Pytest04-编写测试函数

目录

• 4.编写测试函数
  • 4.1 使用assert声明
  • 4.2 预期异常
  • 4.3 测试函数标记
  • 4.4 跳过测试
  • 4.5 标记预期失败的测试
  • 4.6 运行测试子集
    • 4.6.1 单个目录
    • 4.6.2 单个测试文件/模块
    • 4.6.3 单个测试函数
    • 4.6.4 单个测试类
    • 4.6.5 单个测试类中的测试方法
    • 4.6.6 用测试名划分测试集合
  • 4.7 参数化测试
    • 4.7.1 参数化方式
    • 4.7.2 添加额外参数ids

4.编写测试函数

4.1 使用assert声明

    使用pytest编写测试时，若须要传递测试失败信息，能够直接使用Pytho自带的assert关键字。pytest与其余测试框架如unittest的区别以下所示：

pytest	unittest
assert something	assertTrue(something)
assert a==b	assertEqual(a,b)
assert a<=b	assertLessEqual(a,b)
...	...

    pytest中assert主要有如下特色

• 1.assert 后面能够添加任何表达式，若表达式的结果经过bool转换结果为True，则表明测试经过
• 2.pytest 能够重写assert关键字。pytest可截断对原生assert的调用，替换为pytest定义的assert，从而提供更多的详细失败信息

import pytest

def addItemToList(item):
    tmpList=[]
    tmpList.append(item)
    return tmpList


def test_addItemToList():
    t1=addItemToList("a")
    t2=addItemToList("b")
    assert t1==t2

运行结果以下所示：

PS C:\Users\Surpass\Documents\PycharmProjects\PytestStudy\Lesson02> pytest .\test_01.py
=============================test session starts ====================================
platform win32 -- Python 3.7.6, pytest-5.4.2, py-1.8.1, pluggy-0.13.1
rootdir: C:\Users\Surpass\Documents\PycharmProjects\PytestStudy\Lesson02
collected 1 item

test_01.py F                                                                [100%]

================================== FAILURES ======================================
___________________________test_addItemToList ____________________________________

    def test_addItemToList():
        t1=addItemToList("a")
        t2=addItemToList("b")
>       assert t1==t2
E       AssertionError: assert ['a'] == ['b']
E         At index 0 diff: 'a' != 'b'
E         Use -v to get the full diff

test_01.py:12: AssertionError
=================================== short test summary info =========================
FAILED test_01.py::test_addItemToList - AssertionError: assert ['a'] == ['b']
====================================1 failed in 0.29s ==============================

    在上面的运行结果中，失败的测试用例在行首会有一个 > 来标识。以E开头的行是pytest提供的额外断定信息，用于帮助了解异常的具体信息。

4.2 预期异常

    在Python后来的版本，增长了函数参数注解功能，即在定义一个参数后，后面可直接声明参数的数据类型，方便其余人员知道如何调用这个函数，以下所示：

def add(x:int,y:int)->int:
    return x+y

    为确保像这样的函数，在发生类型错误时，能够抛出异常，可使用with pytest.raises(< expected exception >)，以下所示：

def add(x:int,y:int)->int:
    if not isinstance(x,(int,)) or not isinstance(y,(int,)):
        raise TypeError("args must be int")
    else:
        return x+y

def test_add():
    with pytest.raises(TypeError):
        add("1","2")

运行结果以下所示：

PS C:\Users\Surpass\Documents\PycharmProjects\PytestStudy\Lesson02> pytest .\test_01.py
==============================test session starts ================================
platform win32 -- Python 3.7.6, pytest-5.4.2, py-1.8.1, pluggy-0.13.1
rootdir: C:\Users\Surpass\Documents\PycharmProjects\PytestStudy\Lesson02
collected 1 item

test_01.py .                                                              [100%]

=================================1 passed in 0.08s ===============================

    测试用例中test_add()有with pytest.raises(TypeError)声明，则意味着不管with中的内容是什么，都至少会产生TypeError异常。若是测试经过，则说明确实发生了预期的TypeError异常，若是抛出的是其余类型的异常，则与预期不一致，测试失败。

