Best Python Automation Testing Courses Tools

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I'm aware that the vast majority of testers use Java to write automated tests.

But Python is still my fave.

Here are 22 libraries that make Python great that you can find in this guide:

·         Selenium

·         Splinter

·         Robust Robotics

·         Behave

·         Requests

·         Tavern

·         Hypothesis

·         Pywinauto

·         Automagica

·         Gorgeous Soup

·         NumPy

·         PyTest

·         TensorFlow

·         PDFMiner

·         Pyjest

·         Locust

·         PyBuilder

·         Pandas

·         Coverage.py

·         PyUnit

·         PyCharm

·         Faker

Python: why?

The clearest explanation of this was provided in episode 54 of my weekly TestGuild automation podcast by Al Sweigart, author of Automate the Boring Stuff.

His preferred language has always been Python because

·         The learning curve is gradual.

·         It runs on MAC, Linux, and Windows.

·         Even today, it is a real programming language that is employed by developers.

·         Unlike Java, where you sort of simply have to memorise the public, static, void, string, ban, bracket, etc., it states "Hello world" in a single line.

·         Easily recalled syntax

·         You are not compelled to study object-oriented programming by it.

In order to aid you in your testing and automation efforts, what are some of the greatest Python libraries you can use?

The following list includes some of the top Python automation libraries recommended by my previous interviewees as well as some that I've personally found useful.

For Python Functional Test Automation

Selenium

For automated browser UI, you have the Selenium-Python coupling, of course.

Python is used to automate web browser interaction with this Selenium library.

The industry standard for browser-based automation is Selenium.

This is a great choice if the majority of your team consists of test engineers with development expertise or SDETs.

Splinter

Splinter is a clever Python wrapper library for Selenium.

Python web application testing with Splinter is free software. It enables you to programmatically do browser tasks like browsing URLs and interacting with their contents.

It offers a high-level API that makes it simple to create automation scripts for your web apps, which makes developing Python Selenium tests easier.

Robot Framework

The Robot Framework is a great choice if you wish to automate tests using Python. This established tool, designed for testers, employs a keyword-driven method to make tests comprehensible and simple to write.

A number of test libraries and other tools are also included. Although Jython (Java) or IronPython are other options, the Robot Framework is based on Python (.NET).

Robot Framework may test a variety of other things in addition to Selenium WebDriver, however that library may be the most used external test library:

·         FTP

·         MongoDB

·         Android

·         Appium

·         APIs

·         Mainframes

Robot Framework is a fantastic alternative for your automation framework if your team is primarily made up of testers.

Behave

What about libraries for behavior-driven development?

There are numerous BDD frameworks in Python that resemble Cucumber. Probably the most well-known is behave. Cucumber-like in nature, but written in Python.

Requests

Need to perform HTTP activity or REST API testing?

Python-based Requests is an HTTP library with Apache2 licence. By the sheer quantity of downloads, I think this library is one of the most used python libraries. It is essential to your efforts at test automation.

Tavern

Speaking of API testing, Andrew Knight of the Automation Panda also suggested the Tavern library to me. Your REST API testing becomes much more declarative as a result.

Tavern bills itself as a Python library, Pytest plugin, and command-line tool for automated testing of RESTful APIs with a clear, short, and adaptable YAML-based syntax.

Hypothesis

Property-based testing is a testing subject I've been hearing more and more about. If you like Python and have been wanting to give it a try, check out Hypothesis.

You can test numbers in a specific range using a hypothesis for property-based testing, in which case we'll automatically run through numerous alternatives for you. Finding edge cases in your code that you probably wouldn't have thought to search for is therefore helpful.

Pywinauto

Try pywinauto for functional automation that isn't browser-based.

A collection of Python modules called pywinauto can be used to automate Microsoft Window GUIs.

It allows you to communicate keyboard and mouse commands to Windows dialogue boxes and controls. Additionally, it offers some support for trickier tasks like acquiring text data.

Automagica

Python-based Smart Robotic Process Automation (SRPA) platform Automagica is open-source. Automagica is cool since it allows you to swiftly automate a variety of cross-platform tasks like:

·         Website automation

·         manipulating PDFs

·         manipulating files and folders

·         Operation of email

·         Excel and Word automation

·         Tons more

Consider automating tasks that are unrelated to functional testing.

I don't only mean functional test automation when I say "automation," I mean any action that helps quicken the software development cycle.

Beautiful Soup

Beautiful Soup is one of the Python libraries I employ to extract data from HTML and XML files.

I have a directory in my framework that has a variety of Python auxiliary scripts, the most of which make use of Beautiful Soup, even though the core framework I use is Java-based.

