What is API Testing? A Complete Guide To Test APIs

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 ensures it can provide the right data, at the right time, in the right format, and at the expected performance.

How does an API work?

This is how an API response looks like:

So, how does requesting an API happen?

1. The process begins when the client triggers an action requiring data from an API—clicking a button, submitting a form, or running part of a workflow.
2. The request is constructed using an endpoint URL. Each endpoint provides a specific function. For example, if you want product data from the Electronics category of an e-commerce site, the URL might be:
   https://ecommercewebsite.com/products?category=electronics
3. You must specify the HTTP method for the API call. Common methods include:
   • GET: retrieve data
   • POST: create data
   • PUT/PATCH: update data
   • DELETE: remove data
4. If the API endpoint requires parameters, specify them according to the documentation.

Example of an API test

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.

Why is API testing important?

Here are four simple reasons:

1. Make sure it works: API testing confirms that the API returns correct data and responds properly when called.
2. Catch bugs early: It helps detect issues like wrong results, missing fields, or unexpected errors.
3. Handle bad input: Testing ensures the API behaves safely when receiving invalid or unexpected data.
4. Protect connected systems: Because APIs link applications, testing prevents failures from spreading across systems.

Types of API testing

Below are the key types of API testing, along with simple examples:

• Unit Testing: Verifying individual API functions, such as checking whether the “login” endpoint correctly authenticates user credentials.
• Functional Testing: Ensuring an e-commerce API behaves as expected—for example, validating that the shopping cart updates properly.
• Performance Testing: Measuring an API’s speed and responsiveness under various load conditions.
• Security Testing: Validating authentication, authorization, and encryption mechanisms to ensure data is protected.
• Integration Testing: Checking how the API interacts with external systems, like confirming accurate payment processing through a payment gateway.
• Load Testing: Evaluating the API’s performance when many users access it simultaneously.
• Stress Testing: Pushing the API beyond normal limits to see how it handles extreme traffic or large data volumes.
• Fuzz Testing: Sending unpredictable or random inputs such as nonsensical search text to uncover crashes or error-handling issues.

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.

What makes API testing different from other testing types?

1. Language-independent: With API testing, data is exchanged via XML and JSON formats, so any language can be used for test automation. These structured formats make verification fast and stable, and there are built-in libraries to support comparing data.
2. GUI-independent: API testing can be performed before GUI testing. Early testing delivers faster feedback and improves productivity. Core functions can be validated early to uncover small issues and assess the build's quality.
3. Improved test coverage: Most API/web services have specifications, allowing automated tests with high coverage — including functional and non-functional testing.
4. Faster release: Running API tests saves significant time compared to UI testing, allowing teams to release products more quickly.

API test case examples

When testing APIs, it’s important to cover all aspects. Typically, there are three primary areas:

1. Functionality
2. Security
3. Performance

Here are some example test cases for each category:

📚 You may be interested: Top Test Cases for API Testing (With Test Case Template)

Examples of testing API with Python

Scenario 1: Test if the API is online and responding correctly

This is a basic availability check. The script:

1. Imports the requests library
2. Defines the API URL
3. Sends a request — if the server responds with 200 OK, it prints: “✅ API is available and working.”
4. If another status appears (404, 500…), it prints: “❌ API failed with status: [status code]”

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)

Scenario 2: Testing if the API response includes a required field (title)

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)

What are API testing tools?

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:

• Sending different request types (GET, POST, PUT, DELETE, etc.)
• Parameterization and data-driven testing
• Automation and scripting support
• Validation of JSON/XML responses
• Performance and load testing
• Security testing capabilities
• Reporting and analytics

API testing tools make it easier (and often faster) to ensure APIs behave consistently across environments and edge cases.

Best API testing tools QA teams should know

Here are some of the most widely used API testing tools today:

1. Postman

A user-friendly platform for building, sending, and automating API requests. Ideal for both manual and automated testing.

2. Katalon Studio

A low-code/automation-focused API testing tool supporting REST and SOAP APIs, with built-in assertions, data-driven testing, and CI/CD integration.

3. SoapUI / ReadyAPI

A powerful tool for functional, security, and load testing of REST and SOAP services.

4. JMeter

Primarily used for performance and load testing, including APIs.

5. RestAssured

A Java-based library designed for writing automated API tests in code.

Read more: 15 Best API testing tools you should know

Types of bugs that API testing can find

• Functional bugs: The API does not perform the expected action or returns incorrect results.
• Data integrity issues: Returned data is missing, inaccurate, inconsistent, or in the wrong format.
• Performance defects: The API responds slowly, times out, or cannot handle expected traffic levels.
• Security vulnerabilities: Weak authentication, exposed data, injection risks, or unauthorized access paths.
• Broken or incorrect endpoints: Endpoints return wrong status codes, incorrect routes, or unexpected responses.
• Error-handling issues: The API fails to return meaningful errors, uses wrong codes, or crashes on invalid input.
• Integration failures: Problems occur when the API interacts with external systems, databases, or third-party services.
• Concurrency and race condition bugs: Multiple simultaneous requests cause conflicts, overwrites, or inconsistent data.
• Boundary/edge-case failures: The API behaves incorrectly with extreme values, unusual input, or invalid data.
• Compatibility issues: API behaves differently across environments, versions, platforms, or device configurations.

API testing with Katalon: A how-to guide

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:

API testing best practices

1. Combine both manual testing and automated testing. Understand the nature of each approach and use them strategically in your API testing project.
2. Ensure that you have gone through the API documentation before the actual testing begins. Verify that you have all of the details about the API available.
3. Consider edge cases to achieve higher test coverage. These can be as simple as including unsupported characters in the URL. Data-driven testing is a well-recommended practice for this.
4. Include performance tests for your project if you have the bandwidth.

FAQs For API Testing

1. What are the 3 types of testing in API?
   The three main types of API testing are:

• Functional Testing: Ensures the API works as intended, validating inputs, outputs, and behavior.
• Performance Testing: Tests speed, scalability, and reliability under various loads.
• Security Testing: Ensures data protection and guards against vulnerabilities or unauthorized access.

2. Is API testing manual or automated?
   API testing can be both manual and automated.

• Manual Testing: Using tools like Postman to send requests and validate responses manually.
• Automated Testing: Writing scripts with tools like RestAssured or JUnit for CI/CD execution and repeatability.

3. 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.

4. 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.

5. How many days to learn API testing?
   The time to learn API testing depends on your prior experience.

• For beginners, basic manual API testing with tools like Postman can take 1–2 weeks.
• Learning automation testing and frameworks may take 1–2 months with regular practice.

6. What is the future of API testing?
   The future of API testing is promising as APIs play a critical role in software development. Key trends include:

• Increased focus on automation to improve testing speed and efficiency.
• Adoption of AI-driven tools for smarter test generation and bug detection.
• Emphasis on security testing to protect against API vulnerabilities.
• Greater integration of API testing into DevOps and CI/CD workflows.