visualpython 2.2.7

Visual Python is a GUI-based Python code generator, developed on the Jupyter Notebook as an extension.

Introduction

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

3) Enable the package

visualpy install

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

Contributing

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

• Programming Guide: Developer Documentation
• GUI Design Guide: Visual Python GUI Kit 1.0

License

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

Mission & Vision

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

Vision
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.☕