[PYTHON] pytest usage summary

I had rarely written ** "test code" ** until now, but I had the opportunity to write python test code and learned how to use it in a hurry. In this article, I've focused on how to use pytest, a framework for unit testing python.

Reference: Official documentation (https://docs.pytest.org/en/latest/contents.html)

What is pytest

A framework for unit testing in python. There is a similar one called unittest, but pytest seems to be more popular. The following are the features of pytest

--Detailed information when the test fails --Automatically discover modules and functions to be tested --By using the fixture function, you can pre-process tests such as mocking. (See below) --Compliant with unittest

Installation

pip install -U pytest

Easy to use

Simple unit test

Basically, you can run the test as follows.

--Write the test case with ʻassert --Runpytest`

If you enter the file name and method name in test_ *, the test code will be found automatically (you can specify it yourself).

test_sample.py

def func(x):
    return x + 1

def test_answer():
    assert func(3) == 5

Create the above test_sample.py file and Run pytest.

Then, the following test result is displayed.

========================================== test session starts ===========================================
platform darwin -- Python 3.7.6, pytest-5.4.3, py-1.8.1, pluggy-0.13.1
rootdir: /Users/xin/work/study/pytest
plugins: hypothesis-5.5.4, arraydiff-0.3, remotedata-0.3.2, openfiles-0.4.0, doctestplus-0.5.0, astropy-header-0.1.2
collected 1 item                                                                                         

test_sample.py F                                                                                   [100%]

================================================ FAILURES ================================================
______________________________________________ test_answer _______________________________________________

    def test_answer():
>       assert func(3) == 5
E       assert 4 == 5
E        +  where 4 = func(3)

test_sample.py:5: AssertionError
======================================== short test summary info =========================================
FAILED test_sample.py::test_answer - assert 4 == 5
=========================================== 1 failed in 0.18s ============================================

Exception handling test

Exception testing is possible with pytest.raises

error_sample.py

import pytest

def f():
    raise SystemExit(1)

def test_mytest():
    with pytest.raises(SystemExit):
        f()

Running multiple tests in a class

By creating a class with Test as a prefix, you can test the internal test methods at the same time.

test_class.py

class TestClass:
    def test_one(self):
        x = "this"
        assert "h" in x

    def test_two(self):
        x = "hello"
        assert hasattr(x, "check")

fixture

What is a fixture?

A tool provided to set up the test execution environment. I will pick up some useful ones. See below for details (https://docs.pytest.org/en/latest/fixture.html)

tmpdir The tmpdir fixture allows you to create a unique directory that is temporarily available during testing.

test_tempdir.py

import os

def test_create_file(tmpdir):
    p = tmpdir.mkdir("sub").join("hello.txt") #Creating a temporary directory
    p.write("content")
    assert p.read() == "content"
    assert len(tmpdir.listdir()) == 1
    assert 0

monkeypatch The monkeypatch fixture allows you to mock an object. For example, suppose you have the following product code, and one get_value () is a function that cannot be easily executed.

monkeypatch_product.py

def return_value(): #Product code
    a = get_value()
    return a

def get_value(): #Functions that cannot be easily executed
    return 1

At this time, you can execute the test by replacing get_value () with your own mock function by using monkeypatch.setattr.

monkeypatch_test.py

import monkeypatch_product

#Test code
def test_return_value(monkeypatch):
    def mock_get_value():
        return 100

    #Replaced with mock function
    monkeypatch.setattr(monkeypatch_product, "get_value", mock_get_value)
    res = monkeypatch_product.return_value()
    assert res == 100

You can also mock environment variables with monkeypatch.setenv.

monkeypatch_env.py

import os

#Product code
def get_os_user_lower():
    username = os.getenv("USER")

    if username is None:
        raise OSError("USER environment is not set.")

    return username.lower()

#Test code
def test_get_os_user_lower(monkeypatch):
    monkeypatch.setenv("USER", "TestingUser")
    assert get_os_user_lower() == "testinguser"