AutoFake

A Python Library for Mocking Functions in Testing

AutoFake is a Python library that makes it easy to mock functions in your tests. It allows you to run your code normally and records the calls and returns of specified functions. The results are then stored in a backend. During testing, you can reproduce the results of these functions instead of executing their actual implementation, which is useful for isolating the code you are testing and avoiding external dependencies, side effects, and long-running functions. AutoFake is also well-suited for adding tests to legacy code and refactoring (it works well with ApprovalTesting)

Getting Started

Installation

To install AutoFake, simply run:

pip install autofake

Usage

Here's an example of how to use AutoFake:

# example.py

import smtplib
import time

import requests

from autofake import FakeIt, PickleBackend

fakeit = FakeIt(backend=PickleBackend("output.pickle"))


# Mocking external services
@fakeit
def get_data(payload):
    return requests.get("https://www.example.com/data", params=payload).json()


# Avoiding side effects
@fakeit
def send_email(to, subject, message):
    server = smtplib.SMTP("smtp.gmail.com", 587)
    server.ehlo()
    server.starttls()
    server.ehlo()
    server.login("[email protected]", "password")
    message = f"Subject: {subject}\n\n{message}"
    server.sendmail("[email protected]", to, message)
    server.quit()


# As a cache for long running functions
@fakeit
def long_running_process(duration, n):
    time.sleep(duration)
    return n

To record the function calls, parameters, and results, run:

AUTOFAKE=RECORD python example.py

This will run the functions normally and store the results in the output.pickle file.

To fake the functions, run:

AUTOFAKE=FAKE python example.py

This time, the decorated functions will not be executed but their return values (if any) will be retrieved from the backend.

The FakeIt Object

The FakeIt class is the main class in AutoFake and can be initialized with a mode and a backend.

Modes

You can run your code in three modes:

• PRODUCTION mode: the function will be executed normally without any action (this is the default behavior).

• RECORD mode: the function will be executed normally and the call, arguments, and result will be recorded in the backend.

• FAKE mode: the function will not be executed, and its recorded result will be retrieved from the backend for the given arguments.

You can either set the mode when instantiating the FakeIt class by passing the argument mode, or by setting an environment variable AUTOFAKE to one of PRODUCTION, RECORD or FAKE.

Backends

The backend determines where the calls, parameters and returns values are stored. Different backends are provided such as PickleBackend and JSONBackend. Pass the backend as an argument to the FakeIt Initialization.

Decorating functions

To use FakeIt, you have to wrap the functions you want to fake with a FakeIt decorator. This decorator accepts a name, which is used to store the results of the function call with the given name.

Contributing

To contribute to AutoFake, simply fork the repository and create a pull request with your changes.

License

AutoFake is licensed under the MIT License. See the LICENSE file for more information.