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Postman API Testing Tips

How To Use Postman In Python

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Integrating Postman with Python for API Testing

Postman is a powerful tool for API testing, offering a user-friendly interface for crafting requests, inspecting responses, and managing test data. Python, on the other hand, provides a robust environment for automation and scripting. This guide will explore how to leverage the capabilities of both Postman and Python for comprehensive API testing, combining the best of both worlds.

1. Setting Up Your Environment

Before diving into coding, ensure you have the following set up:

  • Postman: Download and install the Postman application from https://www.postman.com/.
  • Python: Download and install the latest Python version from https://www.python.org/.
  • Postman API Client Library: Install the postman library using pip:
Terminal window
pip install postman

2. Exporting Postman Collections

Postman Collections store your API requests in a structured format, making them perfect for automation. To utilize these collections in Python, follow these steps:

  • Create or Open Your Collection: In Postman, create a new collection or open an existing one containing the API requests you want to test.
  • Export to JSON: Navigate to the collection’s settings and choose the “Export” option. Select “Collection v2” format and save the file as a .json file (e.g., my_api.json).

3. Implementing Python Scripts with the ‘postman’ Library

Now, let’s bring your Postman collection to life with Python code:

import postman


# Load the exported Postman collection
collection = postman.Collection.from_file("my_api.json")


# Iterate through each request in the collection
for request in collection.items:
    # Execute the request
    response = request.execute()


    # Process the response
    if response.status_code == 200:
        print(f"Request '{request.name}' successful.")
        print(f"Response: {response.text}")
    else:
        print(f"Request '{request.name}' failed with status code {response.status_code}")

This code demonstrates the basic workflow:

  1. Import the postman library.
  2. Load the exported collection from the JSON file.
  3. Loop through each request in the collection.
  4. Execute each request using request.execute().
  5. Access response information like status code (response.status_code) and response body (response.text).

4. Handling Request Parameters and Assertions

Postman collections can include dynamic parameters and assertions. You can leverage these features with Python:

# Accessing request parameters
username = "testuser"
password = "testpassword"
request.set_parameter("username", username)
request.set_parameter("password", password)


# Making assertions
assert response.status_code == 200
assert "success" in response.text

This example shows:

  1. Setting request parameters dynamically before execution.
  2. Adding assertions to verify response status codes and content.

5. Creating Custom Tests with Python

Postman allows defining test scripts within requests. You can extend these tests with Python logic:

# In the 'Tests' tab of a Postman request
pm.test("Status code is 200", function () {
    pm.expect(pm.response.code).to.be.equal(200);
});


# In your Python script
request = collection.item_by_name("My Request")
request.add_test("Custom Test", "pm.test('Status code is 200', function () { pm.expect(pm.response.code).to.be.equal(200); });")

This demonstrates how to add a custom test script to your Postman request using Python and execute it.

6. Sending Files and Authentication

Postman allows you to send files and handle various authentication mechanisms. Python scripts can integrate these functionalities:

# Sending files:
request.set_file("file_field", "path/to/your/file.txt")


# Basic authentication:
request.set_basic_auth(username, password)


# OAuth 2.0 authentication:
request.set_oauth2_auth(token, token_secret)

This code showcases how to send files with set_file, use basic authentication with set_basic_auth, and apply OAuth 2.0 authentication with set_oauth2_auth.

7. Running Postman Collections from the Command Line

Python can be used to execute Postman collections directly from the command line, making it ideal for CI/CD pipelines.

Terminal window
python postman_runner.py

Here, postman_runner.py would contain your Python code for loading, executing, and validating the collection.

Conclusion

By pairing the user-friendly interface of Postman with the power of Python scripting, you can achieve comprehensive API testing:

  • Automating API testing: Run multiple requests with dynamic parameters and sophisticated assertions.
  • Generating reports: Extract and analyze response data for insightful test reports.
  • Integrating with CI/CD: Seamlessly incorporate API testing into your automated build and deployment process.

This guide has provided a solid foundation for leveraging Postman and Python together for API testing. Explore the vast capabilities of this combined approach and elevate your API testing process to new heights.

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