Top Python Tools Every Python Developer Must Know About

Top Python Tools Every Python Developer Must Know About

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Here are the Top Tools that Every Python developer should know about. 

Today, we’re going to talk about some of the Python tools that developers, coders, and Data Scientists all over the world use the most. Check out our data science certifications from top universities if you are just starting out and want to learn more about data science. 

If you know how to use these Python tools can be helpful for many different tasks. So, dont waste any more time and look at the best Python tools! To get in-depth knowledge of python development tools, stick with Python Training in Chennai.

Tools for Data Science in Python 


Scikit-Learn is an open-source tool for Data Science and Machine Learning. Developers, ML Engineers, and Data Scientists use it to mine and analyse data. Scikit-speed learning when running different benchmarks on toy datasets is one of its best qualities. 

This tool’s main features are classification, regression, clustering, dimensionality reduction, model selection, and preprocessing. It has a consistent API that is easy to use, grid, and random searches.


Keras is a top-end neural network library written in Python that is free and open source. It works well for Machine Learning and Deep Learning. 

Keras is based on four main ideas: being easy to use, being modular, being easy to extend, and working with Python. It gives you the easiest way to describe neural networks. Because Keras is written in Python, it can run on top of popular neural network frameworks like TensorFlow, CNTK, and Theano. 


Theano is a Python library that expresses arrays with more than one dimension. It lets you define, optimise, and evaluate multi-dimensional array-based mathematical computations. Some of its best features are 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. 


SciPy is an open-source library ecosystem built on Python that is used for scientific and technical computing. It’s used a lot in math, science, and engineering. SciPy uses other Python packages like NumPy, IPython, and Pandas to make libraries for common programming tasks in math and science. It is the best tool for working with numbers on a computer and getting results that can be seen. 

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Testing Python tools with automation 


Selenium is the best tool for developing with Python. It is an automation framework for web apps that is free to use. You can write test scripts in Java, C#, Python, PHP, Perl, Ruby, and.Net, among other languages, Selenium. 

Also, you can run tests from any browser (Chrome, Firefox, Safari, Opera, and Internet Explorer) on Windows, macOS, and Linux, the three most popular operating systems. You can also use tools like JUnit and TestNG with Selenium to manage test cases and make reports.

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Robot Framework 

Robot Framework is another open-source generic test automation framework for acceptance testing and acceptance test-driven development (ATTD). It works with tabular test data syntax and is driven by keywords. Robot Framework combines many test automation frameworks to meet different needs. 

Adding more Python or Java libraries can make the framework do more. Robot Framework can be used to test web apps, but it can also be used to automate tests for Android and iOS apps. 

Wrapping Up 

No matter who uses them, these Python tools can meet a wide range of needs and do many different things. These are some of the best Python tools that tech professionals worldwide use, whether they are Data Scientists, Developers, or Software Engineers. Check out the Python Training in Bangalore at FITA Academy if you want to learn Python and get hands-on experience with different tools and languages. 

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