Interactive computing environment (Jupyter)
Jupyter offers interactive environments for hosting R, python, and a number of other languages for creating reproducible software experiment.
Description
Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages.
There are two main components:
JupyterLab
JupyterLab is a web-based interactive development environment for Jupyter notebooks, code, and data. JupyterLab is flexible: configure and arrange the user interface to support a wide range of workflows in data science, scientific computing, and machine learning. JupyterLab is extensible and modular: write plugins that add new components and integrate with existing ones.
Jupyter Notebook
The Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, data visualization, machine learning, and much more.
Where do I go for help?
Olexandr can assist in the following areas:
- Advice on installation
- User training
- Best practice in using Jupyter efficiently
- Helping with sharing the reproducible experiments
Email Olexandr directly for advice.
Alternatively Olexandr is a founder of the Research Software Microsoft Team. This is free to join and offers open discussions on all aspects of research software development.
Service location
Service cost
Free
Are there limits to the service?
No support offered for coding help however the Research Computing Team can assist with software developments.
Expertise level required to use this service
Novices would be advised to take a software carpentry workshop.
Example / Use case for this service
Jupyter Notebooks For Reproducible Research https://github.com/olexandr-konovalov/repro-jupyter