It's excellent for site scraping as well. Beautiful Soup is the library of choice if you have a straightforward static webpage and you need to locate a small piece of information hidden somewhere in the HTML.

The webpage itself may be downloaded using the requests library, and Beautiful Soup will assist you in parsing it.

NumPy

NumPy was mentioned by Brain Okken, the host of the Python-based podcast Test & Code, as his go-to Python library for tasks like testing electrical engineering code.

PyTest

One of the top test automation tools available is pytest, according to Andrew Knight.

One factor is that it is so brief and test-specific. Instead of testing classes, you create tests for functions in Pytest. Additionally, you can define other functions that are designated as fixtures in a dependency injection manner if you want to do set and cleanup.

Therefore, based on their scope, the fixtures will be automatically invoked, and anything they yield will be injected into your test routines. This greatly increases the scalability and reuse of setup and cleaning.

Brian also said that even while it could take you some time to understand pytest fixtures, it will be well worth the effort because of how powerful they are. Python test package pytest is a must-learn for beginners.

TensorFlow

If you've been keeping up with the most recent developments in the automation industry over the past few years, you are aware of how hot artificial intelligence is as a topic.

Google developed and released TensorFlow, a Python library for quick numerical computations. It is a foundation library that may be used to build Deep Learning models directly or indirectly using wrapper libraries created on top of TensorFlow to make the process easier.

PDFMiner

How frequently have you felt the urge to check a PDF's content?

The sheer quantity of Python modules available for interacting with various types of technology, such as parsing PDF files or Excel files, genuinely caught me off guard.

PDFMiner may be useful if you need to check or validate the text in a PDF file. This package essentially functions as a tool for extracting text from PDF files.

Pyjest

Have you heard of Jest, a framework for unit-level automated testing?

It was developed by Facebook and contains features like its interactive watch mode, which you can utilise to enhance processes that make test-driven development simpler.

Locust

Do your Python scripts need additional performance tests added?

Python-based Locust is an easy-to-use load testing tool.

You can determine how many concurrent users a system can support with locust as well.

Cool things that come with Locust include:

·         utilising pure Python to generate your test cases

·         having the ability to simulate a large number of users fast

·         A welcoming Web-based UI that is extensible

·         suitable for API testing

PyBuilder

Python-based PyBuilder is a build automation tool that mostly works with Python projects.

According to its website, it is founded on the idea of dependency-based programming, but it also has a potent plugin mechanism that enables the creation of build life cycles that are comparable to those found in build tools like Apache Maven.

Pandas

For the Python programming language, Pandas is an open-source, BSD-licensed library that offers high-performance, user-friendly data structures and data analysis tools.

According to information on their website, pandas addresses the issue that Python has historically been excellent for data munging and preprocessing but less so for data analysis and modelling. By bridging this gap, pandas enables you to complete all of your data analysis tasks in Python without moving to a more specialised language like R.

Coverage.py

Python projects can have their code coverage evaluated using the utility Coverage.py.

This package was suggested by Kyle Tice in the comments section: "Coverage.py is one of the most well-liked code coverage tools for Python. To calculate coverage, it makes use of tracing hooks and code analysis capabilities included in the Python standard library. It is compatible with the latest releases of CPython, PyPy, Jython, and IronPython. Pytest and unit tests can both use Coverage.py.

PyUnit

You might find UnitTest (PyUnit) a simple transition to the Python ecosystem if you come from the Java world and are familiar to camelCasing, according to Francesco Piscani on LinkedIn.

PyCharm

I'm not sure how, but Daryl Flowers on LinkedIn pointed out that I should have added my preferred IDEs to this list.

You may be familiar with JetBrain's IntelliJ if you are used to utilising Java for automation testing. They also produce the fantastic PyCharm Python-specific IDE for expert coders.

Faker

Have you ever had to automate an application when each test run needed different data?

It can be a hassle. Faker steps in at this point.

Using a faker, you may dynamically generate data such as names, phone numbers, addresses, SSNs, and other types of information that appear to be real. When you need to construct automated tests, this is quite helpful.

There are ones for most languages, but for Python, look at Joke2k's Faker on GitHub. You can create fake data with this Python Faker library.

 

You should attend Andrew Knight's presentation at the Automation Guild on How to Start Testing with Python if you want to learn more about Python Automation Testing Course and want a short introduction to the language. Before looking out the following python testing libraries, this would be a wonderful place to start for you.

Additionally, it has the intelligence to determine which tests to run based on how the files have changed since your previous code repository commit.