Studio User Guide

Last updated Jul 16, 2025

API Test Automation

Studio supports API test automation through the New Service wizard. You can import and test API definitions in various API formats, including Swagger, and others. The API test automation capabilities of Studio allow you to build, manage, and run automated tests across different services.

After the import, you can use service definitions in Test Automation projects to validate endpoints, responses, and behaviors. You can also publish service libraries as .nupkg packages, either locally or to Orchestrator, and reuse them as dependencies in your test workflows.

Studio also supports Postman as an additional option for importing API collections. To import a collection, generate an API key in your Postman account and use it in the New Service wizard. Studio integrates with Newman, the command line runner of Postman, so you can validate collections directly from the command line. For more details on the Postman requirements, visit Postman collections.

API test example using Postman

The following example uses a data collection defined in Postman, imports it in a Studio library, publishes the library with the collection, installs it in a testing project, and uses testing activities part of the UiPath.Testing.Activities pack to verify the data usage.

The test cases are designed for a workflow that automatically applies for loans and retrieves loan data for bank customers.

To check Postman and Newman installation prerequisites read this page.

Define a Data Collection

In Postman, either define a data collection or import an existing one to your current workspace. We created a data collection for applying for a loan, retrieving, and deleting loan details. When used in a API test project, this collection checks whether the logic of our workflow is correct.

Import Collections

To import a collection in Studio , create a library project and make use of the New Service window. Access to the collection is granted through the Postman API key. Add this key in the File or Link field and click Load.

Select only the endpoints you would like to load in your project, and add a new Namespace if needed.

Check the Linked collections box so that a link is used so the newest version of your collection is executed at runtime, instead of a version stored locally. Click Save when done.

Using Data Collections

After the collection is imported in the Studio library, its endpoints are automatically transformed into activities, available in the Activities tab, under the namespace that you previously set.

In our example, a separate Sequence file was created for each activity generated from the endpoints.

After adding an activity, add the Postman environment (in between quotes "") in the Properties panel.

Data values defined in the Postman collection are imported as Arguments:

Libraries can be published locally or in Orchestrator as a .nupkg package.

Load Library in API Test Project

Create a test project in Studio using the Test Automation project type.
Install the published library as a dependency using the Manage Packages window.
Sequence files previously defined in the library are now available in the Activities panel under the library's namespace, together with activities generated from the Postman import.
Use these activities in your API test automation project, combined with activities part of the UiPath.Testing.Activities pack. We created a test project to verify the data entered when applying for a loan in our demo application. This small test uses a set of hardcoded variables, visible here in the Properties panel:

This simple test process was used as a smoke test, to check if the application responded correctly. Several such tests can be created in Studio, depending on your automation needs.
To verify several scenarios in one test project, go to the ribbon, New > Data Driven Test Case. Import the data set, as explained here. Below is an example of such a test case. The values are now stored into arguments, mapped in the activity.
Select Run file or Debug file with data variations and choose the data to use. This is useful when testing several scenarios with multiple data sets.
After running the process, the results are visible in the Output panel.