Selenium webdriver using python for beginners

Learn why Python is preferred for Selenium, highlighting faster script execution, easier code, the broad Python community, and strong Selenium WebDriver bindings that streamline browser automation.

Explore Selenium, an open source tool that automates browser actions with record and playback, Selenium IDE, WebDriver, and Grid, enabling cross browser testing with Python and other languages.

Record and playback web interactions with Selenium IDE and Catalon Studio, set up in Chrome or Firefox, and export scripts to Python for Selenium tests.

Learn how to install Selenium for Python using pip, verify the installation, and configure browser drivers to automate web interactions with the Selenium WebDriver.

Learn how to create your first Selenium automation script in PyCharm by setting up Selenium, importing WebDriver, and launching a browser with a Chrome driver, then address common setup issues.

Learn how to identify web elements using locators, inspect elements to gather properties, and use id, name, or class or XPath selectors to interact with objects in Selenium.

Identify web element properties with inspect element, copy them as locators, or use Selenium IDE and the element locator add-on to capture XPath selectors for your scripts.

Learn to locate elements in selenium using python with strategies such as id, class name, name, link text, css selector, and xpath, and perform actions like click or send keys.

Learn to automate a bing.com search using selenium with python by opening the browser, locating the search field, entering a query, and clicking the search button, then closing the browser.

Learn to run Selenium Python tests without specifying driver executables by using the webdriver-manager package, install via pip, and automate browser actions with Chrome in your scripts.

Learn to handle checkboxes in Selenium Python by locating the checkbox, inspecting its status, and toggling it with click. Use conditional logic to report or enforce the desired checked state.

Learn to handle radio buttons in selenium python by opening the app, identifying radio button properties, clicking to select the 'strict' option, and verifying with isSelected, printing status.

Learn to handle dropdowns in Selenium Python using send keys and the select class, with select by index, by value, and by visible text to interact with options.

Master using findElements to collect multiple browser objects with various selectors in selenium python, compare with findElement, and handle empty results and text extraction.

Learn to identify all dropdown options with the option tag using Selenium Python, first on Bing.com and then on Salesforce, and compare driver.findElements with dropdown.findElements to capture and print values.

Explore performing tab operations in Selenium with Python by using send_keys within a for loop that processes links, prints their text, and maximizes the browser for reliable execution.

Learn to handle frames in selenium python by switching to the frame, interacting with elements inside it, and returning to the main page using default content.

Learn two reliable methods to select a date in a Selenium Python date picker: directly send date input, or manually click calendar cells and navigate months using next button.

Learn how to capture x and y coordinates of a web element using Selenium Python, using location and get_attribute to retrieve size and class attributes for precise interactions.

Learn to perform drag and drop in Selenium Python using by offset coordinates and action chains, identify source and destination elements, and adapt scripts for resizable elements.

Master handling tooltips with Selenium Python by inspecting elements and using get attribute to capture tooltip text. Apply these steps to automate tooltips on web pages.

Learn how to handle auto suggestions in Selenium with Python by entering a value, collecting and printing all suggestions, and capturing a screenshot to a file path.

Learn to automate mouse hover with Selenium in Python using ActionChains to reveal the 'before you fly' options and select travel information via robust element identification and XPath strategies.

Use Selenium Python to capture all elements with find_elements, loop through them, extract text, compare to travel information, click the match, and break the loop in a test script.

Learn to manage multiple browser windows in selenium webdriver using python, including switching to new windows, interacting with elements in each window, and handling frames within applications like Salesforce.

Learn to manage multiple browser windows and nested frames in selenium with python, including switching to frames, opening new windows, interacting across windows, and returning to the main window.

Learn to handle webtables with Selenium Python by identifying the target table, iterating over rows with a for loop, and extracting tag name and description for each row.

Master implicit and explicit waits in Selenium Python to synchronize actions with page loads, use expected conditions for elements, and avoid no such element exceptions during tests.

Learn how to handle browser alerts with Selenium WebDriver in Python, including switching to alerts, retrieving text, and performing accept or dismiss actions after a 15-second wait.

Learn to execute JavaScript within Selenium Python to interact with difficult web elements by running scripts, inputting values, and clicking search buttons on a browser.

Discover data driven testing with Excel in Selenium Python. Read data from Excel, loop through rows and columns, and feed values into a web test.

Learn to apply the unittest framework to Selenium Python automation, creating test cases and suites, using setup and teardown, and running Salesforce login, dropdown, and window handling examples with reports.

Learn to structure Selenium tests in Python using a unit test framework. Use setUp and setUpClass to run login and create user workflows with multi-window handling.

