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## 一、执行已安装包中的测试用例
在某一些场景下，比如需要执行发布包中的测试用例或者自己开发了一个包发布安装之后想再执行已安装包的测试用例（当然发布包的时候需要将测试文件夹一起打包，否则找不到用例），此时在任意位置使用 --pyargs参数指定即可，比如如下指定执行numpy包的tests用例执行
```bash
$ pytest --pyargs numpy.tests
========================================================================= test session starts ==========================================================================
platform win32 -- Python 3.9.7, pytest-6.2.5, py-1.10.0, pluggy-1.0.0
rootdir: D:\src\blog\tests\demo02
plugins: allure-pytest-2.9.43, caterpillar-pytest-0.0.2, hypothesis-6.31.6, forked-1.3.0, rerunfailures-10.1, xdist-2.3.0
collected 49 items

test_ctypeslib.py .......................                                                                                                                         [ 46%]
test_matlib.py ........                                                                                                                                           [ 63%]
test_numpy_version.py ..                                                                                                                                          [ 67%]
test_public_api.py ..........                                                                                                                                     [ 87%]
test_reloading.py ...                                                                                                                                             [ 93%]
test_scripts.py X.                                                                                                                                                [ 97%]
test_warnings.py .                                                                                                                                                [100%]

=========================================================================== warnings summary ===========================================================================
..\..\..\..\Python39\lib\site-packages\numpy\tests\test_matlib.py:2
  D:\Python39\lib\site-packages\numpy\tests\test_matlib.py:2: PendingDeprecationWarning: Importing from numpy.matlib is deprecated since 1.19.0. The matrix subclass is n
ot the recommended way to represent matrices or deal with linear algebra (see https://docs.scipy.org/doc/numpy/user/numpy-for-matlab-users.html). Please adjust your code
 to use regular ndarray.
    import numpy.matlib

test_matlib.py::test_ones
  D:\Python39\lib\site-packages\numpy\tests\test_matlib.py:12: PendingDeprecationWarning: the matrix subclass is not the recommended way to represent matrices or deal wi
th linear algebra (see https://docs.scipy.org/doc/numpy/user/numpy-for-matlab-users.html). Please adjust your code to use regular ndarray.
    np.matrix([[ 1.,  1.,  1.],

test_matlib.py::test_ones
  D:\Python39\lib\site-packages\numpy\tests\test_matlib.py:15: PendingDeprecationWarning: the matrix subclass is not the recommended way to represent matrices or deal wi
th linear algebra (see https://docs.scipy.org/doc/numpy/user/numpy-for-matlab-users.html). Please adjust your code to use regular ndarray.
    assert_array_equal(numpy.matlib.ones(2), np.matrix([[ 1.,  1.]]))

test_matlib.py::test_zeros
  D:\Python39\lib\site-packages\numpy\tests\test_matlib.py:19: PendingDeprecationWarning: the matrix subclass is not the recommended way to represent matrices or deal wi
th linear algebra (see https://docs.scipy.org/doc/numpy/user/numpy-for-matlab-users.html). Please adjust your code to use regular ndarray.
    np.matrix([[ 0.,  0.,  0.],

test_matlib.py::test_zeros
  D:\Python39\lib\site-packages\numpy\tests\test_matlib.py:22: PendingDeprecationWarning: the matrix subclass is not the recommended way to represent matrices or deal wi
th linear algebra (see https://docs.scipy.org/doc/numpy/user/numpy-for-matlab-users.html). Please adjust your code to use regular ndarray.
    assert_array_equal(numpy.matlib.zeros(2), np.matrix([[ 0.,  0.]]))

test_matlib.py::test_identity
  D:\Python39\lib\site-packages\numpy\tests\test_matlib.py:26: PendingDeprecationWarning: the matrix subclass is not the recommended way to represent matrices or deal wi
th linear algebra (see https://docs.scipy.org/doc/numpy/user/numpy-for-matlab-users.html). Please adjust your code to use regular ndarray.
    assert_array_equal(x, np.matrix([[1, 0], [0, 1]]))

test_matlib.py::test_eye
test_matlib.py::test_eye
test_matlib.py::test_rand
test_matlib.py::test_randn
  D:\Python39\lib\site-packages\numpy\matrixlib\defmatrix.py:69: PendingDeprecationWarning: the matrix subclass is not the recommended way to represent matrices or deal
with linear algebra (see https://docs.scipy.org/doc/numpy/user/numpy-for-matlab-users.html). Please adjust your code to use regular ndarray.
    return matrix(data, dtype=dtype, copy=False)

test_matlib.py::test_eye
  D:\Python39\lib\site-packages\numpy\tests\test_matlib.py:30: PendingDeprecationWarning: the matrix subclass is not the recommended way to represent matrices or deal wi
th linear algebra (see https://docs.scipy.org/doc/numpy/user/numpy-for-matlab-users.html). Please adjust your code to use regular ndarray.
    assert_array_equal(xc, np.matrix([[ 0,  1,  0],

test_matlib.py::test_eye
  D:\Python39\lib\site-packages\numpy\tests\test_matlib.py:37: PendingDeprecationWarning: the matrix subclass is not the recommended way to represent matrices or deal wi
th linear algebra (see https://docs.scipy.org/doc/numpy/user/numpy-for-matlab-users.html). Please adjust your code to use regular ndarray.
    assert_array_equal(xf, np.matrix([[ 1,  0,  0,  0],

-- Docs: https://docs.pytest.org/en/stable/warnings.html
============================================================= 48 passed, 1 xpassed, 12 warnings in 12.58s ==============================================================

$
```
## 二、在执行脚本之前加载自定义插件
通过 -p 参数在执行脚本之前加载自定义插件，命令如下，这里因为涉及自定义插件的看法，暂时不详细演示，待后续开发自定义插件后再继续讨论使用
```bash
pytest -p mypluginmodule
```
通过 -p 命令和在插件名称钱加no手动禁止默认插件加载,如下表示禁止doctest插件加载
```bash
pytest -p no:doctest
```
## 三、在IDE中通过右键执行当前文件的方式执行用例
test_case01.py文件内容如下，比如在pycharm中，按照如下编写，直接右键执行即可执行测试用例
```python
import pytest

def test_func1():
    print("\nin test_case01.test_func1......")
    assert 1 == 1

def test_func2():
    print("\nin test_case01.test_func2......")
    assert 1 == 1

if __name__ == "__main__":
    pytest.main()

```
若指定pytest的参数，如下：
```python
import pytest

def test_func1():
    print("\nin test_case01.test_func1......")
    assert 1 == 1

def test_func2():
    print("\nin test_case01.test_func2......")
    assert 1 == 1

if __name__ == "__main__":
    pytest.main(['-s','test_case01.py'])
```
可以在测试文件中调用自定义插件，具体使用格式如下，这里插件待后续进行插件开发时再行讨论
```python
import sys
import pytest

def test_func1():
    print("\nin test_case01.test_func1......")
    assert 1 == 1

def test_func2():
    print("\nin test_case01.test_func2......")
    assert 1 == 1

class MyPlugin:
    def pytest_sessionfinish(self):
        print("*** test run reporting finishing")

if __name__ == "__main__":
    sys.exit(pytest.main(["-s"], plugins=[MyPlugin()]))

```

至此，基本完成pytest的执行方式的总结了，其他更高级话题待后续继续补充

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