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Basic use of pytest
2022-07-06 11:52:00 【mb61037a3723f67】
Catalog
- test ： The exception thrown is consistent with the specified
- test ： The exception thrown is inconsistent with the exception tested .
- test ： Store exception information in variables .
- test ： Capture exception content through exception content .
- Test warning assertions ：
- Write warning information to variables ：
- Capture information through warning content
- Case study ： Verify function level
- Case study ： Verify class level
- Case study ： Verify module level ：
- 1: fixture Simple use ：
- 2：conftest.py The use of documents
- 3：@pytest.mark.usefixtures decorate
- 1: pytest.mark.xfail()
- 2：pytest.mark.skip()
- 3：pytest.mark.skipif()
- 4： pytest.mark.parametrize()
- 1： Plug in installation
- 2： Generate test reports
- 3： Control the execution sequence of test cases
- 4: Failure to retry
- 5： Cancel plug-in
- 1：Yaml Grammatical rules
- 2：Yaml The use of data structures
- 3： Python Read Yaml File and write Yaml file
One ： Pytest Installation ：
pip install -U pytest -i https://pypi.tuna.tsinghua.edu.cn/simple
Two ： pytest A simple case of ：
- Pytest Able to identify test The first method and Test Initial class .
- Do not print by default , You need to specify print ： pytest.main([’-s’])
- If the class does not Test start , Methods in a class even with test It will not be executed at the beginning .
import pytest
def test_01():
print(" I am a test_01")
def test_02():
print(" I am a test_02")
class Test_demo(object):
def test_03(self):
print(" I am a test_03")
def test_04(self):
print(" I am a test_04")
class Tsts_demo(object):
def test_05(self):
print(" I am a test_05")
if __name__ == '__main__':
pytest.main(['-s'])
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Running results ：
3、 ... and ： Assertion
- The assertion is python Self contained , No unitest Medium .
- Classification of assertions : assert Assertion , Exception assertion , Warning assertion .
1： assert Assertion ：
- When the assertion prediction fails , The remarks will be in AssertionError Throw out , And output on the console .
Case study ：
import pytest
def test_1():
num = 1 + 1
assert num == 2, 'num==2 Condition not satisfied '
def test_2():
num = 1 + 1
assert num == 3, 'num==3 Condition not satisfied '
if __name__ == '__main__':
pytest.main(['-s'])
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Running results ：
2： Exception assertion
- If a specified exception occurs, pass , If there is an exception that is not specified, an error is reported .
- pytest.raises（ Expected exception class ,match = Abnormal matching information ）
- with pytest.raises(TypeError) as Variable : This variable stores all the information of the exception .
- Variable .__dict__ Get all the attributes of the variable .
Case study ：
First, a function of leap year is given as the function to be tested ：
# A function of whether it is a leap year
def is_leap_year(year):
# First judge year Is it an integer
if isinstance(year, int) is not True:
raise TypeError(" The parameter passed in is not an integer ")
elif year == 0:
raise ValueError(" The first year of A.D. began in A.D ！！")
elif abs(year) != year:
raise ValueError(" The parameter passed in is not a positive integer ")
elif (year % 4 == 0 and year % 100 != 0) or year % 400 == 0:
print("%d Year is a leap year " % year)
return True
else:
print("%d Year is not a leap year " % year)
return False
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test ： The exception thrown is consistent with the specified
class TestAssert(object):
def test_01(self):
with pytest.raises(TypeError):
# You pass in a string , It will be thrown out. TypeError It's abnormal , however pytest.raises The designated is TypeError So the test passed .
is_leap_year('2020')
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test ： The exception thrown is inconsistent with the exception tested .
class TestAssert(object):
def test_01(self):
with pytest.raises(TypeError):
# What's coming in is 0, It will be thrown out. ValueError It's abnormal , however pytest.raises Specifies the TypeError So the test failed , Throw an exception .
is_leap_year(0)
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test ： Store exception information in variables .
class TestAssert(object):
def test_01(self):
with pytest.raises(TypeError) as err_info:
# What's coming in is 0, It will be thrown out. ValueError It's abnormal , however pytest.raises Specifies the TypeError So the test failed , Throw an exception .
is_leap_year('2000')
print(" The type of exception that occurs is ：", err_info.type)
print(" All abnormal information ：", err_info.__dict__)
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test ： Capture exception content through exception content .
