Python Selenium Architecture:
Python Selenium is an automation framework used for automation browsers & web application testing and web scraping. Its architecture contains several inbuilt functions and libraries that work together to automate interactions with web browsers.
Components of Selenium Architecture
- Selenium WebDriver
- Client Libraries
- JSON Wire Protocol
- Browser
- Web Application
- Tests/Scripts
- Sandboxing
- Remote WebDriver
Selenium WebDriver
At the core of Selenium is the WebDriver, which is responsible for interacting with web browsers. WebDriver communicates with the browser through a native browser-specific driver, which acts as a bridge between the WebDriver API and the browser.
It provides a platform-specific API for automating browser actions. There are different WebDriver implementations for various browsers (e.g., ChromeDriver, GeckoDriver for Firefox, EdgeDriver, etc.).
Client Libraries
The Python Selenium client library provides classes and methods to interact with web elements, manage browser sessions, and perform numerous tasks on the web pages. The primary client library for Python Selenium is the Selenium WebDriver Python API. These libraries enable developers to write Python scripts to automate tasks on web applications.
JSON Wire Protocol
The JSON Wire Protocol is a communication method used between the WebDriver and the browser's native driver. The Selenium client library in Python communicates with the WebDriver using this protocol. It defines a set of RESTful APIs and JSON payloads to send commands and receive responses.
Browser
Selenium supports multiple web browsers, including Chrome, Firefox, Edge, Safari, and others. Each browser has its own WebDriver implementation, ensuring compatibility and consistency across different browsers. The web browser is the target application for automation.
Web Application
Selenium allows you to locate web elements (e.g., buttons, input fields, links) within the web application's DOM (Document Object Model) and perform actions on it.
Tests/Scripts
Selenium scripts use WebDriver methods to navigate to web pages, interact with elements, submit forms, extract data, and perform various other operations. These scripts define a series of actions and verifications to be performed on the web application Test scripts are written by testers using the Selenium client library in Python.
Sandboxing
Each virtual environment contains its own Python interpreter and libraries, ensuring that one project's dependencies do not interfere with another's. Sandboxing allows you to isolate Python projects and their dependencies. Isolated virtual environments enhance stability and security. Bugs or updates in one project won't affect others, reducing the risk of security vulnerabilities.
Remote WebDriver
A Remote WebDriver in Selenium is a way to execute Selenium scripts on a remote machine, allowing you to control a web browser that runs on a different computer or environment. This is useful for distributed testing scenarios like, cross-browser testing.
Python Virtual Environment
A virtual environment is a networked application that allows a user to interact with both the computing environment and the work of other users A Python virtual environment is a self-contained and isolated Python environment that allows you to manage and control dependencies, libraries, and packages for a specific project separately from the system-wide Python installation
Significance of Python Virtual Environment
Python virtual environments are significant for decoupling the python installations & pip packages, as they provide a way to isolate and manage project-specific dependencies, maintain reproducibility, and avoid conflicts between packages.
Dependency Isolation
Virtual environments allow developers to isolate project-specific dependencies, including libraries and packages to preventing conflicts between package versions.
Example:
On working with Project A and Project B. Project A requires requests==2.24.0, while Project B requires requests==2.26.0. Without virtual environments, installing one version of requests would break the other project.
Version Management:
Virtual environments allow you to work with different Python versions for different projects. ensuring compatibility with project-specific requirements.
Example:
create virtual environments for Python 2.x and Python 3.x projects, for example, and switch between them easily.
Reproducibility:
Virtual environments make it easy to replicate the exact development environment on another machine by specifying project dependencies in a requirements.txt file.
Example:
To share your project's dependencies, create and maintain a requirements.txt file.
Generate a requirements.txt file
pip freeze > requirements.txt
Share the requirements.txt file with collaborators
No Administrative Privileges Required:
Virtual environments allow you to work on multiple projects with varying dependencies on a single system. This is especially useful on shared hosting or systems where you don't have full control.
Example:
You can create a virtual environment in your user directory without needing superuser permissions.
--Create a virtual environment in your home directory
python -m venv ~/myenv
Testing and Isolation:
Isolation in testing means creating controlled environments for testing code to prevent interference or contamination from external factors. Virtual environments are invaluable for testing because they allow us to create an isolated environment for testing your code without affecting the global Python environment.
Example:
Consider setting up a virtual environment for running unit tests.
--Create a virtual environment for testing
python -m venv test_env
--Activate the testing environment
source test_env/bin/activate
--Install testing dependencies
pip install pytest
--Run tests within the isolated environment
pytest my_tests.py
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