Python Selenium Automation for Beginners

Happy to share that my first Automation Engineering blog was published on LinkIT under INTECS - UoM. This article reflects my journey with Python and Selenium and what I learned from my first automation project.💻 Read here: https://lnkd.in/dyrmbtuD #Python #Selenium #Automation #INTECS #LinkIT

🚀 I just built an API Test Automation project using Python! In this project, I implemented automated tests for a REST API using Python, Requests and Pytest. 🔹 Covered CRUD operations: GET (list & single user) POST (create user) PUT & PATCH (update user) DELETE (remove user) 🔹 Also included negative test scenarios This project helped me better understand how APIs work and how to validate responses without relying on UI. 🔗 GitHub project: https://lnkd.in/dFpYwxws #QA #AutomationTesting #Python #APITesting #Selenium #SoftwareTesting

🚀 Mastering Prompting in Selenium & Python for Automation Testing In automation testing, the quality of your results depends on how well you guide your tools—especially when working with AI-assisted scripts in Selenium and Python. Here are two simple but powerful principles I follow: 🔹 Principle 1: Write clear and specific instructions Ambiguity leads to flaky tests. The more precise your steps, locators, and validations, the more stable your automation becomes. 🔹 Principle 2: Give the model time to think Complex scenarios (like dynamic elements, waits, or API validations) need structured reasoning. Break problems into steps for better accuracy. 💡 Whether you're building frameworks in Selenium or writing Python automation scripts, clarity + structured thinking = reliable results. 👉 Small improvements in prompting can significantly reduce debugging time and increase test stability. #Selenium #Python #AutomationTesting #SoftwareTesting #QA #PromptEngineering #TestAutomation #AIinTesting

Beyond the Boilerplate: Why Pytest Fixtures are the secret weapon of Python automation. If your test setup logic feels like a teetering Jenga tower of inherited classes and repetitive setUp methods, you’re likely spending more time managing code than actually testing. In the world of Python, moving toward Pytest Fixtures is like switching from manual configuration to a streamlined, automated workflow. The beauty of fixtures lies in their ability to handle complex dependencies while keeping your test files remarkably clean and focused. Why moving away from standard class-based setups changes everything: Explicit Dependency Injection: No more wondering where a database connection or a browser instance magically came from. In Pytest, you pass fixtures as arguments directly to your test function. It’s clear, readable, and tells you exactly what a test requires before you even look at the logic. The Magic of Scopes: Not every resource needs to be recreated for every single test. Pytest allows you to define the "lifetime" of a fixture—whether it’s for a single function, a class, or the entire session. Why log in to your application 50 times when you can do it once, share the state, and significantly speed up your entire pipeline? The "Yield" Revolution: Forget about writing separate, detached cleanup methods. By using the yield keyword, you can combine setup and teardown into a single, intuitive function. Everything before yield happens before the test; everything after handles the cleanup—even if the test fails. Modular Power with conftest.py: You can organize your fixtures in a central conftest.py file, making them globally available across your project without a single import statement. It’s the cleanest way to share configurations across hundreds of test files. Quality in automation is about building a framework that doesn't become a maintenance burden six months down the road. Leveraging fixtures allows you to treat your test infrastructure as a set of modular, reusable components rather than a massive block of copy-pasted boilerplate. Are you still using classic class-based setups, or have you embraced the power of fixtures? Let’s talk about your most complex setup—how many fixtures do you usually "chain" together for a single E2E test? #Python #Pytest #TestAutomation #SDET #SoftwareEngineering #CleanCode #TestGeeks

🐍📈 Test Your Python Apps — Learn how to effectively test your Python code using modern tools and current best-practices #python #learnpython

It Worked Yesterday… What Changed? Hello everyone 👋 Most beginners assume that if a script works once, it’ll work everywhere. That’s wrong. One of the first real issues I faced while learning Selenium was dealing with different screen sizes (viewports). A script that works perfectly on your screen can fail on another machine just because: - The element is not visible - The layout shifts - The button moves or gets hidden - That’s when I understood automation is not just about finding elements, it’s about handling real-world scenarios. While exploring Selenium with Python, I started learning how to: - Adjust browser window size - Maximize or set custom viewports - Ensure elements are visible before interacting Something as simple as viewport handling can decide whether your script is reliable or flaky. Still early in the journey, but now I’m starting to see the gap between “it works” and “it works everywhere.” If you’ve faced similar issues or have tips on making scripts more stable, I’d love to hear them. #Selenium #Python #AutomationTesting #SoftwareTesting #LearningJourney

