What are the commonly used python programming software?

The main types of Python development software are: integrated development environment (IDE), code editor, interpreter, library and framework. IDEs provide comprehensive development environments (e.g. PyCharm, Visual Studio Code), code editors are used to write code (e.g. Atom, Vim), interpreters execute code (e.g. CPython, Jython), and libraries and frameworks provide pre-written code (e.g. NumPy, Scikit-learn, Django).

Commonly used Python programming software

Python is a popular programming language suitable for various application scenarios . There are many software tools available for Python development, each offering different features and benefits.

Integrated Development Environment (IDE)

The IDE provides a comprehensive development environment for writing, debugging, and deploying Python code.

• PyCharm: Professional-grade IDE that provides advanced code editing, code analysis and debugging tools.
• Visual Studio Code: Popular and open source IDE with excellent code navigation and extension support.
• Sublime Text: A lightweight and customizable text editor with syntax highlighting and code snippet support.

Code Editor

The code editor is used for writing and editing Python code, but has less functionality than an IDE.

• Atom: An open source text editor with strong package management and community support.
• Vim: A powerful text editor that provides efficient code editing and navigation.
• Emacs: Another powerful text editor with extensive customizability and extensibility.

Interpreter

The interpreter is the software used to execute Python code.

• CPython: The official interpreter for Python, written in C language.
• Jython: A Java-based Python interpreter that allows Python code to interoperate with Java code.
• IronPython: A Python interpreter based on the Microsoft .NET Framework that allows Python code to interoperate with .NET code.

Libraries and Frameworks

Libraries and frameworks provide pre-written code that can be used to extend Python functionality.

• NumPy: Scientific computing library for processing multi-dimensional arrays and matrices.
• Pandas: Data analysis and processing library for manipulating data frames and time series.
• Scikit-learn: Machine learning library, providing various machine learning algorithms and models.
• Django: Web framework for creating dynamic and interactive web applications.
• Flask: Microframework for building lightweight web applications.

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