There must be parameters in the matching exception information , And the type is TypeError.
class TestAssert(object):
def test_01(self):
with pytest.raises(TypeError, match=" Parameters ") as err_info:
# What's coming in is 0, It will be thrown out. ValueError It's abnormal , however pytest.raises Specifies the TypeError So the test failed , Throw an exception .
is_leap_year('2000')
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3： Warning assertion
- The biggest difference between warning assertions is that variables can store multiple warnings .
- pytest.warns（）
Active and standby work ： Customize three warning throwing functions ：
def make_warn():
# Throw a version update warning
warnings.warn("deprecated", DeprecationWarning)
def not_warn():
# Don't throw any warnings
pass
def user_warn():
# Throw a compatibility warning
warnings.warn("user warn", UserWarning)
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Test warning assertions ：
class TestWarns(object):
# The test exception is consistent with your own definition
def test_01(self):
with pytest.warns(DeprecationWarning):
make_warn()
# The test exception is inconsistent with your own
def test_02(self):
with pytest.warns(DeprecationWarning):
user_warn()
# The test is normal
def test_03(self):
with pytest.warns(DeprecationWarning):
not_warn()
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test result ：
Write warning information to variables ：
class TestWarns(object):
# The test exception is consistent with your own definition
def test_01(self):
with pytest.warns((DeprecationWarning, UserWarning )) as record:
make_warn()
user_warn()
print(" The length of the variable storing exception information :", len(record))
print(" Store the first information of the exception information variable ：", record[0].message)
print(" Store the first exception type of the exception information variable ：", record[0].category)
print(" All attributes of exception information ", record.__dict__)
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test result :
Capture information through warning content
class TestWarns(object):
# The test exception is consistent with your own definition
def test_01(self):
with pytest.warns((DeprecationWarning), "user") as record:
make_warn()
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result ： Because there is no user, So wrong reporting .
Four ：setup and teardown function
- Function level ：setup_function() teardown_function()
Scope of action ： Only for those outside the class test Function in action , Each is executed once .
- Class level ： setup_class() teardown_class() setup_method() teardown_method()
setup_class() teardown_class()： Execute only once for the current class .
setup_method() teardown_method()： For methods in the current class , Execute every time .
- Module level ：setup_model() teardown_model()
Only execute the start and end of the current file once .
Case study ： Verify function level
import pytest
def test_01():
print(" I'm a normal function 01")
def test_02():
print(" I'm a normal function 02")
def setup_function():
print(" I am the preposition function of ordinary function ")
def teardown_function():
print(" I am the post function of ordinary function ")
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Case study ： Verify class level
import pytest
class Test_Demo(object):
def test_01(self):
print(" I am a function in class 01")
def test_02(self):
print(" I am a function in class 02")
@classmethod
def setup_class(self):
print(" I am a class pre function ")
@classmethod
def teardown_class(self):
print(" I am a class post function ")
def setup_method(self):
print(" I am the method preposition function in the class ")
def teardown_method(self):
print(" I am a method postposition function in class ")
if __name__ == '__main__':
pytest.main()
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Case study ： Verify module level ：
import pytest
def setup_module():
print(" I am a module pre function ")
def test_01():
print(" I'm a test function ")
def teardown_module():
print(" I am a module post function ")
if __name__ == '__main__':
pytest.main()
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5、 ... and ：pytest.fixture Use
1: fixture Simple use ：
Decorate it on ordinary functions , The name of the ordinary function passed in the test function , The name of ordinary function can be used inside the test function , Represents the return value of ordinary functions .
Case study ： Be careful ： Run the tested function before running it fixture Functions of decoration .
import pytest
@pytest.fixture()
def get_url():
print(" I'm just an ordinary function ")
return "http://www.baidu.com"
def test_web(get_url):
print(" Running test function ")
print(" Print get_url The return value of ：", get_url)
if __name__ == '__main__':
pytest.main()
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2：conftest.py The use of documents
（ The inside of this module is fixture Decorative functions can be used directly ）
- If the use case is used in multiple test files in the test The same fixture function , You can move it to conftest.py In file , The required fixture The object will be automatically pytest Find out , Instead of importing every time .
