It is no longer surprising to hear that Python is one of the most popular languages among Developers and in the Data Science community. While there are numerous reasons behind Python’s popularity, it is primarily because of two core reasons.

  • Python has a very simple syntax – almost equivalent to the mathematical syntax – and hence, it can be easily understood and learned.

  • It offers extensive coverage (libraries, tools, etc.) for scientific computing and Data Science.

These Python tools can be convenient for many different purposes if you know how to use them right. So, without further delay, let’s look at the best Python tools out there!

Automation Testing Python tools

1. Selenium

Selenium is undoubtedly one of the best Python development tools. It is an open-source automation framework for web applications. With Selenium, you can write test scripts in many other programming languages, including Java, C#, Python, PHP, Perl, Ruby, and .Net.

Furthermore, you can perform tests from any browser (Chrome, Firefox, Safari, Opera, and Internet Explorer) in all of the three major operating systems – Windows, macOS, and Linux. You can also integrate Selenium with tools like JUnit and TestNG for managing test cases and generate reports.

 2. Robot Framework

Robot Framework is another open-source generic test automation framework designed for acceptance testing and acceptance test-driven development (ATTD). It uses tabular test data syntax and is keyword-driven. Robot Framework integrates many frameworks for different test automation requirements.

You can expand the framework’s abilities by further integrating it with Python or Java libraries. Robot Framework can be used not only for web app testing but also for Android and iOS test automation.

 3. TestComplete

TestComplete is an automation testing software that supports web, mobile, and desktop automation testing. However, you must acquire a commercial license to be able to use it. TestComplete also allows you to perform keyword-driven testing, just like Robot Framework. It comes with an easy-to-use record and playback feature.

It supports many scripting languages, including Python, VBScript, and C++ script. Just like Robot Framework, software testers can perform keyword-driven testing. A noteworthy feature of this Python tool is that its GUI object recognition abilities can both detect and update UI objects. This helps reduce the efforts required to maintain test scripts.

Data Science Python tools

4. Scikit-Learn

Scikit-Learn is an open-source tool designed for Data Science and Machine Learning. It is extensively used by Developers, ML Engineers, and Data Scientists for data mining and data analysis. One of the greatest features of Scikit-Learn is its remarkable speed in performing different benchmarks on toy datasets.

The primary characteristics of this tool are classification, regression, clustering, dimensionality reduction, model selection, and preprocessing. It offers a consistent and user-friendly API along with grid and random searches.

 5. Keras

Keras is an open-source, high-level neural network library written in Python. It is highly suited for ML and Deep Learning. Keras is based on four core principles – user-friendliness, modularity, easy extensibility, and working with Python. It allows you to express neural networks in the easiest way possible. Since Keras is written in Python, it can run on top of popular neural network frameworks like TensorFlow, CNTK, and Theano.

 6. Theano

Theano is a Python library designed explicitly for expressing multi-dimensional arrays. It allows you to define, optimize, and evaluate mathematical computations comprising multi-dimensional arrays. Some of its most unique features include its tight integration with NumPy, transparent use of GPU, efficient symbolic differentiation, speed and stability optimizations, dynamic C code generation, and extensive unit-testing, to name a few.

 7. SciPy

SciPy is an open-source Python-based library ecosystem used for scientific and technical computing. It is extensively used in the field of Mathematics, Science, and Engineering. SciPy leverages other Python packages, including NumPy, IPython, or Pandas, to create libraries for common math and science-oriented programming tasks. It is an excellent tool for manipulating numbers on a computer and generate visualized results as well.

 Web Scraping Python tools

8. Beautiful Soup

Beautiful Soup is a Python library for extracting data from HTML and XML files. You can integrate it with your preferred parser to leverage various Pythonic idioms for navigating, searching, and modifying a parse tree. The tool can automatically convert incoming documents to Unicode and outgoing documents to UTF-8 and is used for projects like screen-scraping. It is a great tool that can save you hours of work.

 9. LXML

LXML is a Python-based tool designed for C libraries – libxml2 and libxslt. It is highly feature-rich and one of the most easy-to-use libraries for processing XML and HTML in Python. It facilitates safe and convenient access to libxml2 and libxslt libraries by using the ElementTree API.

 What’s unique is that it combines the speed and XML features of these libraries with the simplicity of a native Python API. Furthermore, it extends the ElementTree API to provide support for XPath, RelaxNG, XML Schema, XSLT, and C14N.

10. Scrapy

Scrapy is an open-source and collaborative framework written in Python. Essentially, it is an application framework used for developing web spiders (the classes that a user defines) that crawl web sites and extract data from them. It is mainly used for extracting the data from websites.

Scrapy is a fast, high-level web crawling and scraping framework that can also be used for many other tasks like data mining, automated testing, etc. It can efficiently run on all three major operating systems, that is, Windows, macOS, and Linux.

Bonus: 11. Urllib

Urllib is a Python package that is designed for collecting and opening URLs. It has various modules and functions to work with URLs. For instance, it uses “urllib.request” for opening and reading URLs that are mostly HTTP; “urllib.error” to define the exception classes for exceptions raised by urllib.request; “urllib.parse” to define a standard interface to fragment Uniform Resource Locator (URL) strings up in components, and “urllib.robotparser” function to create a single class.


These Python tools can cover a wide range of needs and functionalities, irrespective of who is using them. Whether a, Developer, Software Engineer, or Data Scientist these are some of the best Python tools that are used by tech professionals all around the world.

Learn Online PYTHON -EducateNXT




1 year ago

The other day, while I was at work, my cousin stole my iPad and tested to see if it can survive a thirty foot drop, just so she can be a youtube sensation. My iPad is now broken and she has 83 views. I know this is totally off topic but I had to sha



1 year ago

Amazing! Its really amazing post, I have got much clear idea on the topic of from this article. inter milan tröja LilianaSc maglia napoli 2022 prezzo DarrenDre



1 year ago

When someone writes an post he/she retains the image of a user in his/her mind that how a user can be aware of it. Thus that's why this piece of writing is great. Thanks! arsenal trøje MDHLupita sverige tröja 2022 HolleyBoo



1 year ago

I used to be suggested this web site by means of my cousin. I am now not sure whether this post is written by way of him as no one else recognise such exact about my trouble. You're amazing! Thank you! maglia donnarumma ColumbusS manchester tröja Made



1 year ago

Hmm it looks like your website ate my first comment (it was extremely long) so I guess I'll just sum it up what I submitted and say, I'm thoroughly enjoying your blog. I as well am an aspiring blog blogger but I'm still new to everything. Do you hav



1 year ago

Hello there! I just would like to offer you a big thumbs up for your excellent information you have here on this post. I am coming back to your website for more soon. ac milan drakt FallonCan manchester united matchtröja barn ReedTvfpa



1 year ago

Great post. I was checking constantly this blog and I am impressed! Very useful information particularly the last part :) I care for such info a lot. I was looking for this particular info for a long time. Thank you and good luck. paris saint germain



1 year ago

Hello, I want to subscribe for this blog to take newest updates, thus where can i do it please help out. terza maglia ajax DedraMajo maglia arsenal 2022 DoyleEddi


Hello World!

1 year ago