    在上面的测试用例中，仅检验了传参数据的类型异常，也能够检查值异常，好比在检验一个参数的数据类型以后，也能够再检验其内容，为校验异常消息是否符合预期，能够增长as exInfo语句获得异常消息的值，再进行校验，示例以下所示：

def add(x:int,y:int,operator:str)->int:
    if not isinstance(x,(int,)) or not isinstance(y,(int,)) or not isinstance(operator,(str,)):
        raise TypeError("args must be int")
    if operator=="+":
        return x + y
    elif operator=="-":
        return x - y
    else:
        raise ValueError("operator must be '+' or '-' ")

def test_add():
    with pytest.raises(ValueError) as exInfo:
        add(1,2,"*")
    exInfo=exInfo.value.args[0]
    expectInfo="operator must be '+' or '-' "
    assert expectInfo== exInfo

运行结果以下所示：

PS C:\Users\Surpass\Documents\PycharmProjects\PytestStudy\Lesson02> pytest .\test_01.py
=============================test session starts ============================
platform win32 -- Python 3.7.6, pytest-5.4.2, py-1.8.1, pluggy-0.13.1
rootdir: C:\Users\Surpass\Documents\PycharmProjects\PytestStudy\Lesson02
collected 1 item

test_01.py .                                                      [100%]

============================1 passed in 0.13s ================================

4.3 测试函数标记

    pytest提供了标记机制，容许使用marker对测试函数进行标记，一个测试函数能够有多个marker，一个marker也能够用来标记多个测试函数。

对测试函数进行标记，一般使用的场景为冒烟测试，通常状况下冒烟测试不须要跑所有的测试用例，只须要选择关键的点进行测试，这个时候只跑被标记为冒烟测试的测试用例，会省不少时间。

    示例以下所示：

import pytest

def add(x:int,y:int,operator:str)->int:
    if not isinstance(x,(int,)) or not isinstance(y,(int,)) or not isinstance(operator,(str,)):
        raise TypeError("args must be int")
    if operator=="+":
        return x + y
    elif operator=="-":
        return x - y
    else:
        raise ValueError("operator must be '+' or '-' ")

@pytest.mark.testValueError
@pytest.mark.smoke
def test_addValueError():
    with pytest.raises(ValueError) as exInfo:
        add(1,2,"*")
    exInfo=exInfo.value.args[0]
    expectInfo="operator must be '+' or '-' "
    assert expectInfo== exInfo

@pytest.mark.testTypeErrorTest
@pytest.mark.smoke
def test_addTypeError():
    with pytest.raises(TypeError):
        add("1","2","+")

    如今只须要在命令中指定-m markerName，就能够运行指定的测试用例，以下所示：

PS C:\Users\Surpass\Documents\PycharmProjects\PytestStudy\Lesson02> pytest -m smoke .\test_02.py
=========================test session starts ===============================
platform win32 -- Python 3.7.6, pytest-5.4.2, py-1.8.1, pluggy-0.13.1
rootdir: C:\Users\Surpass\Documents\PycharmProjects\PytestStudy\Lesson02
collected 2 items

test_02.py ..                                                                       [100%]
============================ 2 passed, 4 warnings in 0.12s ====================================

PS C:\Users\Surpass\Documents\PycharmProjects\PytestStudy\Lesson02> pytest -m testValueError .\test_02.py
==============================test session starts ==============================================
platform win32 -- Python 3.7.6, pytest-5.4.2, py-1.8.1, pluggy-0.13.1
rootdir: C:\Users\Surpass\Documents\PycharmProjects\PytestStudy\Lesson02
collected 2 items / 1 deselected / 1 selected

test_02.py .                                                                        [100%]
========================= 1 passed, 1 deselected, 4 warnings in 0.04s ===========================

    针对上面示例，能够得出如下结论

1.pytest.mark.markName:markName由用户自行定义，并不是pytest内置
2.-m:后面也可使用表达式，能够在标记之间添加and、or、not等关键字，以下所示：

pytest -m "testValueError and testTypeError" .\test_02.py
pytest -m "testValueError and not testTypeError" .\test_02.py

