pytest和单元测试

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pytest 查找规则:

如果不带参数运行pytest，那么查找从testpaths(如果有)或者当前目录开始查找，否者，命令行参数就用于目录、文件查找。

• 递归遍历目录，除非目录指定了不同递归
• 文件名符合test__.py，__test.py
• Test开头的类，并且不能有init方法
• 对test_开头的函数和方法进行测试

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pytest assert方法

通常情况下使用assert语句就能对大多数测试进行断言。
对于异常断言，使用pytest.raises或@pytest.mark.xfail。

对于自定义类型的assert比较断言，使用pytest_assertrepr_compare注册比较断言函数

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pytest fixtures

pytest fixtures提供传统xUnit单元测试中setUp/tearDown的功能，但是比setUp/tearDown更强大(pytest也支持xUnit单元测试)。

• fixtures有名字，可以在测试函数、模块、类或整个工程中明确通过fixtures的名字调用fixtures
• fixtures以模块的方式实现，每个fixtures函数可以调用其他的fixtures
• fixtures可以通过参数或者配置进行复用

fixtures作为参数

# content of ./test_smtpsimple.py
import pytest

@pytest.fixture
def smtp():
    import smtplib
    return smtplib.SMTP("smtp.gmail.com")

def test_ehlo(smtp):
    response, msg = smtp.ehlo()
    assert response == 250
    assert 0 # for demo purposes

test_ehlo的参数smtp就是一个fixture，通过pytest.fixture装饰器定义。定义和使用fixtures的名字必须一样。这里smtp参数就是smtp fixture的返回值。

模块、类、会话级共享fixture

在pytest.fixture装饰器中添加参数scope能改变fixture的生存范围，如果scope='module'，那么fixture就是模块级的，这个fixture函数只会在每次相同模块加载的时候执行。这样就可以复用一些需要时间进行创建的对象。

根据pytest的规则，会在conftest.py文件中查找fixture，这样我们就可以把所有的fixtures放到一个文件中。

Fixtures执行tearDown代码

 # content of conftest.py

import smtplib
import pytest

@pytest.fixture(scope="module")
def smtp(request):
    smtp = smtplib.SMTP("smtp.gmail.com")
    def fin():
        print ("teardown smtp")
        smtp.close()
    request.addfinalizer(fin)
    return smtp  # provide the fixture value

与测试互操作

# content of conftest.py
import pytest
import smtplib

@pytest.fixture(scope="module")
def smtp(request):
    server = getattr(request.module, "smtpserver", "smtp.gmail.com")
    smtp = smtplib.SMTP(server)

    def fin():
        print ("finalizing %s (%s)" % (smtp, server))
        smtp.close()
    request.addfinalizer(fin)
    return smtp

fixture有一个参数request，这个例子通过request取得了模块中的smtpserver变量，还可以通过request取得function, class or module context

参数化fixtures

request不仅能获取测试中的量，还可以为通过request参数话fixtures

# content of conftest.py
import pytest
import smtplib

@pytest.fixture(scope="module",
                params=["smtp.gmail.com", "mail.python.org"])
def smtp(request):
    smtp = smtplib.SMTP(request.param)
    def fin():
        print ("finalizing %s" % smtp)
        smtp.close()
    request.addfinalizer(fin)
    return smtp

本例会创建两个smtp fixtures，它们的不同处在于request.param。每个使用smtp fixture的测试函数都会执行两次，对应不同的param。

通过fixtures对测试进行分组

Autouse fixtures (xUnit setup on steroids)

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参数化fixtures和测试函数

pytest支持fixtures和测试函数的参数化

• fixtures通过pytest.fixture 的 params参数，这个fixture也可以参数化测试函数（只要fixture直接返回request.param）
• 测试函数通过@pytest.mark.parametrize装饰器参数化
• pytest_generate_tests

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Example

• Demo of Python failure reports with pytest
• Basic patterns and examples
  • Pass different values to a test function, depending on command line options
  • Dynamically adding command line options
  • Control skipping of tests according to command line option
  • Writing well integrated assertion helpers
  • Detect if running from within a pytest run
  • Adding info to test report header
  • profiling test duration
  • incremental testing - test steps
  • Package/Directory-level fixtures (setups)
  • post-process test reports / failures
  • Making test result information available in fixtures
  • Integrating pytest runner and cx_freeze
• Parametrizing tests
  • Generating parameters combinations, depending on command line
  • Different options for test IDs
  • A quick port of “testscenarios”
  • Deferring the setup of parametrized resources
  • Apply indirect on particular arguments
  • Parametrizing test methods through per-class configuration
  • Indirect parametrization with multiple fixtures
  • Indirect parametrization of optional implementations/imports
• Working with custom markers
  • Marking test functions and selecting them for a run
  • Selecting tests based on their node ID
  • Using -k expr to select tests based on their name
  • Registering markers
  • Marking whole classes or modules
  • Marking individual tests when using parametrize
  • Custom marker and command line option to control test runs
  • Reading markers which were set from multiple places
  • marking platform specific tests with pytest
  • Automatically adding markers based on test names
• A session-fixture which can look at all collected tests
• Changing standard (Python) test discovery
  • Ignore paths during test collection
  • Changing directory recursion
  • Changing naming conventions
  • Interpreting cmdline arguments as Python packages
  • Finding out what is collected
  • customizing test collection to find all .py files
• Working with non-python tests
  • A basic example for specifying tests in Yaml files

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Mock

Mocking in Python: A Guide to Better Unit Tests
Mock docs