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https://github.com/mgrover1/mscar-python-workshop-2022

Python Workshop Materials for MSCAR 2022
https://github.com/mgrover1/mscar-python-workshop-2022

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Python Workshop Materials for MSCAR 2022

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# MSCAR Python Workshop



[![nightly-build](https://github.com/ProjectPythiaCookbooks/cookbook-template/actions/workflows/nightly-build.yaml/badge.svg)](https://github.com/ProjectPythiaCookbooks/cookbook-template/actions/workflows/nightly-build.yaml)

[![Binder](https://mybinder.org/badge_logo.svg)](https://aws-uswest2-binder.pangeo.io/v2/gh/mgrover1/mscar-python-workshop-2022/main?labpath=notebooks)



## Motivation



This material will be used to provide an overview of how to use Python for the atmospheric and climate sciences.



## Authors



[Max Grover](@mgrover1) [Zach Sherman](zssherman) [Scott Collis](@scollis) [Adam Theisen](@AdamTheisen)



### Contributors





  




## Workshop Recording

The recording for this workshop can be found here!



[![MSCAR Python Workshop 2022](https://img.youtube.com/vi/aNeAtaJWA5M/0.jpg)](https://youtu.be/aNeAtaJWA5M)



## Structure



### Radar Data with Py-ART

Within this section, we cover the basics of Py-ART and apply it to a sample analysis workflow.



### Weather Observations with ACT

The Atmospheric data Community Toolkit (ACT) is a helpful tool when working with atmospheric observations! This portion will focus on reading, visualizing, and analyzing observational datasets from the Atmospheric Radiation Measurement user facility.



### Climate Analysis with Pangeo

Our last section covers how to use the Pangeo stack, specifically Intake-ESM, Xarray, and other components to inspect and visualize earth system model data.



## Running the Notebooks

You can either run the notebook using [Binder](https://mybinder.org/) or on your local machine.



### Using on the Pangeo Binder (**Recommended**)



#### 1. Make Sure You Have a Github Account

The first step is to make sure you have a Github Account.



Here is the link if you do have one already:

- [Github account creation link](https://github.com/join)



#### 2. Log into Pangeo Binder

Next, sign in and authenticate the Pangeo Binder, which is the platform we will use for the workshop:

- [Pangeo Binder Link](https://aws-uswest2-binder.pangeo.io)



The JupyterHub instance we use for this course is relatively small in memory and compute power (~10 GB of memory, 2 CPU cores). For more information about all of the open computational resrouces available within the Pangeo community, check out the [Pangeo Cloud](https://pangeo.io/cloud.html) documentation.



#### 3. Launch our Environment

Now that we have our authentication set up, we can access our content!



Use the following link to launch into the binder:

- [Binder Link](https://aws-uswest2-binder.pangeo.io/v2/gh/mgrover1/mscar-python-workshop-2022/main?labpath=notebooks)



If you are having issues with that (ex. it is taking a long time), try using the following link:

```

https://hub.aws-uswest2-binder.pangeo.io/user/{your_github_username}/lab

```

Where you replace `{your_github_username}` with your github username (ex. `mgrover1`)



#### General Binder Advice



The simplest way to interact with a Jupyter Notebook is through

[Binder](https://mybinder.org/), which enables the execution of a

[Jupyter Book](https://jupyterbook.org) in the cloud. The details of how this works are not

important for now. All you need to know is how to launch a Pythia

Cookbooks chapter via Binder. Simply navigate your mouse to

the top right corner of the book chapter you are viewing and click

on the rocket ship icon, (see figure below), and be sure to select

“launch Binder”. After a moment you should be presented with a

notebook that you can interact with. I.e. you’ll be able to execute

and even change the example programs. You’ll see that the code cells

have no output at first, until you execute them by pressing

{kbd}`Shift`\+{kbd}`Enter`. Complete details on how to interact with

a live Jupyter notebook are described in [Getting Started with

Jupyter](https://foundations.projectpythia.org/foundations/getting-started-jupyter.html).



### Running on Your Own Computer

If you are interested in running this material locally on your computer, you will need to follow this workflow:



1. Clone the `https://github.com/mgrover1/mscar-python-workshop-2022` repository:



   ```bash

    git clone https://github.com/mgrover1/mscar-python-workshop-2022.git

    ```  

1. Move into the `mscar-python-workshop-2022` directory

    ```bash

    cd mscar-python-workshop-2022

    ```  

1. Create and activate your conda environment from the `environment.yml` file

    ```bash

    conda env create -f environment.yml

    conda activate mscar-python-tutorial-dev

    ```  

1.  Move into the `notebooks` directory and start up Jupyterlab

    ```bash

    cd notebooks/

    jupyter lab

    ```