Data-Driven Testing using Selenium Python and Excel

In the world of test automation, data-driven testing is a powerful approach that allows you to run the same test logic against multiple sets of data inputs. This reduces redundancy, improves coverage, and ensures your tests are scalable and maintainable. When combined with Selenium and Python, and powered by data from tools like Excel, you can create flexible and robust test suites.

In this blog, we'll explore how to implement data-driven testing in Selenium Python using Excel files as the source of input data.

What is Data-Driven Testing?

Data-driven testing (DDT) is a software testing method where test scripts read input and expected output values from external data sources like Excel, CSV, or databases. The main advantage of DDT is separation of test logic and test data, which improves reusability and simplifies updates.

Instead of writing multiple test cases with different data, you write one test case and run it with multiple datasets.

Why Use Excel as a Data Source?

Excel is widely used for data entry and reporting, making it a convenient choice for testers and stakeholders. It allows:

Easy editing and storage of test inputs

Structured data representation

Integration with tools like openpyxl or pandas in Python

Setting Up the Environment

Before you begin, install the required packages:

bash

pip install selenium openpyxl

Also, ensure you have the proper web driver (like ChromeDriver) configured for Selenium.

Reading Data from Excel Using openpyxl

Assume you have an Excel file testdata.xlsx with the following content in Sheet1:

Username Password

user1 pass123

user2 pass456

Use the following code to read it:

python

from openpyxl import load_workbook

def read_excel_data(path):

    workbook = load_workbook(filename=path)

    sheet = workbook.active

    data = []

    for row in sheet.iter_rows(min_row=2, values_only=True):

        data.append(row)

    return data

Integrating Excel Data with Selenium Tests

Here's how you can combine Excel data with Selenium to perform login tests:

python

from selenium import webdriver

from selenium.webdriver.common.by import By

import time

def login_test(username, password):

    driver = webdriver.Chrome()

    driver.get("https://example.com/login")

    driver.find_element(By.ID, "username").send_keys(username)

    driver.find_element(By.ID, "password").send_keys(password)

    driver.find_element(By.ID, "loginBtn").click()

    time.sleep(2)

    title = driver.title

    if "Dashboard" in title:

        print(f"[PASS] Login successful for user: {username}")

    else:

        print(f"[FAIL] Login failed for user: {username}")

    driver.quit()

# Run the test for each data row

excel_data = read_excel_data("testdata.xlsx")

for user, pwd in excel_data:

    login_test(user, pwd)

Benefits of This Approach

Reusability: One test function works for all data sets.

Maintainability: Test data changes don't require script changes.

Scalability: Easily scale to hundreds of test inputs.

Business-friendly: Stakeholders can modify test data in Excel.

Conclusion

Data-driven testing with Selenium Python and Excel allows for efficient, scalable, and maintainable test automation. By externalizing test inputs, you reduce code duplication and increase the flexibility of your tests. Whether you're testing login forms, search functionality, or form submissions, integrating Excel with Selenium using Python offers a practical and professional approach to automated testing.

Learn  Selenium with Python Training Course

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