Visual Python

PyPI version
Python: 3.x
License: GPLv3
Code of Conduct: Contributor Covenant


Visual Python is a GUI-based Python code generator, developed on the Jupyter Notebook as an extension.
Visual Python is an open source project started for students who struggle with coding during Python classes for data science.

Try Visual Python if you would like to:

  • manage big data with minimal coding skills.
  • help students / business analysts / researchers to overcome learning barriers for Python.
  • save & reuse repeatedly used codes(snippets).

Getting Started

1. Requirements

Visual Python is a Jupyter Notebook extension.
We recommend installing Anaconda (virtual environment).

  • Python version 3.x
  • Jupyter notebook or Anaconda env

2. How to Install

1) Open Anaconda prompt

  • Windows : Click Start > Search or Select ‘Anaconda Prompt’
  • Mac : Open Launchpad > Select ‘Terminal’

2) Install package from

pip install visualpython

NOTE : Depending on your virtual environment settings, you may need to install Jupyter Extensions.
To install Jupyter Extension, use commands either:

pip install jupyter_contrib_nbextensions


conda install -c conda-forge jupyter_contrib_nbextensions

3) Enable the package

visualpy install

NOTE : If you are using multiple versions of Python, specify the pip version as 3 like the following.

visualpy install --pip3 

4) Activate Visual Python on Jupyter Notebook

Click orange square button on the right side of the Jupyter Notebook menu.

3. Package Control Info

  • Usage: visualpy [option]
  • Optional arguments:

help       - show help menu
install    - install packages
uninstall  - uninstall packages
upgrade    - version upgrade
version    - version check


If you are interested in contributing to the Visual Python, please see
All skills from programmers, non-programmers, designers are welcomed.


GNU GPLv3 with Visual Python special exception (See LICENSE file).

Mission & Vision

To support technology and education so that anyone can leverage big data analytics to create a variety of social values.

To create an environment where everyone can learn and use big data analytics skills easily.

Support Visual Python

Love Visual Python?
Your support will help us continue to actively develop and improve Visual Python.☕


View Github