Python unit testing in the workspace

Azure Databricks provides a suite of tools to discover, run, and track Python unit tests directly in the workspace. Use the testing sidebar pane, inline execution glyphs, and a dedicated results pane to manage your tests without leaving the workspace.

Python unit testing tools are available when you have a valid Python test file open.

Valid Python test files

Azure Databricks follows pytest naming conventions to detect test files, classes and cases.

The following file naming patterns are recognized as valid test files:

• test_*.py
• *_test.py

The following naming conventions detect test classes and cases:

• test-prefixed functions or methods outside of a class
• test-prefixed functions or methods inside Test-prefixed classes (without an __init__ method)
• Methods decorated with @staticmethod or @classmethod inside Test-prefixed classes

For example:

class TestClass():
    def test_1(self):
        assert True

    def test_3(self):
        assert 4 == 3

def test_foo():
    assert "foo" == "bar"

Tests sidebar panel

When you open a valid Python test file, the Tests sidebar pane automatically discovers tests in the current file. When you are inside an authoring context, test discovery covers all files in that context.

From the tests sidebar pane, you can:

• Trigger test actions:
  • Run all tests
  • Run all failed tests
  • Refresh tests
• Monitor test status: View the pass or fail status of each discovered test.
• Filter tests: Filter the test list by name or status. Use the search bar to filter by text or click to filter by status.
• Run individual tests: Execute specific tests directly from the pane. Hover over a test and click .

Run tests with inline glyphs

When you view a Python test file, run buttons appear inline next to each discovered test case. Click to run that test. After each run, the icon updates to indicate whether the test passed or failed.

View inline failure indicators

If a unit test fails, an inline failure indicator appears on the line that caused the failure. Click the indicator to open a modal that displays the full error message.

View test results

When you are on a valid Python test file, a Testing tab is available in the bottom pane. The tab displays the results of the most recent test run, including a full summary and individual test case results.

Hover over a test case to access two options:

• Navigate to test
• Run test