4.4 跳过测试

    pytest内置了一些标记，如skip、skipif、xfail。其中skip、skipif容许跳过不但愿运行的测试。示例以下所示：

1.要直接跳过某一个测试函数，可使用pytest.mark.skip()装饰器便可

import pytest

def add(x:int,y:int,operator:str)->int:
    if not isinstance(x,(int,)) or not isinstance(y,(int,)) or not isinstance(operator,(str,)):
        raise TypeError("args must be int")
    if operator=="+":
        return x + y
    elif operator=="-":
        return x - y
    else:
        raise ValueError("operator must be '+' or '-' ")

@pytest.mark.testValueError
@pytest.mark.smoke
def test_addValueError():
    with pytest.raises(ValueError) as exInfo:
        add(1,2,"*")
    exInfo=exInfo.value.args[0]
    expectInfo="operator must be '+' or '-' "
    assert expectInfo== exInfo

@pytest.mark.skip(reason="skip this case")
def test_addTypeError():
    with pytest.raises(TypeError):
        add("1","2","+")

运行结果以下所示：

PS C:\Users\Surpass\Documents\PycharmProjects\PytestStudy\Lesson02> pytest -v .\test_02.py
==========================test session starts =================================================
platform win32 -- Python 3.7.6, pytest-5.4.2, py-1.8.1, pluggy-0.13.1 -- d:\program files\python\python.exe
cachedir: .pytest_cache
rootdir: C:\Users\Surpass\Documents\PycharmProjects\PytestStudy\Lesson02
collected 2 items

test_02.py::test_addValueError PASSED                                                      [ 50%]
test_02.py::test_addTypeError SKIPPED                                                      [100%]

2.添加跳过的缘由和条件，可使用pytest.mark.skipif()装饰器便可

    若是有一些测试，只有在知足特定条件的状况下，才被跳过，这时候则可使用pytest.mark.skipif()，示例以下所示：

import pytest

def add(x:int,y:int,operator:str)->int:
    """this is sample case"""
    if not isinstance(x,(int,)) or not isinstance(y,(int,)) or not isinstance(operator,(str,)):
        raise TypeError("args must be int")
    if operator=="+":
        return x + y
    elif operator=="-":
        return x - y
    else:
        raise ValueError("operator must be '+' or '-' ")

@pytest.mark.testValueError
@pytest.mark.smoke
def test_addValueError():
    with pytest.raises(ValueError) as exInfo:
        add(1,2,"*")
    exInfo=exInfo.value.args[0]
    expectInfo="operator must be '+' or '-' "
    assert expectInfo== exInfo

@pytest.mark.skipif(add.__doc__=="this is sample case",reason="skip this case")
def test_addTypeError():
    with pytest.raises(TypeError):
        add("1","2","+")

运行结果以下所示：

platform win32 -- Python 3.7.6, pytest-5.4.2, py-1.8.1, pluggy-0.13.1 -- d:\program files\python\python.exe
cachedir: .pytest_cache
rootdir: C:\Users\Surpass\Documents\PycharmProjects\PytestStudy\Lesson02
collected 2 items

test_02.py::test_addValueError PASSED                                                                      [ 50%]
test_02.py::test_addTypeError SKIPPED                                                                      [100%]

尽管跳过的缘由不是必须写，但仍是建议在实际项目尽量的写上，方便知道跳过的缘由，若是想知道跳过的详细缘由，可以使用参数 -rs

PS C:\Users\Surpass\Documents\PycharmProjects\PytestStudy\Lesson02> pytest -rs -v .\test_02.py
======================test session starts ====================================
platform win32 -- Python 3.7.6, pytest-5.4.2, py-1.8.1, pluggy-0.13.1 -- d:\program files\python\python.exe
cachedir: .pytest_cache
rootdir: C:\Users\Surpass\Documents\PycharmProjects\PytestStudy\Lesson02
collected 2 items

test_02.py::test_addValueError PASSED                                                       [ 50%]
test_02.py::test_addTypeError SKIPPED                                                       [100%]
==================================short test summary info =================================
SKIPPED [1] test_02.py:23: skip this case
==========================1 passed, 1 skipped, 2 warnings in 0.04s ========================

