Python is an excellent language for both beginners and experienced coders, which makes it the best choice for most development projects.
Table of Content
- Keras
- Beautiful soup
- Jupyter notebook
- Theano
- Scikit-learn
- Sublime Text
- Sphinx
- Pip
- LXML
- Selenium
Python is very popular with programmers and is the most sought-after language around the globe. Because of this, demand has been increasing at a rapid pace in recent times. Python is an excellent language for both beginners and experienced coders, which makes it the best choice for most development projects. To become a skilled Python programmer, it's important to know the available Python tools. As you read this article, review the most popular 10 must-known Python tools programmers should know in 2022.
1. Keras
Keras is an open-source tool that provides a Python interface for artificial neural networks. It is free and modular, with the ability to reuse code across multiple projects. Other advantages of this framework are that it supports machine learning development with TensorFlow, CNTK and Theano. Keras is a machine learning library that has the capability to emulate the human brain. It also simplifies the creation of deep neural networks and currently supports TensorFlow, Microsoft's Cognitive Toolkit, Theano, and PlaidML among other frameworks.
2. Beautiful soup
Beautiful Soup is a Python package for parsing, finding, and editing parse trees that really take advantage of certain Python features. Convert documents automatically with our new tool. This can save you hours of work & means you don't have to keep answering the same questions again and again.
3. Jupyter notebook
Jupyter Notebook is a favourite destination for data scientists and machine learning engineers, as it helps you write and execute code quickly. All you have to do is run one cell to try it out. Additionally, this Python tool will be one of the best options to consider when it comes to 3D modelling.
4. Theano
If you need to do some mathematical computation and it involves many dimensions, then Theano is perfect for you. It can handle differentiation, different types of computations, testing etc.
5. Scikit-learn
One of the best free Python tools is Scikit-learn. It has features like regression, classification and clustering, which make it invaluable for data analysis models.
6. Sublime Text
Sublime Text is one of those free Python tools that can be used to develop code. It has plugins that you can add to your editor, which provide a range of features, such as auto-complete and much more.
7. Sphinx
Documentation is like a puzzle where you need the right pieces to make it work. Sphinx, a Python tool, can generate numerous files using just a few pieces of information about your project or company. The HTML file for instance gathers all your documentation concerning code and can be browsed in any machine with an Internet connection.
8. Pip
Getting started with Pip is easy. All that you have to do is download it and install it later, preferably with a sound internet connection.
9. LXML
LXML is a Python library specifically for handling XML documents, written in the C programming language. It supports both libxml2 and libxslt (the XML libraries from which it was originally extracted) and has no shortage of features that are missing from other Python libraries. One such example is its support for XPath expressions, without any need to configure the Expressions component explicitly
10. Selenium
Selenium is an open-source automation framework. One of its features is a tool for creating applications and databases. Thus, it can be used widely for computer applications such as computer-assisted learning or multimedia products.
Using this helpful tool, you can now test scripts in a number of different coding languages ? from Java to Python, Ruby and more!
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