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How to use pytest.mark

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by l.rohitharohitha2001@gmail.com dot icon Updated: Dec 11, 2023

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 pytest. mark is a mechanism for adding metadata or markers to your test functions or methods. Markers provide a way to categorize, tag, or annotate tests information.


This can leverage metadata to control the execution of tests.  


Benefits of pytest.Mark:  

  1. Organization: The Markers allow the organization of tests based on different criteria. It has different methods, such as test type, purpose, or features.  
  2. Selective Execution: It enables selective test execution using markers, running specific subsets. The tests depend on criteria like test type or category.  
  3. Dynamic Skipping: It provides the ability to skip tests dynamically based on conditions. This makes it useful for scenarios where a test is not applicable.  
  4. Combining Multiple Markers: It Allows the application of multiple markers to a single. It provides detailed information about the test's nature.  
  5. Fixture Integration: Customize test setups using markers and fixtures.  
  6. Documentation and Readability:  It enhances the readability of the test suite by providing.  
  7. pytest.ini Configuration: You can configure markers in the pytest.ini file.  

 

The use of pytest.mark in Pytest plays an important role in streamlining the testing process. By providing a flexible and intuitive mechanism for categorizing, tagging, and annotating tests.

Fig: Preview of the output that you will get on running this code from your IDE.

Code


In this solution we are using Pytest library of Python.

How to specify several marks for the pytest command

PythondotLines of Code : 40dotLicense : Strong Copyleft (CC BY-SA 4.0)

Dependent Libraries : 
import pytest


@pytest.mark.foo
def test_spam():
    assert True


@pytest.mark.foo
def test_spam2():
    assert True


@pytest.mark.bar
def test_eggs():
    assert True


@pytest.mark.foo
@pytest.mark.bar
def test_eggs2():
    assert True


def test_bacon():
    assert True

$ pytest -q --collect-only -m "foo and not bar"
test_mod.py::test_spam
test_mod.py::test_spam2

$ pytest -q --collect-only -m "not foo and not bar"
test_mod.py::test_bacon

$ pytest -q --collect-only -m "foo or bar"
test_mod.py::test_spam
test_mod.py::test_spam2
test_mod.py::test_eggs
test_mod.py::test_eggs2

Instructions


Follow the steps carefully to get the output easily.


  1. Download and Install the PyCharm Community Edition on your computer.
  2. Open the terminal and install the required libraries with the following commands.
  3. Install Pytest - pip install Pytest.
  4. Create a new Python file on your IDE.
  5. Copy the snippet using the 'copy' button and paste it into your Python file.
  6. Remove 28 to 39 lines from the code.
  7. Run the current file to generate the output.


I hope you found this useful.


I found this code snippet by searching for 'How to specify several marks for the pytest command' in Kandi. You can try any such use case!

Environment Tested


I tested this solution in the following versions. Be mindful of changes when working with other versions.

  1. PyCharm Community Edition 2023.2
  2. The solution is created in Python 3.8 Version
  3. PyTest 7.4.3 Version.


Using this solution, we can be able to use pytest.mark in Python with simple steps. This process also facilities an easy way to use, hassle-free method to create a hands-on working version of code which would help us to use pytest.mark in Python.

Dependent Library


pytestby pytest-dev

Python doticonstar image 10300 doticonVersion:7.3.2doticon
License: Permissive (MIT)

The pytest framework makes it easy to write small tests, yet scales to support complex functional testing

Support
    Quality
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            pytestby pytest-dev

            Python doticon star image 10300 doticonVersion:7.3.2doticon License: Permissive (MIT)

            The pytest framework makes it easy to write small tests, yet scales to support complex functional testing
            Support
              Quality
                Security
                  License
                    Reuse

                      You can search for any dependent library on kandi like 'pytest'.


                      FAQ  

                      1. What is the purpose of using pytest.mark in Python testing?  

                      The purpose of using pytest.mark in Python testing is in the context of the Pytest framework. It's to add metadata or markers to your test functions or methods. These markers provide extra information about the tests and serve various purposes.  

                      • Test Categorization  
                      • Selective Test Execution  
                      • Dynamic Test Skipping  
                      • Documentation and Readability  
                      • Conditional Test Execution  
                      • Integration with Fixtures and Hooks  

                        

                      2. How does the pytest -v test help to improve the efficiency of testing?  

                      The pytest -v option in Pytest helps to increase the verbosity of the test execution output. It stands for "verbose," and when used, it provides more detailed information about the test.  

                      • Detailed Test Output  
                      • Location of Failures  
                      • Fixture Setup and Teardown Information  
                      • Understanding Test Execution Order  
                      • Additional Marker Information  
                      • Summary Information  

                        

                      3. What is a test function marker, and how is it used in pytest?  

                      In Pytest, a test function marker is a way to add metadata or annotations to a test function. These markers provide additional information about the nature and purpose of the test. They play an important role in organizing, categorizing, and controlling the execution. Pytest allows you to create and use custom markers based on your specific testing needs.  

                        

                      4. How has Python Testing evolved with the addition of features like pytest.mark?  

                      Features like pytest.mark have influenced the evolution of Python testing. A popular testing framework for Python has played a key role in this evolution.  

                      • Enhanced Test Organization  
                      • Selective Test Execution  
                      • Dynamic Skipping and Conditional Execution  
                      • Fixture Integration and Customization  
                      • Improved Test Readability  
                      • Expanded Testing Strategies  
                      • Integration with Continuous Integration (CI) Systems  
                      • Increased Developer Productivity  

                        

                      5. How are test function names defined within a pytest framework?  

                      In the Pytest framework, test function names follow a specific convention. The convention is simple: test function names must start with "test_" to act as tests. Pytest uses this naming convention to identify which functions or methods tests.  

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