4.5 标记预期失败的测试

    使用skip和skipif，在知足条件的下，会直接跳过，而不会执行。使用xfail标记，则是预期运行失败，以下所示：

import pytest

def add(x:int,y:int,operator:str)->int:
    """this is sample case"""
    if not isinstance(x,(int,)) or not isinstance(y,(int,)) or not isinstance(operator,(str,)):
        raise TypeError("args must be int")
    if operator=="+":
        return x + y
    elif operator=="-":
        return x - y
    else:
        raise ValueError("operator must be '+' or '-' ")

@pytest.mark.xfail
def test_addValueError():
    with pytest.raises(ValueError) as exInfo:
        add(1,2,"*")
    exInfo=exInfo.value.args[0]
    expectInfo="operator must be '+' or '-' "
    assert expectInfo!= exInfo

@pytest.mark.xfail(add.__doc__=="this is sample case",reason="skip this case")
def test_addTypeError():
    with pytest.raises(TypeError):
        add("1","2","+")

运行结果以下所示：

PS C:\Users\Surpass\Documents\PycharmProjects\PytestStudy\Lesson02> pytest  .\test_02.py
============================test session starts ===================================
platform win32 -- Python 3.7.6, pytest-5.4.2, py-1.8.1, pluggy-0.13.1
rootdir: C:\Users\Surpass\Documents\PycharmProjects\PytestStudy\Lesson02
collected 2 items

test_02.py xX                                                                        [100%]

======================= 1 xfailed, 1 xpassed in 0.19s ===============================

• x表明XFAIL，意味着expect to fail（预期失败，实际上也失败）
• X表明XPASS，意味着expect to fail but passed（预期失败，实际上成功）

    对于标记为xfail，但实际运行结果为XPASS的测试，能够在pytest配置中强制指定为FAIL，在pytest.ini文件按以下修改便可：

[pytest]
xfail_strict=true

4.6 运行测试子集

    前面主要介绍对测试函数进行标记及如何运行。而运行测试子集能够按目录、文件、类中的测试，还能够选择运行某一个测试用例（可能在文件中，也能够在类中）**。

4.6.1 单个目录

    运行单个目录下的全部测试，以目录作为参数便可，以下所示：

pytest --tb=no .\PytestStudy\

4.6.2 单个测试文件/模块

    运行单个测试文件/模块，以路径名加文件名作为参数便可，以下所示：

pytest --tb=no .\PytestStudy\Lesson02\test_01.py

4.6.3 单个测试函数

    运行单个测试函数，只须要在文件名后面添加::符号和函数名便可，以下所示：

pytest .\test_02.py::test_addTypeError

4.6.4 单个测试类

    测试类用于将某些类似的测试函数组合在一块儿，来看看如下示例：

import pytest

class Person:
    _age=28
    _name="Surpass"
    
    def __init__(self,age,name):
        self._name=name
        self._age=age
        
    @classmethod
    def getAge(cls):
        if not isinstance(cls._age,(int,)):
            raise TypeError("age must be integer")
        else:
            return cls._age
    
    @classmethod
    def getName(cls):
        if not isinstance(cls._name,(str,)):
            raise TypeError("name must be string")
        else:
            return cls._name

class TestPerson:
    
    def test_getAge(self):
        with pytest.raises(TypeError):
            Person.getAge("28")
            
    def test_getName(self):
        with pytest.raises(TypeError):
            Person.getName(123)

    以上测试类中的方法都是测试Person中的方法，所以能够放在一个测试类中，要运行该类，能够在文件名后面添加::符号和类名便可，与运行单个测试函数相似，以下所示：

pytest .\test_03.py::TestPerson -v
========================== test session starts ===========================================
platform win32 -- Python 3.7.6, pytest-5.4.2, py-1.8.1, pluggy-0.13.1 -- d:\program files\python\python.exe
cachedir: .pytest_cache
rootdir: C:\Users\Surpass\Documents\PycharmProjects\PytestStudy\Lesson02
collected 2 items

test_03.py::TestPerson::test_getAge PASSED                                          [ 50%]
test_03.py::TestPerson::test_getName PASSED                                         [100%]

