Lightweight Decorator to cache (memoize) function calls and replay responses for expensive computations and API requests.
Pip installable via
pip install functionfaker
Functionfaker offers lightweight and easy to understand function (and method) caching, similar to some of the functionality of the Joblib package. A function response is recorded once and then replayed from cache from thereon. This allows for unit testing applications with API calls without actaully calling the API. It can also speed up prototyping of computationally expensive code. Functionfaker consists of simple code, and provides a single decorator for your functions and methods, as shown in the following "hello world" example.
from functionfaker import response_player import os
response_player decorator to an example function called
@response_player() def add(x, y): return x + y
Then set RECORD mode by setting the environment variable:
# enter record mode, to record function responses. os.environ['RECORD'] = "record"
add function a few times:
# Clear the stored function responses if os.path.exists('responses.p'): os.remove('responses.p') # call the add function to record some responses. add(1,2) add(1,y=3) add(1,3) add(2,1)
Recording response function "add" Recording response function "add" Recording response function "add"
replay mode via the environment variable:
# enter replay mode, so that function will not run, but return stored values instead. os.environ['RECORD'] = "replay"
add function again, with arguments that it has already seen:
result = add(1,2) print("The saved result of adding 1 and 2 using function 'add' is %d"%result)
Faking function "add". Response found The saved result of adding 1 and 2 using function 'add' is 3
The outputs for these inputs (1,2) are now read from cache.
Some funtion arguments might be irrelevant or difficult to serialize. To ignore these arguments, provide the
args2ignore argument as a list of integers to the
response_player decorator, where the integers represent the index in the argument list.
Default function response storage is in a simple Pickle file
responses.p. To use your own storage system, provide a class derived from
BaseStore class with an
get_response method. An object of this class is then provided as the
store argument to the