Set up unit testing for Python code

Unit tests are pieces of code that test other code units in an application, typically isolated functions, classes, and so on. When an application passes all its unit tests, you can at least trust that its low-level functionality is correct.

Python uses unit tests extensively to validate scenarios while designing a program. Python support in Visual Studio includes discovering, executing, and debugging unit tests within the context of your development process, without needing to run tests separately.

This article provides a brief outline of unit testing capabilities in Visual Studio with Python. For more on unit testing in general, see Unit test your code.

Select the test framework for a Python project

Visual Studio supports two testing frameworks for Python, unittest and pytest (available in Visual Studio 2019 starting with version 16.3). By default, no framework is selected when you create a Python project. To specify a framework, right-click on the project name in Solution Explorer and select the Properties option. This opens the project designer, which allows you to configure tests through the Test tab. From this tab, you can select the test framework that you want to use for your project.

  • For the unittest framework, the project's root directory is used for test discovery. This location, as well as the text pattern for identifying tests, can be modified on the Test tab to user specified values.
  • For the pytest framework, testing options such as test location and filename patterns are specified using the standard pytest .ini configuration file. See the pytest reference documentation for more details.

Once you've saved your framework selection and settings, test discovery is initiated in the Test Explorer. If the Test Explorer window is not already open, navigate to the toolbar and select Test > Test Explorer.

Configure testing for Python without a project

Visual Studio allows you to run and test existing Python code without a project, by opening a folder with Python code. Under these circumstances, you'll need to use a PythonSettings.json file to configure testing.

  1. Open your existing Python code using the Open a Local Folder option.

    The Visual Studio startup screen

  2. Within the Solution Explorer window, click the Show All Files icon to show all files in the current folder.

    Show all files button

  3. Navigate to the PythonSettings.json file within the Local Settings folder. If you don't see this file in the Local Settings folder, create it manually.

  4. Add the field TestFramework to the settings file and set it to pytest or unittest depending on the testing framework you want to use.

      "TestFramework": "unittest",
      "UnitTestRootDirectory": "testing",
      "UnitTestPattern": "test_*.py"


    For the unittest framework, if the fields UnitTestRootDirectory and UnitTestPattern are not specified in the PythonSettings.json file, they are added and assigned default values of "." and "test*.py" respectively.

  5. If your folder contains a src directory that is separate from the folder that contains your tests, specify the path to the src folder using the SearchPaths field in your PythonSettings.json file.

      "TestFramework": "unittest",
      "UnitTestRootDirectory": "testing",
      "UnitTestPattern": "test_*.py",
      "SearchPaths": [".\\src"]
  6. Save your changes to the PythonSettings.json file to initiate test discovery for the specified framework.


    If the Test Explorer window is already open CTRL + R,A also triggers discovery.

Discover and view tests

By default, Visual Studio identifies unittest and pytest tests as methods whose names start with test. To see test discovery, do the following:

  1. Open a Python project.

  2. Once the project is loaded in Visual Studio, right-click your project in Solution Explorer and select the unittest or pytest framework from the Properties Test tab.


    If you use the pytest framework, you can specify test location and filename patterns using the standard pytest .ini configuration file. By default, the workspace/project folder is used, with a pattern of test_*py and * See the pytest reference documentation for more details.

  3. After the framework is selected, right-click the project again and select Add > New Item, then select Python Unit Test followed by Add.

  4. This action creates a file with code that imports the standard unittest module, derives a test class from unittest.TestCase, and invokes unittest.main() if you run the script directly:

    import unittest
    class Test_test1(unittest.TestCase):
        def test_A(self):
  "Not implemented")
    if __name__ == '__main__':
  5. Save the file if necessary, then open Test Explorer with the Test > Test Explorer menu command.

  6. Test Explorer searches your project for tests and displays them as shown below. Double-clicking a test opens its source file.

    Test Explorer showing default test_A

  7. As you add more tests to your project, you can organize the view in Test Explorer using the Group By menu on the toolbar:

    Tests Explorer Group By toolbar menu

  8. You can also enter text in the Search field to filter tests by name.

For more information on the unittest module and writing tests, see the Python 3.10 documentation.

Run tests

In Test Explorer you can run tests in a variety of ways:

  • Run All clearly runs all shown tests (subject to filters).
  • The Run menu gives you commands to run failed, passed, or not run tests as a group.
  • You can select one or more tests, right-click, and select Run Selected Tests.

Tests run in the background and Test Explorer updates each test's status as it completes:

  • Passing tests show a green tick and the time taken to run the test:

    test_A passed status

  • Failed tests show a red cross with an Output link that shows console output and unittest output from the test run:

    test_A failed status

    test_A failed with reason

Debug tests

Because unit tests are pieces of code, they are subject to bugs just like any other code and occasionally need to be run in a debugger. In the debugger you can set breakpoints, examine variables, and step through code. Visual Studio also provides diagnostic tools for unit tests.


By default, test debugging uses the ptvsd 4 debugger for Visual Studio 2017 (versions 15.8 and later) and debugpy for Visual Studio 2019 (versions 16.5 and later). If you would like to instead use ptvsd 3, you can select the Use Legacy Debugger option on Tools > Options > Python > Debugging.

To start debugging, set an initial breakpoint in your code, then right-click the test (or a selection) in Test Explorer and select Debug Selected Tests. Visual Studio starts the Python debugger as it would for application code.

Debugging a test

You can also use the Analyze Code Coverage for Selected Tests. For more information, see Use code coverage to determine how much code is tested.