============================= 2 passed in 0.04s ============================================

4.6.5 单个测试类中的测试方法

    若是不但愿运行测试类中的全部测试方法，能够指定运行的测试方法名即，能够在文件名后面添加::类名::类中方法名便可，以下所示：

>>> pytest -v .\test_03.py::TestPerson::test_getName
=========================== test session starts ==================================
platform win32 -- Python 3.7.6, pytest-5.4.2, py-1.8.1, pluggy-0.13.1 -- d:\program files\python\python.exe
cachedir: .pytest_cache
rootdir: C:\Users\Surpass\Documents\PycharmProjects\PytestStudy\Lesson02
collected 1 item

test_03.py::TestPerson::test_getName PASSED                                          [100%]

============================= 1 passed in 0.04s ===============================

4.6.6 用测试名划分测试集合

    -k选项容许用一个表达式指定须要运行的测试，表达式能够匹配测试名或其子串，表达式中也能够包含and、or、not等。

    例如想运行目录中，全部文件中测试函数名包含_add的测试函数，可按以下方式进行操做：

>>> pytest -v -k _add
======================== test session starts ===============================
platform win32 -- Python 3.7.6, pytest-5.4.2, py-1.8.1, pluggy-0.13.1 -- d:\program files\python\python.exe
cachedir: .pytest_cache
rootdir: C:\Users\Surpass\Documents\PycharmProjects\PytestStudy\Lesson02
collected 5 items / 2 deselected / 3 selected

test_01.py::test_add PASSED                                                         [ 33%]
test_02.py::test_addValueError XFAIL                                                [ 66%]
test_02.py::test_addTypeError XPASS                                                 [100%]

==================== 1 passed, 2 deselected, 1 xfailed, 1 xpassed in 0.14s ====================

4.7 参数化测试

4.7.1 参数化方式

    向函数传值并校验其输出是软件测试的经常使用手段，但大部分状况下，仅使用一组数据是没法充分测试函数功能。参数化测试容许传递多组数据，一旦发现测试失败，pytest会及时抛出信息。
    要使用参数化测试，须要使用装饰器pytest.mark.parametrize(args,argsvaules)来传递批量的参数。示例以下所示：

1.方式一

import pytest

def add(x:int,y:int)->int:
    return x+y

@pytest.mark.parametrize("paras",[(1,2),(3,5),(7,8),(10,-98)])
def test_add(paras):
    res=add(paras[0],paras[1])
    expect=paras[0]+paras[1]
    assert res==expect

运行结果以下所示：

>>> pytest -v .\test_04.py
================================================= test session starts =================================================
platform win32 -- Python 3.7.6, pytest-5.4.2, py-1.8.1, pluggy-0.13.1 -- d:\program files\python\python.exe
cachedir: .pytest_cache
rootdir: C:\Users\Surpass\Documents\PycharmProjects\PytestStudy\Lesson02
collected 4 items

test_04.py::test_add[paras0] PASSED                               [ 25%]
test_04.py::test_add[paras1] PASSED                               [ 50%]
test_04.py::test_add[paras2] PASSED                               [ 75%]
test_04.py::test_add[paras3] PASSED                               [100%]

=====================4 passed in 0.10s ====================================

    在parametrize()中第一个参数字符串列表（paras），第二个参数是一个值列表，pytest会轮流对每一个paras作测试，并分别报告每一个测试用例的结果。

    parametrize()函数工做正常，那若是把paras替换为键值对形式了，可否达到一样的效果，以下所示：

2.方式二

import pytest

def add(x:int,y:int)->int:
    return x+y

@pytest.mark.parametrize(("x","y"),[(1,2),(3,5),(7,8),(10,-98)])
def test_add(x,y):
    res=add(x,y)
    expect=x+y
    assert res==expect

