# Python

Python support in the canvas environment is robust, offering comprehensive functionality for a variety of projects, including those focused on data science. The canvas is designed to integrate seamlessly with all Python functions, ensuring that users can leverage the full power of Python's capabilities. 

It features block-level output similar to Jupyter notebooks, providing an intuitive and interactive way to code. However, the canvas offers a more stable environment, reducing the potential for errors and disruptions during complex computations and analyses.

<figure><img src="/files/jPe7ZivH0iBn5kFnxbrs" alt=""><figcaption><p>Python block</p></figcaption></figure>

To learn how to integrate a new package into the canvas, follow the detailed guide provided. Python blocks offer compatibility with Python 3, supporting an extensive array of Python packages.&#x20;

For a comprehensive list of supported packages and step-by-step instructions on adding new ones, refer to the official [documentation](/guide/canvas-view/installing-packages/requirements.md). Rest assured, with Python's robust package support, you'll have the tools needed to effectively enhance your coding environment.


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