Python is one of the most widely accepted programming languages and over the past, Python's application has maximized exponentially. It provides excellent library support and has a large developer community. The programming language is a great starting point for beginners, and several tech startups are also using Python as their primary backend stack. Python is fueling a revolution to bring more people into coding and programming. Do you want to become a better Python programmer in 2022? Are you looking for the best Python tools for Python development? Then you have come to the right place.
Scikit-learn is a free software machine learning tool for the Python programming language. It features various classification, regression, and clustering algorithms with support vector machines. Simple and efficient tools for predictive data analysis. Accessible to everybody and reusable in many contexts. Scikit-learn is one of the best Python tools to learn in 2022.
Keras provides a Python interface for artificial neural networks and acts as an interface for the TensorFlow library. Any Python programmer can learn and understand this tool. Up until version 2.3, Keras supported multiple backends, including TensorFlow, Microsoft Cognitive Toolkit, Theano, and PlaidML.
Theano allows you to define, optimize, and evaluate mathematical computations comprising multi-dimensional arrays. It is one of the best python tools loaded with features like 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. Theano is well-known for building Deep Learning Projects. Programmers should consider this tool for python development.
Next on the list of the top 10 Python tools every programmer should learn in 2022 is SciPy. It is an open-source Python-based tool used for scientific and technical computing. It is built on the NumPy extension and allows Python programmers to manipulate and visualize data with a wide range of high-level commands. SciPy is popular in the field of Mathematics, Science, and Engineering.
Selenium is one of the best Python development tools to learn in 2022. It is an open-source automation framework for web applications that provides a playback tool for authoring functional tests. With Selenium, you can write test scripts in many other programming languages, including Java, C#, Python, PHP, Perl, Ruby, and .Net. Python programmers should definitely learn Selenium in 2022.
Robot Framework is another open-source generic test automation framework designed for acceptance testing and acceptance test-driven development (ATTD). It is a keyword-driven testing framework that uses tabular test data syntax. Robot Framework integrates many frameworks for different test automation requirements.
TestComplete is an automation testing software that supports web, mobile, and desktop automation testing. However, you must acquire a commercial license in order to use it. TestComplete gives testers the ability to create automated tests for Microsoft Windows, Web, Android, and iOS applications.
You can integrate Beautiful Soup 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 projects like screen-scraping. It is a great tool that can save you hours of work.
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.
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 websites and extract data from them. Python developers use Scrapy for extracting data from websites. Scrapy is a fast, high-level web crawling and scraping framework for many other tasks like data mining, automated testing, etc. It can efficiently run on all three major operating systems (Windows, macOS, and Linux).
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