运行结果以下所示：

>>> pytest -v .\test_04.py
====================test session starts =================================
platform win32 -- Python 3.7.6, pytest-5.4.2, py-1.8.1, pluggy-0.13.1 -- d:\program files\python\python.exe
cachedir: .pytest_cache
rootdir: C:\Users\Surpass\Documents\PycharmProjects\PytestStudy\Lesson02
collected 4 items

test_04.py::test_add[1-2] PASSED                                            [ 25%]
test_04.py::test_add[3-5] PASSED                                            [ 50%]
test_04.py::test_add[7-8] PASSED                                            [ 75%]
test_04.py::test_add[10--98] PASSED                                         [100%]

======================4 passed in 0.16s =============================

    若是传入的参数具备标识性，则在输出结果中也一样具有可标识性，加强可读性。也可使用完整的测试标识（pytest术语为node），若是标识符中包含空格，则须要使用引号。从新运行指定的测试以下所示：

>>> pytest -v test_04.py::test_add[1-2]
================================ test session starts =======================================
platform win32 -- Python 3.7.6, pytest-5.4.2, py-1.8.1, pluggy-0.13.1 -- d:\program files\python\python.exe
cachedir: .pytest_cache
rootdir: C:\Users\Surpass\Documents\PycharmProjects\PytestStudy\Lesson02
collected 1 item

test_04.py::test_add[1-2] PASSED                                      [100%]

========================== 1 passed in 0.04s ===================================

3.方式三

    除了以上两种方式以外，还可使用以下方式进行参数化，以下所示：

import pytest

def add(x:int,y:int)->int:
    return x+y

paras=((1,2),(3,5),(7,8),(10,-98))
@pytest.mark.parametrize("p",paras)
def test_add(p):
    res=add(p[0],p[1])
    expect=p[0]+p[1]
    assert res==expect

运行结果以下所示

>>> pytest -v test_04.py
================================ test session starts ======================================
platform win32 -- Python 3.7.6, pytest-5.4.2, py-1.8.1, pluggy-0.13.1 -- d:\program files\python\python.exe
cachedir: .pytest_cache
rootdir: C:\Users\Surpass\Documents\PycharmProjects\PytestStudy\Lesson02
collected 4 items

test_04.py::test_add[p0] PASSED                                          [ 25%]
test_04.py::test_add[p1] PASSED                                          [ 50%]
test_04.py::test_add[p2] PASSED                                          [ 75%]
test_04.py::test_add[p3] PASSED                                          [100%]

==============================4 passed in 0.14s ======================================

4.7.2 添加额外参数ids

1.方式一

    以上几种虽然能够达到参数化的目的，但可读性不太友好，为改善可读性，能够为parametrize()引入一个额外的参数ids，使列表中每一个元素都被标识。ids是一个字符串列表和数据对象列表和长度一致。以下所示：

import pytest

def add(x:int,y:int)->int:
    return x+y

paras=((1,2),(3,5),(7,8),(10,-98))

parasIds=[f"{x},{y}" for x,y in paras]

@pytest.mark.parametrize("p",paras,ids=parasIds)
def test_add(p):
    res=add(p[0],p[1])
    expect=p[0]+p[1]
    assert res==expect

运行结果以下所示

>>> pytest -v test_04.py
========================= test session starts ===================================
platform win32 -- Python 3.7.6, pytest-5.4.2, py-1.8.1, pluggy-0.13.1 -- d:\program files\python\python.exe
cachedir: .pytest_cache
rootdir: C:\Users\Surpass\Documents\PycharmProjects\PytestStudy\Lesson02
collected 4 items

test_04.py::test_add[1,2] PASSED                                       [ 25%]
test_04.py::test_add[3,5] PASSED                                       [ 50%]
test_04.py::test_add[7,8] PASSED                                       [ 75%]
test_04.py::test_add[10,-98] PASSED                                    100%]

