Recommended Libraries for Cyberinfrastructure Users Developing Jupyter Notebooks
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This repository contains information about Jupyter Widgets and how they can be used to develop interactive workflows, data dashboards, and web applications that can be run on HPC systems and science gateways. Easy to build web applications are not only useful for scientists. They can also be used by software engineers and system admins who want to quickly create tools tools for file management and more!
Awesome Jupyter Widgets (for building interactive scientific workflows or science gateway tools)
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A curated list of awesome Jupyter widget packages and projects for building interactive visualizations for Python code
MDAnalysis - Python library for the analysis of molecular dynamics simulations
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MDAnalysis is a python based library of tools for the analysis of molecular dynamics simulations. It is able to read and write many popular simulation formats including CHARMM, LAMMPS, GROMACS, and AMBER and more. This link contains the documentation pages of all MDAnalysis functions and has links to tutorials using Jupyter Notebooks.
Science Gateway Tool/Web App Template (Jupyter Notebook + ipywidgets)
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Use this template to turn any science gateway workflow into a web application!
GPU Computing Workshop Series for the Earth Science Community
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GPU training series for scientists, software engineers, and students, with emphasis on Earth science applications.
The content of this course is coordinated with the 6 month series of GPU Training sessions starting in Februrary 2022. The NVIDIA High Performance Computing Software Development Kit (NVHPC SDK) and CUDA Toolkit will be the primary software requirements for this training which will be already available on NCAR's HPC clusters as modules you may load. This software is free to download from NVIDIA by navigating to the NVHPC SDK Current Release Downloads page and the CUDA Toolkit downloads page. Any provided code is written specifically to build and run on NCAR's Casper HPC system but may be adapted to other systems or personal machines. Material will be updated as appropriate for the future deployment of NCAR's Derecho cluster and as technology progresses.
Research Software Development in JupyterLab: A Platform for Collaboration Between Scientists and RSEs
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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.
OnShape FeatureScripts: Custom features for everyone
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OnShape FeatureScripts allow users to create their own features via OnShape's programming language. The user can make these as simple or complex as they need, and they can save tons of time for heavy OnShape users or complex projects!
How the Little Jupyter Notebook Became a Web App: Managing Increasing Complexity with nbdev
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A tutorial entitled "How the Little Jupyter Notebook Became a Web App: Managing Increasing Complexity with nbdev" presented at SciPy 2023 in Austin, TX. This tutorial is hosted in a series of Jupyter Notebooks which can be accessed in the click of a button using Binder. See the README for more information.
Research Software Engineering Training Materials
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An ongoing collection of RSE training material, workshops, and resources. We are compiling this list as a starting point for future activities. We are especially seeking material that goes beyond basic research computing competency (e.g. what The Carpentries does so well) and is general enough to span multiple domains. Specific tools and technologies used only in one domain, or applicable to only one subset of computing (i.e. HPC) are typically too narrowly focused. When in doubt, submit it to be included or reach out and we’d be happy to discuss.