pytest入门与高级用法指南

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pytest是一款强大的Python测试框架，旨在提供一个简洁、灵活且易于使用的接口来编写单元测试和集成测试。本文档是pytest的0.1版官方文档，由Holger Krekel撰写，他是一名培训师和顾问，链接为<https://merlinux.eu/>，发布日期为2023年2月22日。以下是文档中涵盖的主要知识点： 1. **入门指南** - 学习如何快速上手pytest，包括安装和基本的测试结构设置。 2. **命令行使用指南** - 如何正确地调用pytest，包括理解命令选项和配置文件的使用。 3. **测试编写与断言** - 介绍如何编写和报告测试中的断言，确保代码的预期行为得到验证。 4. **fixture使用** - 解释fixture（固定设置）的作用，如何创建和管理共享资源，如数据准备和清理。 5. **标记与参数化** - 学习如何使用标记来组织和分类测试，以及参数化功能，以处理多态测试用例。 6. **临时目录和文件操作** - 如何在测试中创建和管理临时文件和目录，以模拟真实环境。 7. **模块和环境模拟** - 使用monkeypatch或mock工具来替换模块的行为，以便隔离和控制测试环境。 8. **文档测试** - 包括如何编写和执行文档字符串测试，即doctests。 9. **重试失败测试和状态管理** - 教授如何处理测试失败时的重试策略，以及在测试运行之间保持数据一致性。 10. **日志管理** - 如何控制和记录测试过程中的日志信息，便于调试和监控。 11. **控制输出捕获** - 学习如何捕获标准输出和错误，以及处理输出流的控制。 12. **警告处理** - 掌握如何处理和控制测试过程中产生的警告信息。 13. **跳过和预期失败** - 了解skip和xfail标记的作用，以及何时使用它们来标记不能或不应该通过的测试。 14. **插件安装与使用** - 安装第三方插件以增强pytest的功能，并学习如何自定义插件开发。 15. **插件编写** - 提供插件开发的基础知识，包括编写hook函数和其他核心组件。 16. **与现有测试套件集成** - 如何将pytest与现有的unittest或其他测试框架集成。 17. **unittest风格测试** - 包含了将unittest测试转换为pytest风格的指导。 18. **nose兼容性** - 如何运行专为nose设计的测试用例，确保向后兼容性。 19. **XUnit-style setup** - 设计和实现符合XUnit测试架构的测试集初始化。 20. **Bash自动补全** - 教授如何配置bash环境，以便更方便地使用pytest。这个文档详尽地覆盖了pytest从基础到进阶的各个方面，无论是初次接触还是经验丰富的开发者，都能从中找到所需的信息来提高测试质量和效率。

pytest Documentation, Release 0.1

will not re󰝙ect changes to those 󰝘les 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-7.x.y, pluggy-1.x.y

rootdir: /home/sweet/project

collected 1 item

test_assert1.py F [100%]

================================= 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, comparisons,

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.

12 Chapter 2. How-to guides

pytest Documentation, Release 0.1

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 attributes

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

def myfunc():

raise ValueError("Exception 123 raised")

def test_match():

with pytest.raises(ValueError, match=r".* 123 .*"):

myfunc()

The regexp parameter of the match method is matched with the re.search function, so in the above example

match='123' would have worked as well.

There’s an alternate form of the pytest.raises() function where you pass a function that will be executed with the

given *args and **kwargs and assert that the given exception is raised:

pytest.raises(ExpectedException, func, *args, **kwargs)

The reporter will provide you with helpful output in case of failures such as no exception or wrong exception.

Note that it is also possible to specify a “raises” argument to pytest.mark.xfail, which checks that the test is

failing in a more speci󰝘c way than just having any exception raised:

@pytest.mark.xfail(raises=IndexError)

def test_f():

f()

Using pytest.raises() is likely to be better for cases where you are testing exceptions your own code is delib-

erately raising, whereas using @pytest.mark.xfail with a check function is probably better for something like

documenting un󰝘xed bugs (where the test describes what “should” happen) or bugs in dependencies.

2.2. How to write and report assertions in tests 13

pytest Documentation, Release 0.1

(continued from previous page)

f2 = Foo(2)

> assert f1 == f2

E assert Comparing Foo instances:

E vals: 1 != 2

test_foocompare.py:12: AssertionError

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

FAILED test_foocompare.py::test_compare - assert Comparing Foo instances:

1 failed in 0.12s

2.2.6 Assertion introspection details

Reporting details about a failing assertion is achieved by rewriting assert statements before they are run. Rewritten assert

statements put introspection information into the assertion failure message. pytest only rewrites test modules directly

discovered by its test collection process, so asserts in supporting modules which are not themselves test modules will

not be rewritten.

You can manually enable assertion rewriting for an imported module by calling register_assert_rewrite before you import

it (a good place to do that is in your root conftest.py).

For further information, Benjamin Peterson wrote up Behind the scenes of pytest’s new assertion rewriting.

Assertion rewriting caches les on disk

pytest will write back the rewritten modules to disk for caching. You can disable this behavior (for example to avoid

leaving stale .pyc 󰝘les around in projects that move 󰝘les around a lot) by adding this to the top of your conftest.py

󰝘le:

import sys

sys.dont_write_bytecode = True

Note that you still get the bene󰝘ts of assertion introspection, the only change is that the .pyc 󰝘les won’t be cached on

disk.

Additionally, rewriting will silently skip caching if it cannot write new .pyc 󰝘les, i.e. in a read-only 󰝘lesystem or a

zip󰝘le.

Disabling assert rewriting

pytest rewrites test modules on import by using an import hook to write new pyc 󰝘les. Most of the time this works

transparently. However, if you are working with the import machinery yourself, the import hook may interfere.

If this is the case you have two options:

• Disable rewriting for a speci󰝘c module by adding the string PYTEST_DONT_REWRITE to its docstring.

• Disable rewriting for all modules by using --assert=plain.

16 Chapter 2. How-to guides

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