Pytest自动化测试框架深度指南

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"Python自动化框架Pytest文档详细介绍了如何从零开始使用Pytest，并逐步构建自己的测试框架。Pytest是一个强大的、灵活的Python测试工具，它简化了编写和执行测试用例的过程，提供了丰富的功能来支持测试驱动开发(TDD)和行为驱动开发(BDD)。" Pytest是一个广泛使用的Python自动化测试框架，它以其简洁的语法和高度可扩展性而受到开发者们的青睐。在"Start here"部分，初学者可以快速了解如何安装和运行Pytest的基本步骤，以便开始编写和执行测试。 "如何做指南"章节深入探讨了Pytest的多个关键特性。首先，"如何调用pytest"解释了如何运行测试以及如何指定测试路径。接着，"如何编写和报告断言"介绍了Pytest如何处理测试中的断言，使得测试结果更加清晰易读。"如何使用fixtures"这部分讲解了如何定义和使用fixture，它们是Pytest中用于创建和清理测试环境的关键工具。 "如何标记测试函数属性"部分说明了如何使用不同的标记(@pytest.mark.*)来控制测试行为，如选择性地运行或跳过测试。"如何参数化 fixtures 和测试函数"则展示了如何为测试提供不同输入，从而实现数据驱动测试。 "如何使用临时目录和文件"介绍了在测试中如何处理临时文件和目录，确保测试环境的隔离。"如何monkeypatch/模拟模块和环境"讲解了在测试中如何替换或模拟模块和对象的行为，以便隔离和测试特定功能。关于文档测试，"如何回滚doctests"这部分提供了指导，使得在文档字符串中嵌入的测试也能被正确执行。"如何重跑失败的测试"和"如何在测试运行之间保持状态"帮助开发者更有效地调试和修复问题。 "如何管理日志"、"如何捕获标准输出/错误"和"如何捕获警告"这些部分讲述了如何控制和检查测试过程中的输出信息。"如何使用skip和xfail处理不能成功通过的测试"则提供了处理预期失败和意外失败的方法。此外，Pytest的插件系统也是其强大之处，"如何安装和使用插件"以及"编写插件"章节详细阐述了如何利用和创建自定义插件来扩展Pytest的功能。"如何与现有的测试套件一起使用pytest"、"如何与基于unittest的测试一起使用pytest"、"如何运行nose编写的测试"等章节则帮助用户将Pytest无缝集成到现有项目中。最后，"如何实现xunit风格的设置"和"如何设置bash完成"提供了更多高级使用技巧，提升开发者的效率。

pytest Documentation, Release 6.3

(continued from previous page)

@pytest.fixture

def error_fixture():

> assert 0

E assert 0

test_example.py:6: AssertionError

================================= FAILURES =================================

________________________________ test_fail _________________________________

def test_fail():

> assert 0

E assert 0

test_example.py:14: AssertionError

========================= short test summary info ==========================

FAILED test_example.py::test_fail - assert 0

ERROR test_example.py::test_error - assert 0

Note: Calling pytest.main() will result in importing your tests and any modules that they import. Due to the

caching mechanism of python’s import system, making subsequent calls to pytest.main() from the same process

will not reﬂect changes to those ﬁles between the calls. For this reason, making multiple calls to pytest.main()

from the same process (in order to re-run tests, for example) is not recommended.

2.2 How to write and report assertions in tests

2.2.1 Asserting with the assert statement

pytest allows you to use the standard Python assert for verifying expectations and values in Python tests. For

example, you can write the following:

# content of test_assert1.py

def f():

return 3

def test_function():

assert f() == 4

to assert that your function returns a certain value. If this assertion fails you will see the return value of the function

call:

$ pytest test_assert1.py

=========================== test session starts ============================

platform linux -- Python 3.x.y, pytest-6.x.y, py-1.x.y, pluggy-0.x.y

cachedir: $PYTHON_PREFIX/.pytest_cache

rootdir: $REGENDOC_TMPDIR

collected 1 item

test_assert1.py F [100%]

(continues on next page)

12 Chapter 2. How-to guides

pytest Documentation, Release 6.3

(continued from previous page)

================================= FAILURES =================================

______________________________ test_function _______________________________

def test_function():

> assert f() == 4

E assert 3 == 4

E + where 3 = f()

test_assert1.py:6: AssertionError

========================= short test summary info ==========================

FAILED test_assert1.py::test_function - assert 3 == 4

============================ 1 failed in 0.12s =============================

pytest has support for showing the values of the most common subexpressions including calls, attributes, compar-

isons, and binary and unary operators. (See Demo of Python failure reports with pytest). This allows you to use the

idiomatic python constructs without boilerplate code while not losing introspection information.

However, if you specify a message with the assertion like this:

assert a % 2 == 0, "value was odd, should be even"

then no assertion introspection takes places at all and the message will be simply shown in the traceback.

See Assertion introspection details for more information on assertion introspection.

2.2.2 Assertions about expected exceptions

In order to write assertions about raised exceptions, you can use pytest.raises() as a context manager like this:

import pytest

def test_zero_division():

with pytest.raises(ZeroDivisionError):

1 / 0

and if you need to have access to the actual exception info you may use:

def test_recursion_depth():

with pytest.raises(RuntimeError) as excinfo:

def f():

f()

assert "maximum recursion" in str(excinfo.value)

excinfo is an ExceptionInfo instance, which is a wrapper around the actual exception raised. The main at-

tributes of interest are .type, .value and .traceback.

You can pass a match keyword parameter to the context-manager to test that a regular expression matches on the string

representation of an exception (similar to the TestCase.assertRaisesRegex method from unittest):

import pytest

(continues on next page)

2.2. How to write and report assertions in tests 13

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