Learn to convert Selenium Python tests into a unit test framework, manage Chrome with WebDriver Manager, control test order, and run tests from the command line with verbosity.

Learn to generate Selenium Python test execution reports using two options: a third-party reporter and the default reporting system—and export pass/fail results to a dated report in the reports folder.

Learn to implement the page object model in Selenium with Python by organizing login, home, and create user pages into dedicated classes and properties.

Explore how the page factory model extends the page object model by combining properties, logics, and login methods like enter username in a single class with a driver.

Set up a core repository with GitHub, configure git, commit and push code, and pull the latest changes for collaborative automation testing.

Set up Jenkins as a continuous integration tool, create a freestyle job, and execute a selenium python unittest via a Windows batch command, with console output and optional email notifications.

Explore building a customizable selenium framework in python, demonstrating a page object model, package management, drivers, reports, and screenshot capture for test automation.

This lecture reinforces python concepts and test script steps for selenium webdriver beginners, guiding students to use the downloadable document listing all steps, scenarios, and scripts uploaded with the recording.

Configure pytest in PyCharm, add it to the Python interpreter, create tests starting with test, and run them from IDE or terminal to see login and logout tests execute.

Define preconditions and postconditions in pytest using fixtures and decorators, establishing function- and module-level setup and teardown with yield and scope control.

Learn to use pytest markers to group tests, skip others, and run specific subsets with custom markers like sanity, smoke, and rec, plus parameterized data.

Learn to implement setup and teardown in PyTest for Selenium tests, initialize a global Chrome driver, perform login actions on the Sauce Demo app, and clean up after execution.

Convert a test to a parameterized pytest test by feeding username and password from a data method, running two data sets on SauceDemo.

Generate and compare html and allure reports for selenium python tests by configuring pytest-html and allure-pytest, running tests, and serving reports.

Learn to capture screenshots with selenium webdriver using python, including taking a screenshot during test execution and automatically attaching a failure screenshot to allure reports via pytest fixtures.

Learn to run Selenium WebDriver tests in parallel using pytest fixtures and parameterization, launching Chrome and Safari concurrently across two threads for efficient browser testing.

Define a reusable log utility using Python's logging module, organize under a utils directory with a logs folder, and expose a log function that returns a configured logger for frameworks.

Learn to read data from a config.ini file using configparser in Python, organizing values into sections like basic info and mobile, and retrieving the URL, browser name, and execution OS.

Learn to read data from a config.ini file using Python's configparser for basic info and mobile sections, and build an Excel data utility to read and set cell data, save.

Build a selenium python framework on mac, install selenium, openpyxl, pytest, allure-pytest, xdist, and organize folders for allure reports, logs, page objects, test data, and config for ci cd.

Create a login page class with locators, implement login using Selenium WebDriver in Python, and interact with username, password, and login button to validate the flow.

Create a pytest login test with a global Chrome web driver, open the swag demos URL, call the login page logic, and close the browser in teardown.

Read test data from a config.ini with the config reader's read_config method, define a details section for browser name and url, and fix the path to launch the swag demo.

Explore Selenium webdriver using Python for beginners: refactor browser launch into a shared context, manage driver with self attributes, and generate self-contained HTML reports with pytest and Allure.

Learn to generate and serve allure reports from pytest by configuring the allure directory, converting JSON results into readable reports, and debugging with try-except blocks during a login test.

Learn how to generate Allure and html reports for Selenium tests in Python, attach failure screenshots with dynamic date-time names, and verify page titles with assertions.

Master logout automation in a Python Selenium framework by building a home page object, locating the logout action in the side menu, and validating login-logout flows with driver management.

Demonstrates an end-to-end Selenium automation flow in Python: login, add to cart, checkout, fill user info, place order, and return home, using page objects and test orchestration.

Learn to commit the selenium python framework to a private GitHub repo using add, commit, and push, and prepare for Jenkins-driven execution.

Learn to trigger the selenium framework from Jenkins on macOS, configure allure Jenkins and Shining Panda plugins, and run the py test in a Python virtual environment.

Learn what artificial intelligence means, how computers think and learn from data, and see AI in language understanding, image recognition, and everyday tools like Siri, self-driving cars, and Google Maps.

Explore the role of AI in software development and testing, emphasizing human-in-the-loop approaches and reliability concerns. See how AI augments efficiency by generating manual and automation test cases.

Explore how a large language model acts like a human brain, trained on billions of data to translate, answer, summarize, or generate images, with GPT-4, Claude 3, Gemini, and LaMDA.

Explore retrieval augmented generation as a knowledge base that augments LLMs with a vector database to deliver accurate responses.

