Security News
Research
Data Theft Repackaged: A Case Study in Malicious Wrapper Packages on npm
The Socket Research Team breaks down a malicious wrapper package that uses obfuscation to harvest credentials and exfiltrate sensitive data.
data-factory-testing-framework
Advanced tools
A stand-alone test framework that allows to write unit tests for Data Factory pipelines on Microsoft Fabric and Azure Data Factory.
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:
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:
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:
The following pages go deeper into different topics and concepts of the framework to help in getting you started.
More advanced examples demonstrating the capabilities of the framework:
Fabric:
Azure Data Factory:
Azure Synapse Analytics:
This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.opensource.microsoft.com.
When you submit a pull request, a CLA bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., status check, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.
This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.
This project may contain trademarks or logos for projects, products, or services. Authorized use of Microsoft trademarks or logos is subject to and must follow Microsoft's Trademark & Brand Guidelines. Use of Microsoft trademarks or logos in modified versions of this project must not cause confusion or imply Microsoft sponsorship. Any use of third-party trademarks or logos are subject to those third-party's policies.
FAQs
A stand-alone test framework that allows to write unit tests for Data Factory pipelines on Microsoft Fabric and Azure Data Factory.
We found that data-factory-testing-framework demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 3 open source maintainers collaborating on the project.
Did you know?
Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.
Security News
Research
The Socket Research Team breaks down a malicious wrapper package that uses obfuscation to harvest credentials and exfiltrate sensitive data.
Research
Security News
Attackers used a malicious npm package typosquatting a popular ESLint plugin to steal sensitive data, execute commands, and exploit developer systems.
Security News
The Ultralytics' PyPI Package was compromised four times in one weekend through GitHub Actions cache poisoning and failure to rotate previously compromised API tokens.