Selenium with Python Training in Pune with Placement

The grounding every automation engineer is assumed to have and is quietly judged on in interviews. What testing is for, SDLC and STLC as processes rather than acronyms, verification versus validation, and the functional and non-functional testing types.

Then the daily working vocabulary: smoke, sanity and regression testing and when each runs; writing test scenarios and test cases that someone else can execute; the defect life cycle; and severity versus priority, which candidates routinely conflate. Agile, Scrum and Jira close the module, since that is the process every Pune QA role actually runs inside.

Python from installation onward, scoped to what test automation actually uses. Setup and interpreter basics, variables and data types, operators, conditionals and loops, then the collection types — strings, lists, tuples, sets and dictionaries — which is where most test-data handling lives.

Functions, modules and packages follow, then classes, objects and the object-oriented programming that the Page Object Model depends on entirely. Exception handling and file handling cover reading test data and failing informatively. Virtual environments close the module so every student's project is reproducible.

The core automation skill. Selenium's architecture and the W3C WebDriver protocol, driver setup and browser automation, then locators in depth — id, name, class, link text, CSS selectors and XPath — with the discipline of choosing locators that survive a UI change rather than ones that merely work today.

The module then works through everything a real page throws at you: forms, dropdowns, alerts, frames, multiple windows and tabs, web tables, and mouse and keyboard actions. Synchronisation gets particular attention — implicit versus explicit waits, and why `time.sleep` is the first thing a reviewer will flag. JavaScript execution, screenshots and file upload and download close it.

The test runner that makes Python's automation story compelling. Test discovery and naming conventions, plain `assert` statements with PyTest's introspection, and the fixture model — the feature that genuinely distinguishes PyTest from TestNG once you understand scope and composition.

Fixture scope (function, class, module, session) is taught against real cost: a browser launched per test versus per session changes suite runtime by an order of magnitude. Parameterisation, markers for selective runs, test classes, `conftest.py` for shared fixtures, parallel execution with pytest-xdist, and the plugin ecosystem close the module.

The module that separates someone who writes tests from someone who owns a suite. The Page Object Model implemented properly — page classes, locators as class attributes, methods that express user intent rather than clicks — plus base classes carrying shared driver behaviour.

Then the surrounding structure: reusable utilities, configuration files and environment management, test-data management and data-driven testing, logging that makes a CI failure diagnosable, error handling, and screenshot capture on failure. Folder structure is treated as a design decision, because a framework a new joiner cannot navigate is a framework that gets rewritten.

Behaviour-driven development as it is actually practised, including an honest account of when it earns its overhead and when it is ceremony. BDD fundamentals and the three-amigos idea, then Gherkin syntax — Given, When, Then — and feature files written to be readable by someone who is not a programmer.

Scenarios and scenario outlines for data variation, step definitions that map plain language to Python, hooks for setup and teardown, and tags for selective execution. The module ends by integrating Behave with the Selenium framework built in the previous module, so BDD is a layer on top rather than a parallel universe.

Reports are how a QA engineer communicates with people who will never read the code, so they are treated as a deliverable rather than a switch. PyTest HTML reports for the quick local view, then Allure — the report format most Pune teams standardise on — with suites, steps, attachments and history.

Screenshot and log attachment on failure turns a red test into an actionable one. The module also covers custom reporting, environment and build metadata in the report, and the practical question of what a test-execution summary should say to a delivery manager versus a developer.

Version control as the automation engineer uses it. Git fundamentals — the working tree, staging and commits — then the commands that matter day to day: status, diff, log, add, commit, push and pull.

Branching and merging with conflict resolution done without losing work, then the GitHub layer: repositories, pull requests, code review on test code, and project management. The module closes on maintaining an automation project as a shared asset — `.gitignore` for drivers and reports, meaningful commit messages, and a README that lets a reviewer run your suite.

Getting the suite running without you. CI/CD fundamentals and why an automation suite that only runs on the author's laptop delivers a fraction of its value. Jenkins setup, job creation, and running PyTest through Jenkins with the right Python environment.

GitHub integration triggers runs on push and on pull request; scheduled builds cover nightly regression. Test-report publishing surfaces Allure output in Jenkins itself, and the module ends on pipeline fundamentals plus the operational reality of a suite that fails at 2am — notifications, retries and triage.