onecache 0.8.1

Python cache for sync and async code

OneCache

Python cache for sync and async code.

Cache uses an LRU algorithm and can optionally set TTLs per entry.

Tested automatically on CPython 3.8–3.14 and PyPy 3.9 across Linux, macOS, and Windows (see the workflow badge). Earlier versions may work but are not part of the supported matrix.

Usage

from onecache import CacheDecorator
from onecache import AsyncCacheDecorator


class Counter:
    def __init__(self, count=0):
        self.count = count


@pytest.mark.asyncio
async def test_async_cache_counter():
    """Test async cache, counter case."""
    counter = Counter()

    @AsyncCacheDecorator()
    async def mycoro(counter: Counter):
        counter.count += 1
        return counter.count

    assert 1 == (await mycoro(counter))
    assert 1 == (await mycoro(counter))


def test_cache_counter():
    """Test async cache, counter case."""
    counter = Counter()

    @CacheDecorator()
    def sample(counter: Counter):
        counter.count += 1
        return counter.count

    assert 1 == (sample(counter))
    assert 1 == (sample(counter))

Decorator classes supports the following arguments

• maxsize (int): Maximun number of items to be cached. default: 512
• ttl (int): time to expire in milliseconds, if None, it does not expire. default: None
• skip_args (bool): apply cache as the function doesn't have any arguments, default: False
• cache_class (class): Class to use for cache instance. default: LRUCache
• refresh_ttl (bool): if cache with ttl, This flag makes key expiration timestamp to be refresh per access. default: False
• thread_safe (bool): tell decorator to use thread safe lock. default=False
• max_mem_size (int): max mem size in bytes. Ceil for sum of cache values sizes. default=None which means no limit. For pypy this value is ignored as the objects can change by the JIT compilation.

If num of records exceds maxsize, it drops the oldest.

Development

Install dependencies with Poetry (includes dev + test groups):

poetry install --with test,dev

Run the test suite and coverage locally:

poetry run pytest --cov

Lint and format checks:

poetry run flake8
poetry run autopep8 --in-place --recursive onecache tests

Contribute

1. Fork
2. create a branch feature/your_feature
3. commit - push - pull request

Thanks :)