Selenium Test Automation with Pytest (Data-Driven Testing)

This project showcases a Data-Driven Testing (DDT) approach using Selenium and pytest for testing the login functionality of the website Practice Test Automation. This approach allows you to run the same test with various data sets, ensuring comprehensive test coverage.

Prerequisites

Before running the tests, ensure you have the following installed on your system:

1. Python 3.7+: Ensure Python is installed. You can download it from python.org.
2. Google Chrome: Download and install Chrome from here.
3. ChromeDriver: Download the appropriate ChromeDriver from ChromeDriver Downloads. Ensure it's added to your system's PATH.

Installation

Follow these steps to set up the project:

1. Clone the repository or download the project files.

2. Install the required Python dependencies. You can do this by running the following command:

   pip install -r requirements.txt

3. Verify that ChromeDriver is installed and available in your system's PATH.

Data-Driven Testing Structure

This project utilizes Data-Driven Testing (DDT) with the @pytest.mark.parametrize decorator to manage different test scenarios. This approach allows for running the same test with various sets of input data, improving test coverage and robustness.

• Test File: Contains test cases that utilize @pytest.mark.parametrize to handle various login scenarios, including valid and invalid credentials.

Folder Structure

simple-login-automation_DDT-approach/
│
├── tests/                  # Contains the test cases
│   └── test_login.py       # Pytest test cases using Data-Driven Testing
│
├── ref/                    # Folder for storing images
│   └── Img_1.png           # Screenshot of the website
    └── Img_2.png
    └── Img_3.png
    └── Img_4.png
    └── thumbnail.png
│
├── requirements.txt        # Lists project dependencies
└── README.md               # This documentation

Running the Tests

1. Positive Login Test

This test case verifies the correct login functionality using valid credentials.

pytest -k test_login

2. Negative Login Test: Invalid Username

This test case checks the error message displayed when an invalid username is entered.

pytest -k test_login

3. Negative Login Test: Invalid Password

This test case checks the error message displayed when an invalid password is entered.

pytest -k test_login

Test Cases Description

test_login

• Steps:
  • Navigate to https://practicetestautomation.com/practice-test-login/.
  • Enter various sets of credentials.
  • Submit the form.
  • Verify the expected URL and page content based on the input credentials.

Running All Tests

To run all the test cases together, you can simply execute:

pytest

Notes

• This example uses pytest.mark.parametrize for simplicity. For more complex scenarios, consider using CSV files for data input.
• Explicit waits are recommended to ensure elements are interactable.
• Ensure that your ChromeDriver matches the version of Google Chrome installed on your system.

Future Improvements

• CSV Integration: For handling more extensive data sets.
• Enhanced Error Handling: Add better exception handling and logging.
• Utility Functions: Introduce utilities for managing wait times and retries.

This code demonstrates a basic Data-Driven Testing approach. While there are opportunities for improvement, such as better exception handling and advanced data management, this example serves as a starting point for utilizing DDT in your test automation suite.