Python

Python belongs to the most versatile and at the same time beginner-friendly programming languages.
Two Python environments are available on CodeRoom, which cover different areas of application.

Python 3.8 – Server-side Execution

For more extensive programs, data analysis, and scientific applications, a server-side Python-3.8 environment is available.
Here, programs can be executed with powerful libraries.

Available Libraries

• Astropy – Tools for Astronomy and Astrophysics
• Biopython – Libraries for bioinformatics applications
• Geopandas – Extension of Pandas for geographic data
• Matplotlib – Creation of diagrams and visualizations
• NetworkX – Creation, analysis, and visualization of complex networks and graphs
• NumPy – Foundation for numerical and scientific computing
• openpyxl – Reading, writing, and editing Excel files in the .xlsx format
• Pandas – Data structures and tools for data analysis
• Plotly – Interactive diagrams and visualizations for Python 3 with client-side rendering in the browser
• RDKit – Cheminformatics and analysis of chemical structures
• Requests – Simple HTTP requests and web access
• Scikit-learn – Machine learning and data analysis
• SciPy – Scientific and technical calculations
• Statsmodels – Statistical Modeling and Tests
• SymEngine – Symbolic Mathematics

This environment is particularly suitable for data-driven projects, scientific applications, and more complex programs.

Python 2 – Client-Side Execution with Skulpt

For fast experiments directly in the browser, a client-side Python environment based on Skulpt is available.
Programs are executed directly in the browser without requiring a server.

Available Libraries

This environment contains:

• the standard libraries provided by Skulpt
• pygame – for simple game development and graphical applications
• frameCraft – support for interactive learning and project environments

The browser-based Python environment is particularly suitable for:

• first programming experiences
• interactive exercises in the classroom
• small games and graphical experiments

Explore the following articles to discover diverse examples and projects that demonstrate the possibilities of Python in both environments.