PyPI
Alternatives
Verify before relying
import asyncio
from aiocache import Cache
async def example():
cache = Cache(Cache.MEMORY)
await cache.set('key', 'value')
result = await cache.get('key')
print(result) # 'value'
asyncio.run(example())- Whether the package is licensed under an open-source or proprietary license (metadata shows no license declaration).
- Performance characteristics and typical throughput for each backend type.
- Whether serializers (PickleSerializer, JsonSerializer, MsgPackSerializer) are included by default or require extra dependencies.
- Minimum Python version requirement (classifiers list 3.7 through 3.11 but requires_python is unspecified).
What it is and what it does
aiocache is an asyncio caching library that abstracts over multiple backend storage systems—in-memory, Redis, and memcached—behind a single, consistent API. It lets you cache the results of async functions and manage key-value data without rewriting code when you switch backends. The library includes decorators for transparent caching, serializers to handle Python objects, and a plugin system for hooks like timing and hit-miss tracking.
You can use it as a simple in-process cache for development, swap to Redis or memcached for production, and configure everything through a unified interface. It has no runtime dependencies by default; optional backends require their respective client libraries installed separately.
Use it for
- Cache results of expensive async database queries in a web framework.
- Store serialized Python objects in Redis for sharing cached state across multiple processes.
- Decorate async functions with @cached to automatically memoize results with configurable TTL and namespacing.
- Switch from in-memory caching during development to memcached in production without changing application code.
- Implement multi-key operations (multi_get, multi_set) to batch cache reads and writes efficiently.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
aiocache is actively maintained, has no install friction, and provides a clean abstraction over multiple cache backends—valuable for async Python applications that may need to scale from development to production. The main caveat is the unclear license status; verify the actual license before committing to production use. No known vulnerabilities.
Install
aiocache on PyPI
Before you install
Low install friction with no runtime dependencies. Actively maintained with recent commits and 1437 repository stars. Supports Python 3.7 through 3.11.
Optional backends (Redis, memcached) need separate installation via pip install aiocache[redis] or aiocache[memcached].
License in practice
License status is unclear—no SPDX identifier or raw license text is available in the package metadata. Verify the actual license before using in proprietary or restricted contexts.
Quickstart
import asyncio
from aiocache import Cache
async def example():
cache = Cache(Cache.MEMORY)
await cache.set('key', 'value')
result = await cache.get('key')
print(result) # 'value'
asyncio.run(example())Verify before relying
- Whether the package is licensed under an open-source or proprietary license (metadata shows no license declaration).
- Performance characteristics and typical throughput for each backend type.
- Whether serializers (PickleSerializer, JsonSerializer, MsgPackSerializer) are included by default or require extra dependencies.
- Minimum Python version requirement (classifiers list 3.7 through 3.11 but requires_python is unspecified).
Package facts
| License | Not declared unclear |
| Python support | Not specified |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | None |
| Maintenance | Actively maintained 688 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 8,847,386 / month, #1,587 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Framework :: AsyncIOProgramming Language :: PythonProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.7Programming Language :: Python :: 3.8Programming Language :: Python :: 3.9 |
Evidence: aiocache-0.12.3-py2.py3-none-any.whl
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See also aiomcache · cachelib · cashews · fastapi-cache2 · python-redis-cache · django-redis · python-memcached · pylibmc · django-cache-url · py-key-value-aio