- conftest.py Fixed file name
- stay conftest.py File to achieve common fixture function
Case study ：
1: newly build conftest.py： It defines a person who is @pytest.fixture() Decorate the function that only returns Baidu address .
import pytest
@pytest.fixture()
def get_baidu_url():
return "www.baidu.com"
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2： Another file can be used directly without importing packages conftest Function name in .
import pytest
def test_01_demo(get_baidu_url):
print(get_baidu_url)
if __name__ == '__main__':
pytest.main()
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3： Running results ：
3：@pytest.mark.usefixtures decorate
effect ： If I don't want to use the return value of the decorated function , But you need to call the decorated function before the function is executed , Then you can use @pytest.mark.usefixtures(' Decorated function name ') To deal with it .
Case study ：
import pytest
@pytest.fixture()
def return_url():
print(" I'm Baidu address ： www.baidu.com")
return "www.baidu.com"
@pytest.mark.usefixtures('return_url')
def test_demo():
print(" I'm a test function ")
if __name__ == '__main__':
pytest.main()
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6、 ... and ：fixture Parameters
1： scope Parameters ： Specify the marked function （ Method ） Scope of action
- function : Each test case should be executed once .（ Default ）
- class: Act on the whole class , Each class executes only once .
- module : Scope the whole module （ file ）, Each module is executed only once .
- session ： Scope the entire project , Each project is executed only once .
test function:
import pytest
@pytest.fixture(scope='function')
def foo():
print(" I am being fixture Modified function ")
return " Hello, hello ......."
def test_01(foo):
print(" I am a general test 01:")
print(foo)
def test_02(foo):
print(" I am a general test 02")
print(foo)
class Test_demo(object):
def test_03(self, foo):
print(" I am the test case in the class 03： ")
print(foo)
def test_04(self, foo):
print(" I am the test case in the class 04: ")
print(foo)
if __name__ == '__main__':
pytest.main()
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test ：class
Modify the code just now : become class, Running results ： Be careful ： Non class test cases or every test case should be called .
test ： module:
2: params Parameters
- params Parameters of the receiving list Parameters of type .
- about param Each of these values ,fixture Functions will be traversed and executed once
- Accordingly, it will be driven and used every time fixture The test function of the function executes once .
test
import pytest
@pytest.fixture(params=['renshanwen', '15', '[email protected]'])
def username(request):
print(" I am being fixture Modified function ")
return request.param
def test_demo(username):
print(" I'm a test case ")
print(username)
if __name__ == '__main__':
pytest.main()
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Running results ：
Because there are three decorators in the list , So the test case will be executed three times , Will call the decorated function three times .
3：autouse Parameters
- pytest.fixture(autouse=False) Of autouse The parameter defaults to False, It doesn't automatically execute .
- Set to True when , All currently running test functions will be executed before running fixture function .
demonstration ：
import pytest
@pytest.fixture(autouse=True)
def before():
print(' No matter who you are , Call me first ')
def test_1():
print("test_1")
class Test2:
def test_2(self):
print('test_2')
def test_3(self):
print('test_3')
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7、 ... and ：mark Mark
1: pytest.mark.xfail()
1： Mark the test function as expected failure .
import pytest
@pytest.mark.xfail(reason = " Incomplete function ")
def test_1_demo():
print(" I'm just a decorated one ")
if __name__ == '__main__':
pytest.main()
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Running results ：
2：pytest.mark.skip()
1： Unconditionally skip test cases ：
import pytest
@pytest.mark.skip(reason = " Skip execution ")
def test_1_demo():
print(" I'm just a decorated one ")
if __name__ == '__main__':
pytest.main()
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3：pytest.mark.skipif()
1： Conditionally skip test functions .
import pytest
@pytest.mark.skipif(condition= True, reason = " skip ")
def test_1_demo():
print(" I'm just a decorated one 111111111111111")
@pytest.mark.skipif(condition= False, reason = " Don't skip ")
def test_2_demo():
print(" I'm just a decorated one 222222222222222")
if __name__ == '__main__':
pytest.main()
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2： Running results ：
4： pytest.mark.parametrize()
Purpose ： A parameterized Fixture Methods and test functions
import pytest
@pytest.mark.parametrize(['username', 'password'], [('renshanwen', '12345678'), ('niuniu', '87654321')])
def test_login(username, password):
print("\n")
print("username yes ：", username)
print("password yes ：", password)
if __name__ == '__main__':
pytest.main()
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Running results ：
8、 ... and ： The configuration file
- Configuration file name , pytest.ini Fix .