🚀 Day 8 of My Learning Journey Introduction to API Automation Using Python 🤖What is API Automation? API Automation involves using scripts and tools to test APIs automatically without manual intervention. ✅ Saves time and effort ✅ Improves accuracy and efficiency ✅ Enables continuous testing in CI/CD pipelines 🐍 Why Python? Python is one of the most preferred languages for automation. ✔️ Easy to learn and read ✔️ Powerful libraries for API testing ✔️ Ideal for beginners and professionals ✔️ Widely used in QA and DevOps ✔️ Strong community support 💻 Basic API Automation Example import requests url="{baseURL}/users" response = requests.get(url) print("Status Code:", response.status_code) assert response.status_code == 200 print("Test Passed!") 🎯 This script validates whether the API returns a successful response. #Day8Learning #APIAutomation #Python #SoftwareTesting #QualityAssurance #AutomationTesting #APITesting #PyTest #LearningJourney #TechSkills #QA

The testing section has been extensively revised: • Test examples for cusy.tasks • Added Hypothesis extensions • Agile software development using test-driven development and behaviour-driven development https://lnkd.in/dc9M_J-Y #Python #pytest #Agile #TDD #BDD

Agents building agents? Yep, it's a thing now. With the UiPath Python SDK, you don’t even have to leave your IDE to build, run, and evaluate agents. Check out this tutorial to see how - https://lnkd.in/dsPDtUE3

𝗨𝗡𝗟𝗘𝗔𝗦𝗛 𝗧𝗛𝗘 𝗙𝗨𝗟𝗟 𝗙𝗨𝗥𝗬 𝗢𝗙 𝗣𝗬𝗧𝗛𝗢𝗡: 𝗠𝗔𝗦𝗧𝗘𝗥𝗜𝗡𝗚 𝗧𝗛𝗘 𝗠𝗢𝗦𝗧 𝗗𝗘𝗦𝗧𝗥𝗨𝗖𝗧𝗜𝗩𝗘 𝗢𝗣𝗘𝗥𝗔𝗧𝗢𝗥𝗦 𝗧𝗛𝗔𝗧 𝗪𝗜𝗟𝗟 𝗥𝗘𝗩𝗢𝗟𝗨𝗧𝗜𝗢𝗡𝗜𝗭𝗘 𝗬𝗢𝗨𝗥 𝗖𝗢𝗗𝗜𝗡𝗚 𝗙𝗢𝗥𝗘𝗩𝗘𝗥 As we head into 2026, understanding the fundamental building blocks of code remains the most critical step for any developer transitioning into advanced automation. This tutorial demystifies the core operators in Python, providing a solid foundation for your logic-based programming journey. ARITHMETIC OPERATORS FOR CALCULATION At the heart of every algorithm lie arithmetic operators which allow you to perform basic mathematical computations. You will learn how to go beyond simple addition and subtraction to master modulus, floor division, and exponentiation. These tools are the bedrock for managing data points and numerical logic in your scripts. COMPARISON OPERATORS FOR LOGIC FLOW Comparison operators are the gatekeepers of your control structures. By evaluating relationships between values—such as checking for equality, inequality, or greater-than conditions—you enable your program to make decisions. Mastering these is essential for building effective conditional statements and complex loops. LOGICAL OPERATORS FOR COMPLEX CONDITIONS When a single condition is not enough, logical operators provide the syntax needed to chain multiple requirements together. By utilizing and, or, and not, you gain the ability to write expressive, concise code that handles multifaceted scenarios. Understanding how these operators interact with truth values is a milestone in your development as a proficient Python programmer. Mastering operators is not just about learning syntax; it is about learning how to manipulate data efficiently. As a senior engineer, I recommend internalizing the order of operations and short-circuit evaluation early, as these concepts significantly impact both your code performance and debugging speed. By keeping your logic clean and predictable, you ensure your codebase remains scalable and maintainable as your projects grow in complexity. Tags: #PythonProgramming #CodingTutorial #SoftwareDevelopment #LearnPython 📺 Watch the full breakdown here: https://lnkd.in/dvfGbKke