Creating Custom Test Logs in Selenium Python

 Logging is a critical component of any test automation framework. It helps testers understand what happened during test execution, especially when tests fail. In Selenium Python, while you can rely on the default console output for quick debugging, creating custom test logs gives you more control, better organization, and improved visibility into your test runs.

In this blog, we’ll walk you through how to implement custom logging in your Selenium Python tests using Python’s built-in logging module, and show you best practices to make your logs readable, informative, and production-ready.

🧠 Why Custom Test Logs Matter

Here’s why custom logging is important in test automation:

Traceability: Track what steps were executed and in what order.

Debugging: Easier identification of failures or flaky tests.

Auditability: Logs act as records of test execution for compliance or reporting.

Integration: Useful for integrating with CI/CD pipelines and test reports.

🛠 Setting Up Logging in Selenium Python

Python’s logging module allows you to create configurable logs at different levels (DEBUG, INFO, WARNING, ERROR, CRITICAL). Let’s integrate it into a Selenium script.

1. Basic Logging Configuration

Start by setting up a logging configuration:

python

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import logging

# Configure the logging

logging.basicConfig(

    filename='test_log.log',

    level=logging.DEBUG,

    format='%(asctime)s - %(levelname)s - %(message)s'

)

This creates a file named test_log.log and logs events with timestamps, levels, and messages.

2. Integrating Logging into Selenium Script

Here’s a simple Selenium test with custom logging:

python

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from selenium import webdriver

from selenium.webdriver.common.by import By

import logging

# Configure logging

logging.basicConfig(

    filename='test_log.log',

    level=logging.INFO,

    format='%(asctime)s - %(levelname)s - %(message)s'

)

def test_google_search():

    logging.info("Starting test: Google Search")

    

    try:

        driver = webdriver.Chrome()

        logging.info("Browser launched successfully")

        driver.get("https://www.google.com")

        logging.info("Navigated to Google")

        search_box = driver.find_element(By.NAME, "q")

        logging.info("Search box found")

        search_box.send_keys("Selenium Python")

        logging.info("Entered search term")

        search_box.submit()

        logging.info("Submitted the search")

        assert "Selenium Python" in driver.title

        logging.info("Page title validated")

    except Exception as e:

        logging.error(f"Test failed due to: {str(e)}")

    finally:

        driver.quit()

        logging.info("Browser closed")

test_google_search()

This script logs every major step, from launching the browser to submitting the search form and validating the page title.

✅ Best Practices for Custom Logging

Log Meaningful Information: Log actions like clicking buttons, navigating to URLs, and form submissions.

Use Log Levels Wisely:

DEBUG for detailed diagnostic output

INFO for general progress updates

ERROR for exceptions and failures

Avoid Over-Logging: Don't log every single WebDriver call. Focus on logical test steps.

Organize Logs by Test Case: Use separate log files for each test or include test names in log entries.

Add Screenshot Paths: Log screenshot file names when capturing images during failures.

📦 Bonus: Creating a Custom Logger Function

You can encapsulate your logging setup in a function or module for reuse:

python

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def create_logger(name):

    logger = logging.getLogger(name)

    handler = logging.FileHandler(f"{name}.log")

    formatter = logging.Formatter('%(asctime)s - %(levelname)s - %(message)s')

    handler.setFormatter(formatter)

    logger.addHandler(handler)

    logger.setLevel(logging.INFO)

    return logger

Call this function in your tests to generate separate log files.

🧩 Final Thoughts

Custom logging in Selenium Python not only improves visibility into your test runs but also makes debugging significantly easier. With structured logs, you can quickly identify what failed, why it failed, and what happened before and after. By following best practices and leveraging Python’s logging module, you can build more maintainable and scalable automation frameworks.

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