Introduction to Pytest: Basics, Advanced Techniques, and Extensions

All theory is for practice, so we start with a simple example: create a test file # pytest test_sample.py def inc(x): return x + 1 def test_answer(): assert inc(3) == 5 and run it with # pytest test_sample.py . The test fails because the assertion is wrong, demonstrating Pytest's basic rule that test modules and functions must be prefixed with test_ and use assert for verification.

Pytest also supports exception handling using with pytest.raises(...) :

<code># -*- coding:utf-8 -*-
# @Time   : 2021-09-05
# @Author : Carl_DJ

import pytest

def f():
    raise SystemExit(1)

def test_mytest():
    # 捕获异常
    with pytest.raises(SystemExit):
        f()
</code>

Test classes can be used to group tests, following the same test_ naming convention:

<code># -*- coding:utf-8 -*-
# @Time   : 2021-09-05
# @Author : Carl_DJ

class TestClass:
    # test_开头
    def test_one(self):
        x = "this"
        assert "h" in x
    # test_开头
    def test_two(self):
        x = "hello"
        assert hasattr(x, "check")
</code>

Running pytest in a directory containing multiple test scripts automatically discovers and executes all tests, enabling a "lazy" mode for batch testing.

Advanced techniques include parameterization, which allows a single test function to run with multiple inputs:

<code># 使用parametrize对测试用例参数化
@pytest.mark.parametrize("test_input,expected", [
    ("3+5", 8),
    ("'2'+'4'", "24"),
    ("6*9", 54)
])
def test_eval_1(test_input, expected):
    assert eval(test_input) == expected
</code>

Marks act as tags to include or exclude tests. For example, a slow test can be marked and later run or skipped via pytest.ini configuration:

<code># 标签
@pytest.mark.slow
def test_mark():
    print("test mark")
    time.sleep(10)
    assert 5 == 5
</code>

<code>[pytest]
markers =
    slow: marks tests as slow (deselect with '-m "not slow"')
</code>

Running only fast tests: pytest test_sample.py -m "not slow" ; running only slow tests: pytest -m slow .

Fixtures provide reusable setup/teardown logic, similar to unittest but more powerful, and can be nested:

<code># -*- coding:utf-8 -*-
# @Time   : 2021-09-05
# @Author : Carl_DJ

import pytest

@pytest.fixture
def first_entry():
    return "a"

@pytest.fixture
def second_entry():
    return 2

@pytest.fixture
def order(first_entry, second_entry):
    return [first_entry, second_entry]

@pytest.fixture
def expected_list():
    return ["a", 2, 3.0]

def test_string(order, expected_list):
    order.append(3.0)
    # 断言
    assert order == expected_list
</code>

Fixtures can also manage resources such as database connections by defining them in conftest.py .

Pytest can be extended with plugins and hooks. Creating a directory a with conftest.py and test_sub.py allows custom behavior:

<code># 在目录a下创建conftest.py
def pytest_runtest_setup(item):
    # 在目录a下运行每个用例
    print("setting up", item)

# 在目录a下创建test_sub.py
def test_sub():
    pass
</code>

Running pytest a/test_sub.py --capture=no displays the custom hook output.

In summary, Pytest offers simple test discovery, powerful parameterization, marking, fixtures, configuration via pytest.ini , and extensibility through plugins and hooks, making it a versatile tool for Python testing.