APIs are the backbone of the digital world, and API testing is crucial to ensure that this middleman works seamlessly.
In this article, we’ll explore the concept of API testing in depth. We’ll also show you how easy and simple it is to automate API testing with just a few steps.
API testing is a process used to check whether an API works correctly. It looks at how the API performs, how secure it is, and how it handles different inputs and situations.
Simply put, an API allows applications and software components to transfer data with each other. Think of app A as having a special function, like a unique filter. App B can't directly use that filter, but if app A provides an API, app B can access and use the filter as if it were its own feature.
API testing ensures it can provide the right data, at the right time, in the right format, and at the expected performance.
This is how an API response looks like:
So, how does requesting an API happen?
Let’s look at an API request using the JSONPlaceholder API, which provides fake JSON data for testing and prototyping. We'll make a GET request to retrieve a list of posts from the /posts endpoint:
import requests
# Base URL of the JSONPlaceholder API
base_url = "https://jsonplaceholder.typicode.com"
# Endpoint to retrieve posts
endpoint = "/posts"
# Construct the full URL
url = base_url + endpoint
# Make the GET request
response = requests.get(url)
# Check if the request was successful
if response.status_code == 200:
posts = response.json()
for post in posts:
print("Post ID:", post["id"])
print("Title:", post["title"])
print("Body:", post["body"])
print()
else:
print("Error:", response.status_code)In this request, the Base URL and endpoint are combined to create the full URL.
We then make a GET request to retrieve the data — in this example, the Post ID, Title, and Body fields. API testing checks whether each part of this process works as expected.
Here are four simple reasons:
Below are the key types of API testing, along with simple examples:
By applying these types of API testing, teams can ensure their APIs are correct, fast, secure, and dependable, ultimately delivering a reliable experience to end users.
When testing APIs, it’s important to cover all aspects. Typically, there are three primary areas:
Here are some example test cases for each category:
| Category | Test Case Description |
| API functional testing | Verify that the API endpoint "/users" returns a list of users. |
| Test the POST method on the "/users" endpoint to create a new user. | |
| Validate that required fields such as username and email are mandatory when creating a new user. | |
| Test pagination handling for large data sets returned by the "/users" endpoint. | |
| Verify that an appropriate error response is returned when a user is not found. | |
| API security testing | Attempt SQL injection via API parameters to check for vulnerabilities. |
| Check API responses for exposure of personally identifiable information (PII). | |
| Validate that authentication tokens are required for sensitive endpoints such as "/admin". | |
| Test for XSS vulnerabilities by injecting JavaScript code into inputs. | |
| Verify that rate limiting is enforced to prevent brute-force attacks. | |
| API performance testing | Measure the average response time of the "/users" endpoint under normal load. |
| Conduct load testing by simulating high volumes of concurrent requests. | |
| Test response time of "/products" during peak traffic such as flash sales. | |
| Verify concurrency handling by sending multiple parallel requests to "/orders". | |
| Identify performance bottlenecks by monitoring CPU and memory under heavy stress. |
📚 You may be interested: Top Test Cases for API Testing (With Test Case Template)
This is a basic availability check. The script:
import requests
url = "https://jsonplaceholder.typicode.com/posts"
response = requests.get(url)
if response.status_code == 200:
print("✅ API is available and working.")
else:
print("❌ API failed with status:", response.status_code)
This test checks whether a specific post (/posts/1) includes a title field in its JSON response.
import requests
url = "https://jsonplaceholder.typicode.com/posts/1"
response = requests.get(url)
if response.status_code == 200:
data = response.json()
if "title" in data:
print("✅ 'title' field is present.")
else:
print("❌ 'title' field is missing.")
else:
print("❌ API failed with status:", response.status_code)
API testing tools are software applications designed to help testers validate the functionality, reliability, performance, and security of APIs. They allow teams to send requests to API endpoints, inspect responses, automate test execution, and integrate testing into CI/CD pipelines.
Most tools provide features such as:
API testing tools make it easier (and often faster) to ensure APIs behave consistently across environments and edge cases.
Here are some of the most widely used API testing tools today:
A user-friendly platform for building, sending, and automating API requests. Ideal for both manual and automated testing.
A low-code/automation-focused API testing tool supporting REST and SOAP APIs, with built-in assertions, data-driven testing, and CI/CD integration.
A powerful tool for functional, security, and load testing of REST and SOAP services.
Primarily used for performance and load testing, including APIs.
A Java-based library designed for writing automated API tests in code.
Read more: 15 Best API testing tools you should know
Now let’s see how we can do API testing without coding. Low-code API testing tools are particularly great for testers/QA teams with basic coding expertise. These codeless testing tools help you achieve your goals faster and easier.
Let’s perform a mock API test on https://reques.in, which is a hosted REST API that’s ready to respond to your requests.
In this case, we will make a GET request to list the users. As you can see, we have the Base url as “https://reqres.in/api/users” and the “?page=2” as the query parameter.
Let’s see how it can be done in Katalon. To get started, first download and install the tool.
As you arrive at the Katalon Studio interface, navigate to File > New > Web Service Request. You can also create a test case, test suite, test suite collection, or write a new Groovy script here.
Here we’ll name it “API sample test cases on Reqres”. The request type is “RESTful”, and our endpoint URL is https://reqres.in/api/users?page=2. Add any description if needed, and click OK.
You now have your API request ready to go! The screen below now shows the HTTP Method and the Endpoint URL, with the query parameters automatically parsed. You can now click on the Run button to execute the test.
You can immediately see the response with a status of 200 OK and all of the user data listed below. You have successfully run an API test in Katalon with just a few clicks.
Of course, we don’t want to have to do this again and again, so we want to have a system of automated API tests ready to be run at each development cycle.
With Katalon TestOps you can sync test creation with test management activities. From there, you can plan, create new tests, execute, and view detailed reports on your test history.
You can also reuse test artifacts across different projects for minimal maintenance. API data-driven testing is made simple with multiple data sources (e.g., XLS, CSV) and databases supported.
Instead of manually inputting API parameters, we can create custom fields that dynamically fetch the right type of data from a spreadsheet to run your tests. Watch this video to see how:
Does API testing need coding?
API testing often requires basic coding knowledge for automation but not always for manual testing. Automated testing frameworks like Postman, RestAssured, or JMeter involve scripting. However, low-code/no-code tools allow testers to perform API testing with minimal or no coding.
Is API testing good for a career?
Yes, API testing is an excellent career choice. With APIs being integral to modern applications, demand for skilled API testers is high. It offers opportunities to work on cutting-edge technologies and can lead to advanced roles in quality assurance, automation engineering, or software development.
How many days to learn API testing?
The time to learn API testing depends on your prior experience.