Research Software Development in JupyterLab: A Platform for Collaboration Between Scientists and RSEs

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Title: Research Software Development in JupyterLab: A Platform for Collaboration Between Scientists and RSEs
Category: Learning
Skill Level:
Beginner (304), Intermediate (305)

Description:
Iterative Programming takes place when you can explore your code and play
with your objects and functions without needing to save, recompile, or leave
your development environment. This has traditionally been achieved with a
REPL or an interactive shell. The magic of Jupyter Notebooks is that the
interactive shell is saved as a persistant document, so you don't have to
flip back and forth between your code files and the shell in order to program
iteratively.

There are several editors and IDE's that are intended for notebook
development, but JupyterLab is a natural choice because it is free and open
source and most closely related to the Jupyter Notebooks/iPython projects.
The chief motivation of this repository is to enable an IDE-like development
environment through the use of extensions. There are also expositional
notebooks to show off the usefulness of these features.


Link to Resource:
- JupyterLabIDE GitHub Repository (https://github.com/Accessible-Data-and-Code/jupyterlab-ide)

Tags:
ai (271), visualization (781), big-data (4), data-analysis (422), deep-learning (303), machine-learning (272), astrophysics (297), data-science (688), novel-accelerators (790), computational-chemistry (81), genomics (537), materials-science (516), gravitational-waves (597), oceanography (331), particle-physics (295), physiology (507), psychology (586), quantum-computing (574), quantum-mechanics (281), biology (515), open-ondemand (249), science-gateway (28), c++ (321), jupyterhub (214), python (69), r (32)

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