Skip to main content
Donate to the Python Software Foundation or Purchase a PyCharm License to Benefit the PSF! Donate Now

Function Faker

Project description

functionfaker

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

Add the response_player decorator to an example function called add:

@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"

Call the 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"

Set replay mode via the environment variable:

# enter replay mode, so that function will not run, but return stored values instead.
os.environ['RECORD'] = "replay"

Call the 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 update and get_response method. An object of this class is then provided as the store argument to the response_player decorator.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Filename, size & hash SHA256 hash help File type Python version Upload date
functionfaker-0.2.tar.gz (4.4 kB) Copy SHA256 hash SHA256 Source None

Supported by

Elastic Elastic Search Pingdom Pingdom Monitoring Google Google BigQuery Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN SignalFx SignalFx Supporter DigiCert DigiCert EV certificate StatusPage StatusPage Status page