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Best Python Tools Every Developer Must Use

It’s not shocking to learn that Python is among the most well-known languages among developers as well as in it’s Data Science community. 

Although there are many reasons for the popularity of Python however, it’s mainly due to two main factors.

  • Python is a simple syntax that is almost identical to the mathematical syntax which means it is easy to comprehend and understood.
  • It also provides comprehensive coverage (libraries tools, libraries and tools, etc.) for scientific computing as well as Data Science.

There are many reasons to utilize Python technology to conduct research and data analysis. 

Today, we’ll discuss the most commonly utilized Python tools used by developers as well as coders as well as Data Scientists across the world.

These Python tools can be useful for a myriad of reasons if you can make them work. 

Therefore, with no any further delay, let’s take a take a look at the top Python tools available!

Best Python Tools You Must Have To Know

1) Scikit-Learn

Scikit-Learn is an open-source software developed to support Data Science and machine learning. 

It is widely utilized by Developers, ML Engineers, and Data Scientists for data mining and analysis of data. 

One of the best advantages of Scikit-Learn is its speedy performance in running different benchmarks on toy data sets.

The most important features of this software are classification, regression clustering, dimensionality reduction models selection and preprocessing. 

It has a consistent and user-friendly API, as well as grids and random search results.

2) Keras

Keras is an open source, advanced neural networks library that is written using Python. 

It is well-suited to ML as well as Deep Learning . 

Keras is built upon four fundamental principles: modularity, user-friendliness, simple extension, and working with Python. It lets you create neural networks the most straightforward way that is possible. 

Because Keras was written using Python it runs on top of well-known neural network frameworks such as TensorFlow, CNTK, and Theano.

3.) Theano

Theano is A Python library that was specifically designed to assist in creating multi-dimensional arrays. 

It lets you define the, optimize and then evaluate mathematical operations that comprise multi-dimensional arrays. 

Its most distinctive highlights include its tight integration with NumPy as well as its the use of a transparent GPU effective symbolic differentiation speed and stability optimizations and active C code generation and extensive unit-testing just to name just a few.

4.) SciPy

SciPy is an open source Python library that is utilized to perform scientific and technical computation. 

It is widely utilized in the fields of mathematics, science, and Engineering. SciPy makes use of other Python applications, like NumPy, IPython, or Pandas, to create libraries for the most common mathematics and science-based programming. 

It’s a fantastic tool to manipulate numbers on a PC and produce visual results too.

Automatization Testing Python tools

5) Selenium

Selenium is without doubt one of the top Python software tools for developing. 

This is an open source automation tool that can be used for web-based applications. 

With Selenium it is possible to create test scripts using many other programming languages like Java, C#, Python, PHP, Perl, Ruby, and .Net.

Additionally, you can run tests with all browsers (Chrome, Firefox, Safari, Opera, and Internet Explorer) on all of the three operating systems: Windows, macOS, and Linux. 

Selenium can also be integrated with tools such as JUnit and TestNG to manage tests and generating reports.

6.) Robot Framework

Robot Framework is another open-source generic test automation framework developed for acceptance testing and testing driven development (ATTD). 

It utilizes test data syntax that is tabular and is driven by keywords. Robot Framework incorporates several frameworks for various testing automation needs.

It is possible to expand the framework’s capabilities by further integrating to Python as well as Java library. 

Robot Framework is a great tool not only for web-based app testing, but it can also be used to automate test automation for Android and iOS testing automation.

7) TestComplete

TestComplete is an automation test software that allows mobile, web and desktop automated testing. 

It is required to purchase an commercial license in order for the right to use it. 

TestComplete can also conduct keyword-driven tests, much as Robot Framework. 

It also comes with a simple-to-use recording and playback feature.

It is compatible with a variety of scripting languages like Python, VBScript, and C++ script. 

Similar to Robot Framework, software testers can run tests using keywords. 

One of the most notable features in the Python software is the fact that it’s GUI ability to recognize objects simultaneously detect and modify UI objects. 

This reduces the time needed to keep test scripts up-to-date.

Web Scraping Python tools

Here we will discuss best python tools for web scraping.

8.) Gorgeous Soup

Beautiful Soup Beautiful Soup is Beautiful Soup is a Python library that extracts information in HTML as well as XML files. 

It is possible to integrate it with the parser you prefer to use a variety of Pythonic phrases for navigation through, searching, and altering the parse tree. 

This tool is able to convert documents that are received to Unicode and documents that are sent out to UTF-8. 

It can also be employed in projects like screen-scraping. It’s a fantastic tool that will make your life easier.


LXML is a Python-based application developed to work with C libraries namely libxml2 and the libxslt. 

It’s extremely feature-rich and is among the easiest libraries to use to process XML or HTML within Python. 

It allows safe and secure access to libxslt and the libxml2 libraries using an ElementTree API.

It is unique in that it blends its speed as well as XML capabilities of these libraries, with the ease of the native Python API. 

In addition it expands it’s ElementTree API to provide support for XPath, RelaxNG, XML Schema, XSLT, and C14N.

10) Scrapy

Scrapy is an open source, cooperative framework developed in Python. It is essentially an application framework that is used to create web crawlers (the classes that the user creates) that search for web pages and extract information from these. 

It is mostly employed to extract the information from websites.

Scrapy is a speedy high-level web crawling, high-level scraping framework which can be utilized for a variety of other tasks , including automatized testing, data mining and so on. 

It runs efficiently across all three major operating systems, which are, Windows, macOS, and Linux.

11.) Urllib

Urllib is an Python program that was designed to collect and open URLs. It comes with a variety of functions and modules that deal with URLs. 

It uses, for instance “urllib.request” to open and reading URLs that are primarily HTTP; “urllib.error” to define the exception classes that are used for the exceptions that are raised in urllib.request; “urllib.parse” to create a standard interface to split Uniform Resource Locator (URL) strings into components and “urllib.robotparser” function that creates one class.

The Wrapping Up

Here we have discussed best tools which every Python developers should use for their web development project.

These Python tools are able to meet an array of requirements and functions, regardless of the person using them. 

If you’re an Data Scientist or Developer or software Engineer These are the top Python tools which are utilized by professionals in tech all over the globe.

Hope this article will help you to meet with your requirements.


Kosha Shah is a digital strategist at Technostacks Infotech, a top web, mobile, and python development company in India, USA, and UK. She writes engaging blog topics for trends, mobile, and industry software news.

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