Maximizing efficiency: running API requests with varied data sets in Postman
6-minute read
Published 5, Jul 2024

In the world of software development, efficient API testing is crucial for delivering robust and reliable applications. Running API requests with varied data sets ensures comprehensive testing, uncovering edge cases and potential issues that might otherwise go unnoticed.

This article delves into leveraging Postman, a popular API development and testing tool, to run the same API request multiple times with different data sets, maximizing efficiency and effectiveness in the testing process. An article from our QA Automation Member, Irving Soto.

Challenges in API testing

API testing presents several challenges, particularly when dealing with diverse data sets. Common issues include:

  • Data management: Handling and organizing numerous data sets can become cumbersome.
  • Test coverage: Ensuring that all potential scenarios are tested requires significant effort.
  • Efficiency: Running repetitive tests manually is time-consuming and prone to human error.
  • Dynamic data generation: Creating dynamic and realistic data for testing often involves complex scripting and setup.
Problem to solve

Let’s say we have an endpoint to create users with a simple POST request to /api/users:

{ “name”: “user.01” }

In this case, the API will create a user. We can simply put this request in a Postman collection and start testing it pretty easily. But what should we do if we want to test with different names?

  • What if we want to test with a very long username?
  • What if we want to test with a username with special characters in it?
  • What if we have a dataset we want to test for the same API?
Leveraging Postman for varied data sets

Obviously, there are multiple ways to do it. Postman offers powerful features to address these challenges, enabling efficient API testing with varied data sets. Key capabilities include:

  • Pre-request scripts: JavaScript code snippets executed before the API request, allowing dynamic data generation and manipulation.
  • Collection runner: A feature to run a collection of API requests multiple times with different data sets.
  • Environment variables: Variables that can be set and modified to inject different data into API requests dynamically.

In this article, we are going to see how we can use Pre-request Scripts, Environment Variables, and Workflows to achieve that in the most efficient way.


Implementing solutions

Example: Testing user creation API with varied data sets

Suppose you have an API endpoint for creating users. To test this endpoint with different user data, follow these steps:

  1. Create a collection: Group related API requests in a Postman collection.
  2. Set up environment variables: Define variables for dynamic data (e.g., userNames and currentUserName).Write pre-request script: Use the pre-request script to cycle through different usernames.Configure request: Use the environment variable in the request body.

    3. Set up workflow in tests section: Use the postman.setNextRequest() function to control the workflow and loop through the requests until all usernames are used.

    “Create User” with the actual request name.

    Running the collection

     Set initial environment variable: Before running the collection, ensure userNames is set with all the usernames you want to test.Run collection: Execute the collection in the Collection Runner to see the requests being made with different usernames.

    Pre-request script and tests example

    Here’s a complete example of the pre-request script and tests section for the “Create User” request:

    Pre-request Script:


Lessons learned

Implementing dynamic data testing in Postman reveals several insights:

  • Enhanced test coverage: Running requests with varied data sets improves test coverage, identifying more potential issues. 
  • Improved efficiency: Automating repetitive tasks reduces manual effort and speeds up the testing process. 
  • Better data management: Using pre-request scripts and workflows streamlines data organization and management. 

Running API requests with varied data sets in Postman significantly enhances testing efficiency and coverage. By leveraging pre-request scripts, environment variables, and workflows, developers and testers can streamline their workflows, uncovering potential issues early in the development process. Continuous optimization and adaptation of testing strategies are crucial for maintaining high-quality software development practices.

Postman stands out as a versatile and powerful tool, enabling engineers to maximize efficiency in API testing, ultimately leading to more robust and reliable applications.


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