=================================== 4 passed in 0.11s ============================

    parametrize()不只适于通常的测试函数，也能够适用类，在用于类中，则数据集会被传递给该类的全部方法，以下所示：

import pytest

paras=((1,2),(3,5),(7,8),(10,-98))
parasIds=[f"{x},{y}" for x,y in paras]

class Oper:
    _x=0
    _y=0

    def __int__(self,x,y):
        self._x=x
        self._y=y

    @classmethod
    def add(cls,x,y):
        return x+y

    @classmethod
    def sub(cls,x,y):
        return x-y

@pytest.mark.parametrize("p",paras,ids=parasIds)
class TestOper:
    def test_add(self,p):
        res=Oper.add(p[0],p[1])
        expect=p[0]+p[1]
        assert res==expect

    def test_sub(self,p):
        res = Oper.sub(p[0], p[1])
        expect = p[0] - p[1]
        assert res == expect

运行结果以下所示

>>> pytest -v test_04.py
============================= test session starts =============================
platform win32 -- Python 3.7.6, pytest-5.4.2, py-1.8.1, pluggy-0.13.1 -- d:\program files\python\python.exe
cachedir: .pytest_cache
rootdir: C:\Users\Surpass\Documents\PycharmProjects\PytestStudy\Lesson02
collected 8 items

test_04.py::TestOper::test_add[1,2] PASSED                                  [ 12%]
test_04.py::TestOper::test_add[3,5] PASSED                                  [ 25%]
test_04.py::TestOper::test_add[7,8] PASSED                                  [ 37%]
test_04.py::TestOper::test_add[10,-98] PASSED                               [ 50%]
test_04.py::TestOper::test_sub[1,2] PASSED                                  [ 62%]
test_04.py::TestOper::test_sub[3,5] PASSED                                  [ 75%]
test_04.py::TestOper::test_sub[7,8] PASSED                                  [ 87%]
test_04.py::TestOper::test_sub[10,-98] PASSED                               [100%]

============================ 8 passed in 0.13s ================================

2.方式二

    在给@pytest.mark.parametrize()装饰器传入参数列表时，还能够在参数值中定义一个id作为标识，其语法格式以下所示:

@pytest.mark.parametrize(<value>,id="id")

    示例以下所示：

import pytest

class Oper:
    _x=0
    _y=0

    def __int__(self,x,y):
        self._x=x
        self._y=y

    @classmethod
    def add(cls,x,y):
        return x+y

    @classmethod
    def sub(cls,x,y):
        return x-y

@pytest.mark.parametrize("p",[pytest.param((1,2),id="id-1"),pytest.param((3,5),id="id-2"),
                              pytest.param((7,8),id="id-3"),pytest.param((10,-98),id="id-4")])
class TestOper:
    def test_add(self,p):
        res=Oper.add(p[0],p[1])
        expect=p[0]+p[1]
        assert res==expect

    def test_sub(self,p):
        res = Oper.sub(p[0], p[1])
        expect = p[0] - p[1]
        assert res == expect

运行结果以下所示

>>> pytest -v test_04.py
==============test session starts ====================================
platform win32 -- Python 3.7.6, pytest-5.4.2, py-1.8.1, pluggy-0.13.1 -- d:\program files\python\python.exe
cachedir: .pytest_cache
rootdir: C:\Users\Surpass\Documents\PycharmProjects\PytestStudy\Lesson02
collected 8 items

test_04.py::TestOper::test_add[id-1] PASSED                             [ 12%]
test_04.py::TestOper::test_add[id-2] PASSED                             [ 25%]
test_04.py::TestOper::test_add[id-3] PASSED                             [ 37%]
test_04.py::TestOper::test_add[id-4] PASSED                             [ 50%]
test_04.py::TestOper::test_sub[id-1] PASSED                             [ 62%]
test_04.py::TestOper::test_sub[id-2] PASSED                             [ 75%]
test_04.py::TestOper::test_sub[id-3] PASSED                             [ 87%]
test_04.py::TestOper::test_sub[id-4] PASSED                             [100%]

=============================== 8 passed in 0.19s =============================

    在id不能被参数批量生成，须要自定义时，这个方法很是适用。

原文地址：http://www.javashuo.com/article/p-qreunrvh-nn.html

本文同步在微信订阅号上发布，如各位小伙伴们喜欢个人文章，也能够关注个人微信订阅号：woaitest，或扫描下面的二维码添加关注：