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We are migrating! Check out https://nasa-sarp.github.io/sarp_lessons for the latest content -- A repository to support the NASA SARP internship programming curriculum

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SARP Lessons Update

SARP Lessons is in the process of migrating to the NASA-SARP github org. We're excited to be expanding. Check out https://nasa-sarp.github.io/sarp_lessons for the most up-to-date content.


SARP Lessons

This repository holds the less content that is used for instruction during the NASA Student Airborne Research Program (SARP) summer internship.

Organization

The content is organized into a few folders:

  1. lessons - notebooks used in an organized lecture format. Each one also has practice problems
  2. additional_lectures - supplemental notebooks used throughout the summer for quick code talks. No practice problems
  3. snippets - useful pieces of code that were written to support student project, but aren't always organized well or consistently commented
  4. language_agnostic_content - PDFs that were used to teach coding concepts broader than just sytnax

Environments

The environment.yml file in the root directory builds an enviroment that can be used to execute the notebooks. There is not currently an environment.yml for building the docs, but one could be make by starting with the student environment.yml environment and then adding conda install -c conda-forge jupyter-book. You may also need to install some sphinx extensions.

Getting Setup (Student)

Instructions and environment for building the docs are in the docs/ folder

If you are running this on a SARP laptop then great news - you are already set up! If you are getting set up on a personal computer you can follow the steps below to create a coding environment there.

  1. Install Anaconda Go to the Anaconda website, find your operating system, and follow the instructions. This step puts a version of Python on your computer that you will use for analysis. Anaconda is also an environment manager and a package manager.

  2. Configure your base environment Part A Add conda-forge as an anaconda channel.

conda config --add channels conda-forge

Part B Install jupyter lab, as well as an additional library that allows juptyer lab to see other conda environments on your system.

conda install -n base nb_conda_kernels
conda install -n base -c conda-forge jupyterlab

After installing the two packages above, you can set conda-forge to be your default channel.

conda config --set channel_priority strict

Note: You could do this step right after adding conda-forge as a channel, but some issues have been reported due to nb_conda_kernels using the Conda Forge installation in this case. The safest route is to set the channel priority after installing nb_conda_kernels and jupyterlab.

  1. Create a work environment From the root of this repository, run the command:
conda env create -f environment.yml

This will create a new enviornment called sarp with all the packages that are used in this repository in it. It may take several minutes for the dependencies to solve.

Opening your work environment

From a new command line window (or your base conda environment) run:

jupyter-lab

A new Jupyter Lab session should open! When prompted to choose an enviroment, or anytime you create a new notebook, select Python [conda env:sarp] as the kernel.

Happy coding!

Developer Notes

Running the book

  • conda activate sarp_docs
  • jupyter-book build . from root
  • python -m http.server --directory _build/html/

Deploy

link

  1. Build book jupyter-book build .
  2. trigger the ghp-import utility to do its magic ghp-import -n -p -f _build/html

About

We are migrating! Check out https://nasa-sarp.github.io/sarp_lessons for the latest content -- A repository to support the NASA SARP internship programming curriculum

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