Simulating Dataverse

3 minute read

Introduction

The Experimental.SimulateDataverse function allows you to simulate responses from the Dataverse without actually querying the live data. This is particularly useful for testing and development purposes, as it enables you to create predictable and controlled responses for various scenarios.

What is Mocking?

Mocking is a technique used in software testing to simulate the behavior of real objects. By using mocks, you can create controlled environments where you can test specific parts of your application in isolation. This helps ensure that your tests are reliable and repeatable, as they are not dependent on external factors.

Benefits of Mocking

Test Isolation: Mocking allows you to isolate the component you are testing from the rest of the system. This means you can focus on testing the functionality of that component without worrying about the behavior of other parts of the system.
Control Over Test Scenarios: By using mocks, you can create specific scenarios, including both expected and edge cases. This helps you verify that your application behaves correctly under various conditions.
Consistency: Mocking ensures that your tests produce consistent results, as the mocked responses are predefined and do not change.

Example: Simulating Dataverse

Lets look at an example of simulating a dataverse. The first set fo checks validate the expected accounts. After using the SimulateDataverse function empty accounts should be returned.

NOTES:

If the value does not match the test will return “One or more errors occurred. (Exception has been thrown by the target of an invocation.)”

Reload the page to reset the sample to the default state

Want to explore more concepts examples checkout the Learning Playground to explore related testing concepts.

Using Experimental.SimulateDataverse

The Experimental.SimulateDataverse function allows you to define simulated responses for Dataverse actions such as query, create, update, and delete. Here is the syntax:

```powerfx
Experimental.SimulateDataverse({ Action: "Query", Entity: "TableName", When: { Field: "value" }, Then: Table({Name: "Test"}) })
```

Parameters

Name	Description
Action	The Dataverse action to simulate (e.g., Query, Create, Update, Delete).
Entity	The pluralized entity name from metadata.
When	The optional query string to apply.
Filter	A Power Fx expression that needs to be matched. This will automatically be mapped to the OData $filter command.
Then	The Power Fx table to return to be returned to the Power App.

Recording Sample Values

To obtain values for the Experimental.SimulateDataverse function, you can:

Use the network trace of the Browser Developer Tools when using Experimental.Pause(). Filter the traffic by searching for /api/data/v.
Use Recording your first test to record an app that queries Dataverse.

Example

Simulate a Query Response with Sample Data. When the Power App queries all accounts, respond with sample data:

 Experimental.SimulateDataverse({Action: "query", Entity: "accounts", Then: Table({accountid: "a1234567-1111-2222-3333-44445555666", name: "Test"}) })

Simulate a Query with Specific Conditions. When a request is made with an account query name of “Other”, return no results:
```
 Experimental.SimulateDataverse({Action: "query", Entity: "accounts", When: {Name: "Other"}, Then: Table()})
```

Why This Function is Useful

The Experimental.SimulateDataverse function is useful because it allows developers and makers to:

Test and Debug: Simulate different scenarios and responses without affecting live data, making it easier to test and debug applications.
Predictable Results: Create controlled and predictable responses, which is essential for automated testing and ensuring consistent behavior.
Development Efficiency: Speed up the development process by allowing developers to work with simulated data instead of waiting for actual data to be available.

By using this function, you can ensure that your Power Apps behave as expected in various scenarios, leading to more robust and reliable applications.

Summary

In this section, you learned how to use the Experimental.SimulateDataverse function to simulate responses from the Dataverse. This function allows you to create controlled and predictable responses for various scenarios, making it easier to test and debug your applications. By using mocking techniques, you can isolate components, create specific test scenarios, and ensure consistent results. This leads to more efficient development and more reliable applications.

Using simulations