Metadata-Version: 2.1
Name: aiomemoizeconcurrent
Version: 0.0.6
Summary: Memoize concurrent asyncio Python function calls
Home-page: https://github.com/michalc/aiomemoizeconcurrent
Author: Michal Charemza
Author-email: michal@charemza.name
License: UNKNOWN
Description: # aiomemoizeconcurrent [![CircleCI](https://circleci.com/gh/michalc/aiomemoizeconcurrent.svg?style=svg)](https://circleci.com/gh/michalc/aiomemoizeconcurrent) [![Test Coverage](https://api.codeclimate.com/v1/badges/5e70552f9dd435a18326/test_coverage)](https://codeclimate.com/github/michalc/aiomemoizeconcurrent/test_coverage)
        
        Memoize concurrent asyncio Python coroutine calls. This offers short-lived memoization: for any given set of arguments, the cache lasts only for the length of a single call.
        
        
        ## Installation
        
        ```base
        pip install aiomemoizeconcurrent
        ```
        
        ## Usage
        
        For a coroutine whose arguments are hashable, you can create a _memoized_ version by passing it to `memoize_concurrent`. Any concurrent calls to this version that have the same arguments will result in only a _single_ run of original coroutine. 
        
        For example, creating 3 concurrent invocations of a coroutine where 2 of them have identical arguments
        
        ```python
        import asyncio
        from aiomemoizeconcurrent import memoize_concurrent
        
        async def main():
            memoized_coro = memoize_concurrent(coro)
        
            results = await asyncio.gather(*[
                memoized_coro('a'),
                memoized_coro('a'),
                memoized_coro('b'),
            ])
            print(results)
        
            await memoized_coro('a')
        
        async def coro(value):
            print('Inside coro', value)
            await asyncio.sleep(1)
            return value
        
        loop = asyncio.get_event_loop()
        loop.run_until_complete(main())
        loop.close()
        ```
        
        will only run `coro` twice, as shown by the output
        
        ```
        Inside coro a
        Inside coro b
        ['a', 'a', 'b']
        ```
        
        
        ## Use cases
        
        This can be used to memoize a function making calls to an API, and especially if
        
        - you expect many concurrent calls;
        - identical concurrent calls are idempotent;
        - there are enough such calls that are identical to justify such a caching layer.
        
        It can also be used to avoid concurrency edge cases/race conditions with multiple tasks accessing shared resources. For example, multiple tasks may need to dynamically create shared UDP sockets. To ensure that this dynamic generation isn't called by multiple tasks at the same time for the same address, it can be wrapped with `memoize_concurrent`.
        
        The function `memoize_concurrent` works with both coroutines, and functions that return a future.
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Framework :: AsyncIO
Requires-Python: ~=3.5
Description-Content-Type: text/markdown
