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通过在模块内定义pytestmark变量，从而可以对模块内的所有测试函数以及测试类中的测试方法进行参数化处理，如下所示定义了一个pytestmark变量，然后定义了一个测试函数，同时定义了一个测试类，类中定义了两个测试方法，当然如果要在测试文件中作用参数化，则必须要求测试函数以及测试类中的测试方法的形参必须是一致的。
```python
import pytest

pytestmark = pytest.mark.parametrize("n,expected", [(1, 2), (3, 4),(1,100)])

def test_01(n,expected):
    assert n + 1 == expected
    
class TestClass:
    def test_02(self, n, expected):
        assert n + 1 == expected
        
    def test_03(self, n, expected):
        assert (n * 1) + 1 == expected
```
执行结果如下，可见此时测试文件中的测试函数和测试方法均执行了而且对参数化提供的三组数据均进行了验证，从结果看有6个用例通过，有三个用例失败。
```bash
(demo-HCIhX0Hq) E:\demo>pytest -s
=================== test session starts ===================
platform win32 -- Python 3.7.9, pytest-7.2.0, pluggy-1.0.0
rootdir: E:\demo
plugins: assume-2.4.3, rerunfailures-10.2
collected 9 items

test_demo.py ..F..F..F

======================== FAILURES =========================
_____________________ test_01[1-100] ______________________

n = 1, expected = 100

def test_01(n,expected):
>       assert n + 1 == expected
E       assert (1 + 1) == 100

test_demo.py:6: AssertionError
________________ TestClass.test_02[1-100] _________________

self = <demo.test_demo.TestClass object at 0x0000022C5E04D408>
n = 1, expected = 100

def test_02(self, n, expected):
>       assert n + 1 == expected
E       assert (1 + 1) == 100

test_demo.py:10: AssertionError
________________ TestClass.test_03[1-100] _________________

self = <demo.test_demo.TestClass object at 0x0000022C5E04DFC8>
n = 1, expected = 100

def test_03(self, n, expected):
>       assert (n * 1) + 1 == expected
E       assert ((1 * 1) + 1) == 100

test_demo.py:13: AssertionError
================= short test summary info =================
FAILED test_demo.py::test_01[1-100] - assert (1 + 1) == 100
FAILED test_demo.py::TestClass::test_02[1-100] - assert (1 + 1) == 100
FAILED test_demo.py::TestClass::test_03[1-100] - assert ((1 * 1) + 1) == 100
=============== 3 failed, 6 passed in 0.09s ===============

(demo-HCIhX0Hq) E:\demo>
```

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