- The comments in the configuration file are
; - addopts = -s test_20.py : Specify the command to run
- testpaths = ./ : Specify the path of the test file
- python_files = test*.py : Identify with test Opening file
- python_classes = Test* : Identify with Test Initial class
- python_functions = mike* : Identify with test Initial function
Case study ：
[pytest]
addopts = -s test_12.py test_13.py
testpaths = ./
python_files = test_*.py
python_classes = Test_*
python_functions = test_*
; stay ini The comment statement in the file starts with a semicolon , All comment statements, no matter how long, are exclusive until the end
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Nine ： Common plug-ins
1： Plug in installation
workon test_v7 # Enter the virtual environment
pip install pytest-html # Generate test reports
pip install pytest-ordering # Control the execution order of functions
pip install pytest-rerunfailures # Failure to retry
2： Generate test reports
1： Test code ：
import pytest
def test_01():
print(" Test successful test cases ")
assert True
def test_02():
print(" Test cases that fail ")
assert False
if __name__ == '__main__':
pytest.main()
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2： Carry out orders ：
pytest -s test17_port.py --html=./report.html
3: Report display ：
3： Control the execution sequence of test cases
import pytest
@pytest.mark.run(order= 3)
def test_01():
print(" I am test case one ")
@pytest.mark.run(order=1)
def test_02():
print(" I am test case two ")
@pytest.mark.run(order=2)
def test_03():
print(" I am test case three ")
if __name__ == '__main__':
pytest.main()
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Running results :
4: Failure to retry
1： Code ：
import pytest
def test_01():
print(" Test successful test cases ")
assert True
def test_02():
print(" Test cases that fail ")
assert False
if __name__ == '__main__':
pytest.main()
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2： Carry out orders ：
pytest -s test17_port.py --reruns 2
3: Running results ：
5： Cancel plug-in
- -p no:ordering : Unsort
- -p no:html ： Cancel generating test report
- -p no:rerunfailures ： Cancellation failed. Try again
Ten ： Yaml
1：Yaml Grammatical rules
- Case sensitive .
- Use indentation to indicate hierarchy .
- Indentation is not allowed tab key , Only Spaces are allowed .
- The number of Spaces indented is not important , As long as the elements of the same level are aligned to the left .
Yaml Online editor address ： http://old.qqe2.com/jsontool/yaml.php
2：Yaml The use of data structures
1： Yaml And python Transformation ：
Be careful ：Yaml The space after the colon of an object cannot be omitted .
2： Yaml In the array ：
3: Yaml Anchors and references in ：
3： Python Read Yaml File and write Yaml file
1： install PyYaml library ：
pip3 install -U PyYAML
2: Read Yaml file ：
Prepare test files test.yaml
Search_Data:
search_test_001:
value: 456
expect: [4,5,6]
search_test_002:
value: " Hello "
expect: {"value":" Hello "}
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yaml.read.py File read test.yaml Data in ：
import yaml
with open("./test.yaml", "r") as f:
data = yaml.load(f, Loader=yaml.FullLoader)
print(data
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Running results ：
3： Write content to Yaml file
1: yaml_write.py To write
import yaml
data={'Search_Data': {
'search_test_002': {'expect': {'value': ' Hello '}, 'value': ' Hello '},
'search_test_001': {'expect': [4, 5, 6], 'value': 456}
}
}
# To set the encoding format , Otherwise, there will be Chinese code disorder
with open('./yaml_hello.yaml', 'w', encoding='utf-8') as f:
yaml.dump(data, f,allow_unicode=True)
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2： Execution results ：
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