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Testing an Insight Python Model

You can use the xpressinsight test mode to set up manual or automated tests of your Python code outside Xpress Insight.
Important: Do not activate test mode when running your application within Xpress Insight. Test mode should only be used in an external, non-production environment outside Insight.

Testing your Python code involves simulating user-interface (UI) interactions using functions in the xpressinsight package along with the data_connector property. You can run these tests manually or automate them using the pytest framework.

To set up test mode during the development of a Python Insight app:

  1. Use the xpressinsight.create_app function to create a test environment within the __main__ function: 
    if __name__ == "__main__":
    app = xi.create_app(InsightApp)
    sys.exit(app.call_exec_modes(["LOAD", "RUN"]))

    This code automatically configures temporary working directories and returns a new InsightApp instance. (You can also configure the test environment manually using the AppInterface classes and methods.)

  2. Use the data_connector property to apply modified entity values between execution modes by calling its save_input() method. This example sets and applies an entity value before calling the RUN execution mode: 
    if __name__ == "__main__":
    app = xi.create_app(InsightApp)
    app.call_exec_modes("LOAD")

    # Simulate UI behaviour
    app.InputEntity = 0.2
    app.data_connector.save_input()
    app.call_exec_mode('RUN')

    This process simulates the behavior of a UI user, making it possible to run different scenarios of values assigned to entities outside Xpress Insight.

Covered Topics
  • Setting Up Unit Tests Using the Pytest Framework
    As your Python model grows in complexity and size, you might need to implement automated testing in order to maintain its functionality. The Python package pytest provides a framework for reusing testing functions and objects as part of a test routine, which can help keep your testing logic organized and maintainable.
  • Parameterized Unit Testing Using Pytest
    Manual setup of individual tests might not be suitable for real-world, large-scale applications where tests must run automatically on several files and functions. Parameterized testing with pytest makes it possible to automate the same tests with multiple sets of input data, eliminating the need for redundant test code.
Parent Topic Advanced Topics

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