APIs enable seamless data communication among software applications and digital services, making it one of the most essential backbone of our modern society. Carrying such importance, API testing is always highly recommended to ensure that the API is working as expected.
However, APIs may not be fully available to be tested, especially during the earlier stages of development, or when the API providers impose certain access restrictions to their APIs. To resolve such challenges, QA teams use a technique called API mocking, which basically involves creating a simulated version of the real API.
In this article, we will dive deep into the concept of API mocking, explore related concepts, show you how to create a mock API with several simple steps, and best practices to follow during that process.
Read More: What Are APIs? Examples of APIs
API mocking is a software development technique where testers create a simulated version of a real API. This mock API only mimics the behavior, and does not process any data or communicate with external systems. API mocking allows testers to have a substitute to carry on with their testing activities in case the actual API is not available.
At the end of the day, a mock API is only a mimic, and does not have the full capabilities of a real API. Have a look at the comparison chart below to understand the differences between the two:
Aspect | Mock API | Real API |
Purpose | Testing, development, and simulation | Production data and service provision |
Data Processing | Simulated, no actual data processing | Real data processing, storage, and retrieval |
Network Communication | Local or within a testing environment | Over networks, typically the internet |
Response Consistency | Consistent and controlled | Can vary based on server load and conditions |
Data Availability | Generated or predefined data | Access to actual, live data |
Testing and Development | Used during development and testing | Used in production to serve clients/users |
Dependency Isolation | Isolates components from external dependencies | May introduce external dependencies |
Error Simulation | Can simulate error scenarios | May encounter unexpected errors in production |
Security and Privacy | No security or privacy concerns | Requires security measures for sensitive data |
Cost | Cost-effective (no external service costs) | May involve costs (hosting, data transfer, etc.) |
In summary, mock APIs enable more efficient testing and development, allowing developers to work in controlled environments with isolated components for more reliable test results. Real APIs, on the other hand, are production-grade interfaces providing access to actual data for end users.
A mock API is an isolated API, and it is not affected by changes in external services/databases/systems. This simplifies the API testing effort, as the QA team can test it in a highly controlled environment where the independent and dependent variables are clearly defined.
Sometimes the availability of a specific API is necessary to support the development of another system that relies on that API. Thanks to API mocking, teams can work on their respective parts of the system without waiting for external APIs to be fully implemented or stable.
API providers have predefined quotas for how much you can access and use their APIs at varying pricing plans. Creating a mock API can be an economically feasible option if the team does not want to incur additional expenses.
On a similar note, API providers have clear terms as to how their APIs should be used to prevent abuse, but this turns out to be a roadblock against testers who want to test the API “at its limit”. For example, a tester wants to test how the API performs in case of a server outage, which is a rare scenario, and it is impossible to test that on a real API. That is when API mocking shines through.
Since API mocking happens in the local environment, the added level of security and privacy is truly appealing. If the team wants to test scenarios involving sensitive data (such as user credentials), API mocking is the way to go.
Having a mock API provides the team with higher granularity for load testing, i.e., they can more precisely control the system load they want to put the API under. For example, the team can check if the API performs well under normal load, higher than average load, and extreme load.
Many of the challenges encountered in client-side development stem from issues with data handling. These issues can take the form of making incorrect API calls, neglecting to implement error handling, or receiving unexpected responses from the server—problems that occur frequently during both the development and production phases of a project.
API mocking comes to the rescue by enabling developers to replicate a precise API interaction that triggers an issue. This is highly effective for troubleshooting and resolving problems because it allows developers to mimic not only failed scenarios but also successful ones. By simulating these interactions, developers can gain valuable insights into the root causes of issues and efficiently address them, ultimately improving the overall reliability and functionality of their applications.
API mocks offer a valuable way to envision how the application might function if it had been developed differently, all without the need for a full rewrite or committing to a different technological ecosystem. They provide a window into alternative possibilities and help developers make informed decisions about the software's future direction.
Imagine a developer tasked with building the frontend of an e-commerce website, where users can browse products, view product details, and add items to their shopping carts. In this scenario, the actual product data and prices are typically managed by the backend systems and are provided through an API.
When starting the frontend development, the backend API might not be fully developed or accessible (e.g., it’s under construction, being developed by another team, or integrated with external services that are still in progress).
This is when you need API mocking. Instead of waiting for the actual API, teams can build a mock API that “does a good enough job” to substitute for the real one. This resolves the roadblock and accelerates the development speed.
API mocking tools and libraries facilitate the API mocking process. Several notable API mocking tools/libraries include:
Postman is a comprehensive API platform that simplifies the entire API lifecycle and enhances collaboration for building and using APIs more efficiently. It offers tools for storing, cataloging, and collaborating on various API artifacts, including specifications, documentation, test cases, and metrics. With various workspace options, integrations with key development tools, and the flexibility to start for free or choose from paid plans, Postman is a versatile and powerful solution for API development and management across industries.
For API mocking specifically, Postman allows you to establish mock servers that aid in API development and testing. These mock servers mimic the functionality of actual API servers by receiving requests and delivering responses. By integrating a mock server into your collection and incorporating examples within your requests, you can replicate the behavior of a genuine API.
Read More: Top 15 Postman Alternatives for You to Consider
MockServer is a powerful tool that offers flexibility and control in various aspects of development and testing, making it a valuable asset for teams working with HTTP-dependent services and APIs. It simplifies testing by enabling the recreation of different responses for HTTP dependencies, ensuring comprehensive and effective testing of applications. MockServer also helps to isolate the system under test, ensuring tests remain reliable and unaffected by external changes like network failures or server reboots.
WireMock is a library designed for creating stubs and simulating web services. It establishes an HTTP server that you can interact with, much like you would with a real web service. While a WireMock server is active, you can define expected behaviors, make service calls, and then confirm that the expected behaviors have been observed.
Nock is a Node.js library that serves as an HTTP server mocking and expectations tool. It is instrumental in testing modules that independently make HTTP requests. For instance, when testing a module that interacts with a CouchDB server or communicates with the Amazon API, Nock enables isolated testing of that specific module. Nock achieves this by overriding Node's http.request function and also extends its coverage to modules using http.ClientRequest directly.
Pretender is a mock server library designed for XMLHttpRequest and Fetch, featuring an expressive syntax inspired by Express/Sinatra for specifying routes and their corresponding handlers. When Pretender is activated, it temporarily takes over the native XMLHttpRequest and Fetch mechanisms, intercepting all requests and routing them to a custom pretend service you've configured.
Mirage is a JavaScript library aimed at frontend developers to simulate backend APIs effectively. Unlike other mocking libraries, Mirage excels in recreating dynamic scenarios typically achievable only with a real production server. It addresses the challenge many developers face when dealing with dynamic server data during app development by providing a client-side solution.
Mirage allows developers to work with mock data locally, eliminating the need to rely on an actual backend or struggle with networking issues later on. It serves as a versatile and convenient tool for both development and testing, offering predefined conventions that streamline the setup process, making it an essential resource for frontend development.
Mock Service Worker (MSW) is an API mocking library that leverages the Service Worker API to intercept real requests. By harnessing the Service Worker's capability to capture requests for caching purposes, Mock Service Worker empowers API mocking at the highest level of network communication. It effectively serves as a mock server substitute without the need for creating an actual one.
Since Service Worker is a universally supported API in modern browsers, incorporating Mock Service Worker into your application or testing setup is a hassle-free process, involving only the placement of a worker file and the declaration of mocks.