Explore how generative AI differs from traditional AI for beginners by creating new content such as code, documents, images, audio, and video, rather than only analyzing existing data.

Understand AI memory concepts by examining how past interactions are stored, retained, and retrieved, distinguishing short-term and long-term memory with chatbot examples.

Explore how an AI agent functions as a goal-driven software program that uses tools, plans actions, executes tasks, and adapts based on observed results.

Explore LangChain and LangGraph, showing how an llm uses rag with data via a vector store, including data loading, chunking, and embedding, and how a line graph coordinates ai tools.

Define MCP as a model context protocol that standardizes how AI models call tools and exchange responses, acting as a universal adapter between the model and external systems.

Explore human in the loop, hallucination, and guardrails in AI, with practical examples like Copilot approvals and budget checks, and learn when to involve humans and how to prevent errors.

Learn how fine tuning updates an existing knowledge base to tailor AI interactions for customers and staff, and how it differs from retrieval augmented generation.

Provide a clear context to a language model to boost accuracy and relevance of its outputs. Learn how context before tasks helps the model follow rules and produce targeted results.

Unlock the basics of prompt engineering by understanding what prompts are, why clarity and context matter, and how precise inputs prevent hallucinations when guiding AI through travel planning.

Define an llm context as manual or automation tester with a .txt rules file, then attach user story, acceptance criteria, and UI mockup to generate Excel test cases, avoiding hallucinations.

Create a manual context file and use ChatGPT prompts to generate login flow test steps, covering positive and negative scenarios with clear instructions.

Explore zero shot, one shot, few shot prompts, and chain of thought techniques to guide automation testing with LLMs, and learn how clear context files improve accuracy.

Compare ChatGPT, Copilot, and Cursor AI for coding tasks, highlighting how Copilot and Cursor integrate with VSCode to understand your codebase and generate framework-aware automation code.

Explore how OpenAI powers chatbots and copilots like ChatGPT, and learn how its GPT models and DALL-E image generation shape modern AI through shared principles and collaboration.

Explore how AI models, including GPT and dalle E, are data-trained algorithms that recognize patterns and generate outputs, and distinguish AI models from LLMs.

Explore n8n workflow for automating business tasks without code and create a trial account. Build AI-enabled automations using nodes and workflows, such as email reminders and data processing.

Discover how to generate an OpenAI API key, copy the secret key, and connect AI agents for Python projects, preparing for building an AI agent in the next session.

Create a workflow in n8n that uses an AI agent powered by OpenAI GPT-4.1 mini to read a Google Drive data sheet and email when a match is found.

Learn to build an n8n workflow that reads a sheet, picks an email value, and sends a targeted email using AI-driven prompts, with error handling and dynamic recipient selection.

Create a n8n workflow that reads employee data from Google Sheets sheet two. When status is S, send an email to each user stating that their background verification has started.

Learn to set up a Jira cloud account and create a project. Generate an API token and integrate Zephyr test management to handle test cases and defects.

Learn to automate Jira bug creation with an n8n workflow that reads new defects from a sheet, enables Zephyr, and configures email, api token, and domain credentials.

Use an n8n workflow to create Jira bugs when the status is new, using the defect column values as descriptions and linking to the new state.

Create a public chat in an n8n workflow, generate a shareable URL, and drive defect creation from Google Sheet data by analyzing statuses and updating records.

Learn how OpenAI tokens power cost and processing, with tokens defined as word parts or four characters, and how prompts affect usage, rate limits, and budgeting.

Create a chrome extension for record and playback using Cursor AI to generate Playwright TypeScript or Selenium Java scripts, with setup and loading unpacked extensions in Chrome.

Develop the Cursor AI chrome extension for record and playback that captures browser actions, generates test scripts (Playwright TypeScript or Selenium), and enables download.

Create an otp shield mobile app that monitors text messages, calls, and whatsapp for otp requests, alerts users, and blocks apk files, using android studio, gradle, and cursor ai prompts.

Get a concise overview of gpt4all, an open-source desktop platform for running llms locally offline. Learn how to download, configure a low-memory model, and generate test cases from local documents.

Install the GitHub Copilot plugin in PyCharm from the plugins marketplace, sign in to GitHub, and restart the IDE to enable AI pair programming and code writing assistance.

Learn to generate a Selenium Python login script with Copilot in PyCharm, automate login to a sample site, wait five seconds, and improve element locators with HTML context.

Generate selenium python framework code with copilot, using page objects and test cases to automate login flows, manage locators, and follow framework rules for reliable testing.

The instructor updates the AI video series, expanding from basics to advanced concepts, including test script generation, framework and tool implementation, with daily uploads over the next week.