API Mocking in Postman v.s. Apidog: Which is Better?

API mocking is crucial for developers, especially in the early stages of software development when backend API endpoints may be incomplete or still under construction. Mock APIs simulate the behavior of these backend APIs, allowing front-end developers to test their applications without waiting for the backend to be finalized.

Apidog An integrated platform for API design, debugging, development, mock, and testing

REAL API Design-first Development Platform. Design. Debug. Test. Document. Mock. Build APIs Faster & Together.

apidog

Both Postman and Apidog provide API mocking capabilities, but their approaches differ. This article explores three common scenarios to highlight how each tool handles API mocking.

Scenario 1: Mocking API Response with Fixed Values

Let’s take a user detail endpoint as an example for returning fixed values. The endpoint is set up as follows:

• Request method: GET.
• URL: /api/user/{id} (where {id} is the user ID parameter)
• Response type: JSON
• Response content:

{
id: number, // user ID
name: string, // username
avatar: string, // avatar image URL
}

• The expected API mock response:

{
"id": 1,
"name": "Jane,
"avatar": "http://dummyimage.com/100x100",
}

Using Postman to Mock API Responses with Fixed Values

In Postman, you must manually create a mock server and define the desired response data within that server.

Once set up, you can find the created mock under Collections. Click the Send button, and you’ll receive the predefined fixed API response.

Using Apidog to Mock API Response with Fixed Values

Apidog streamlines this process by automatically generating mock APIs when you create the endpoint documentation. This eliminates the need to manually set up the mock server and define the API from scratch, which is a significant advantage over Postman.

Apidog generates random, dynamic mock data based on the API response defined in the documentation. To set specific fixed values for the API response, simply:

1. Define your response example in the endpoint documentation:

2. Adjust the mock priority to Response Example First in the project settings:

Once you save these configurations, you can find the mock API URLs in the endpoint documentation. You can easily copy the URL for direct use in your project code.

If you want to test the mock API first, click the Request button at the end of the mock API, and Apidog will return the expected mock response data.

Scenario 2: Mocking Randomized or Realistic API Response Data

When you need the API endpoint to return randomized or realistic data, Apidog has you covered with Smart Mock—a feature not available in Postman. With Apidog, you can generate varied, dynamic responses for more realistic testing scenarios.

Using Apidog to Mock Randomized API Response Data

To mock randomized API response data in Apidog, ensure that the mock priority is set to Smart Mock First.

On the endpoint documentation, find the Mock URL, and click the Request button at the end, Apidog will return the randomized mock data. Each time you send a request, the API response data updates with new random values.

Using Apidog to Mock Realistic API Response Data

When you want to simulate API responses with realistic data that accurately reflects real-world business scenarios, Apidog is the ideal solution. Unlike Postman, which can help mock realistic API response data, Apidog allows you to easily create these realistic mock responses in a highly visual manner, all without the need for additional configurations.

Here’s how to do it: On the endpoint documentation, locate the data field you wish to mock with realistic data. You'll see a "Mock" option immediately following the field. By clicking it, a list of built-in data expressions for realistic mock data will appear. You can choose an expression that fits the data field or enter your own Faker.js expressions to tailor the mock data.

As you can see, the generated API response data is incredibly realistic, resembling real human data. Each time you send a request, the API response updates while maintaining that same lifelike quality!

Scenario 3: Customizing API Mock Rule

There are instances when you need to mock specific data that aligns with certain conditions. For example, you might want to simulate exceptional cases, such as returning an error response when the ID is set to 999.

{
"error": 1,
"errorMsg": "User information not found"
}

Using Apidog to Customize API Mock Rules

While Postman has limited capabilities for customizing API mock rules,  Apidog's Advanced Mock feature enables you to customize your API mock rules to handle these scenarios easily. By defining the conditions under which different responses should be returned, you can create a more robust and accurate testing environment that reflects real-world situations. This flexibility allows you to ensure that your API behaves as expected, even in edge cases.

Once you have configured the mock expectations, you can quickly test them to validate their accuracy:

6 Best Practices for Mocking API with Apidog

API mocking is essential for modern software development, enabling developers to simulate API responses for comprehensive testing. Learn how Apidog’s user-friendly interface and robust features simplify the process, allowing for efficient data simulation and improved development workflows.

Apidog BlogOliver Kingsley

Conclusion

API mocking is an essential tool that allows developers to efficiently test front-end applications without waiting for backend implementation. While both Postman and Apidog provide valuable API mocking capabilities, Apidog stands out with its user-friendly interface and features like Smart Mock and Advanced Mock, which facilitate more realistic and customized testing scenarios. By leveraging these capabilities, developers can simulate a wide range of API responses, ensuring their applications are robust and ready for real-world use. Whether you need fixed values, randomized data, or customized rules, Apidog has the tools to streamline your development process.