thornfield 1.5.1

Advanced caching in python

thornfield: Advanced caching in python

Installation

pip install thornfield

Usage

Choose the cache storage you want to use - in-memory, redis and postgresql are currently implemented. You can use a different storage by implementing the Cache interface.

Then, use the cached decorator to annotate the function being cached:

cacher = Cacher(cache_factory_func)

@cacher.cached
def foo():
    ...

The decorator supports:

• Setting an expiration time for the cached values.
• Caching only values that match a constraint (e.g. not None).
• Using only some of the function parameters as keys for the cache.
• Caching async functions.

Caching only some parameters

In case you don't want to use all the parameters of the function as cache key, you can the Cached or NotCached types:

from thornfield.typing import Cached, NotCached

@cached
def request(url: str, token: str, timeout: NotCached[int]):
    ...


@cached
async def request_async(url: Cached[str], timeout: int, callback):
    ...

Caching abstract methods

In order to avoid adding the same decorator to all implementations of an abstract method, you can use cache_method as follows:

class Base(ABC):
    def __init__(self):
        cacher.cache_method(do_something)

    @abstractmethod
    def do_something(self):
        pass

Cache Factories

In the cache_factories package you can find cache factories for Redis and PostgreSQL. They both cache each function to a different table (in PostgreSQL, db in Redis).

Their create method can be passed as cache_impl to the constructor of Cacher.