A stand-alone test framework that allows to write unit tests for Data Factory pipelines on Microsoft Fabric, Azure Data Factory and Azure Synapse Analytics.
The framework is currently in Public Preview and is not officially supported by Microsoft.
The framework evaluates pipeline and activity definitions which can be asserted. It does so by providing the following features:
- Evaluate expressions by using the framework's internal expression parser. It supports all the functions and arguments that are available in the Data Factory expression language.
- Test an activity with a specific state and assert the evaluated expressions.
- Test a pipeline run by verifying the execution flow of activities for specific input parameters and assert the evaluated expressions of each activity.
The framework does not support running the actual pipeline. It only gives you the ability to test the pipeline and activity definitions.
Given a WebActivity
with a typeProperties.url
property containing the following expression:
@concat(pipeline().globalParameters.BaseUrl, variables('Path'))
A simple test to validate that the concatenation is working as expected could look like this:
# Arrange
activity = pipeline.get_activity_by_name("webactivity_name")
state = PipelineRunState(
parameters=[
RunParameter(RunParameterType.Global, "BaseUrl", "https://example.com"),
],
variables=[
PipelineRunVariable("Path", "some-path"),
])
# Act
activity.evaluate(state)
# Assert
assert "https://example.com/some-path" == activity.type_properties["url"].result
Data Factory does not support unit testing, nor testing of pipelines locally. Having integration and e2e tests running on an actual Data Factory instance is great, but having unit tests on top of them provides additional means of quick iteration, validation and regression testing. Unit testing with the Data Factory Testing Framework has the following benefits:
- Runs locally with immediate feedback
- Easier to cover a lot of different scenarios and edge cases
- Regression testing
Before you start writing tests, you need to set up the repository and install the framework:
If you are not that experienced with Python and prefer a step-by-step guide, use the more detailed getting started guide.
The framework allows you to write two types of tests:
- Activity testing - for testing activities in isolation
- Pipeline testing - for testing the entire pipeline
The following pages go deeper into different topics and concepts of the framework to help in getting you started.
- Debugging your activities and pipelines
- Development workflow
- Overriding expression functions
- Framework internals
More advanced examples demonstrating the capabilities of the framework:
Fabric:
Azure Data Factory:
Azure Synapse Analytics:
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