Pytest.mark.parameterize and mock use

Catalog

pytest.mark.parametrize

mock.patch

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pytest.mark.parametrize

Now there is zjk.py modular , Want to test one of them add Function functions , Pass in x, y, hold x The result after square is similar to y Add and return .

zjk.py:

def power(x):
    return x ** 2


def add(x ,y):
    x = power(x)
    return x + y

Create a test file , Test documents are generally in test Beginning or end , establish test_zjk.py:

import pytest
from zjk import add


@pytest.mark.parametrize("pow_res, x, y, excepts", [
    (4, 2, 5, 9),
    (16, 4, 11, 27)
])
def test_add(pow_res, x, y, excepts):
    res = add(x ,y)
    assert res == excepts

stay pycharm Test functions can be run separately in ：

  There is no error in the operation result , Explain that all test cases pass ：

If the test case fails and does not meet the expected results , The error will prompt which use case fails ：

 

 @pytest.mark.parametrize

This is a function for parameter simulation settings , The test function in this example passed 4 Parameters , among x,y be necessary , The other two were added by myself , because x,y Is the incoming value to be measured , The other two are x The value after square , One is the expected output value , Corresponding relation , Here are two sets of test cases , And represents to run 2 Time ： 

call add Function to get the calculation result , keyword assert Assertion , The judgment result is different from the expected result , Don't wait for FAlse, Will not pass the use case , The screenshot above .

mock.patch

Look at the above. zjk.py Inside add The function calls a power Functional , and add Is the function you want to test , We just want to test the code of this function , The function procedure called halfway doesn't want to care , Want to use the value it returns directly , Because in case power Functions are network requests ,cmd Orders, etc , You need the Internet , Machines, etc , So in order to focus on testing , use patch simulation power Function return value

zjk.py Let's add another function ：

def power(x):
    return x ** 2


def sub(y):
    return y - 1


def add(x ,y):
    x = power(x)
    y = sub(y)
    return x + y

test.py modify ：

import mock
import pytest
from zjk import add


@pytest.mark.parametrize("x, y, excepts, pow_res, sub_res", [
    (2, 5, 8, 4, 4),
    (3, 4, 12, 9, 3),
    (7, 7, 4, [1], 3)
])
@mock.patch("zjk.sub")
@mock.patch("zjk.power")
def test_add(mock_power, mock_sub, x, y, excepts, pow_res, sub_res):
    if isinstance(pow_res, list):
        mock_power.side_effect = pow_res
    else:
        mock_power.return_value = pow_res
        mock_sub.return_value = sub_res
        res = add(x ,y)
        assert res == excepts

Added  @mock.patch, Represents the to be tested add The function called by the function intermediate procedure , Such as zjk.sub, Here, it means that what is passed in is sub Function path , Then you need to test the function test_add Passing in functions , The format is mock_ Function name , And there are sequence requirements , Order of incoming parameters （ Left to right ）, Decorator sequence （ Down and up ）

parametrize You also need to add power,sub Value of function , You can test

This is used here. if else To illustrate  side_effect,return_value

return_value  Good understanding is to set the return value , Such as  mock_power.return_value = pow_res  hold  power  The return value of the function , But it must be numeric or string 

side_effect  The requirement of assignment must be an iteratable object , So in the use case, there is one I took from the list 

Set according to the actual situation , If you use it in reverse, you will report an error

Take a look at the results ：