geocomputing

This is the main repository for Agile's geocomputing courses.

Requirements

In order to build files, you will need the following:

• Python 3.9+.
• The course-building package, kosu. To install it:

shell pip install kosu

Usage

To see high-level help:

kosu --help

Usage of build

Run kosu on the command line to build the geocomp (Intro to Geocomputing) class:

kosu build geocomp

You can build any course for which a YAML file exists. So the command above will compile the course specified by geocomp.yaml.

All of the commands can take the option --all. This will apply the command to all of the courses listed under all in .kosu.yaml. In this case, don't pass any individual course name.

In addition, you can pass the following options:

• --clean / --no-clean — Whether to delete the build files. Default: clean.
• --zip / --no-zip — Whether to create the zip file for the course repo. Default: zip.
• --upload / --no-upload — Whether to upload the zip file to geocomp.s3.amazonaws.com. Default: no-upload. Note that this requires AWS credentials to be set up on your machine.
• --clobber / --no-clobber — Whether to silently overwrite existing ZIP file and/or build directory. If no-clobber, the CLI will prompt you to overwrite or not. Default: no-clobber.

To build the machine learning course, silently overwriting any existing builds on your system:

kosu build geocomp-ml --clobber

Usage of clean

Cleans the build files for a course. I.e. everything in build and its ZIP file.

kosu clean geocomp-ml

Usage of publish

Publish a course, or those listed in all.yaml. The ZIP file(s) will be uploaded to AWS. For example, to publish all the courses:

kosu publish --all

Usage of test

Tests that a specific course builds, leaving no sawdust, or use the --all option to test all courses in all.yaml. This command builds a course, does not make a ZIP, does not uplad anything, and removes the build folder. (To keep the build folder or make a zip, use the build command with the appropriate options, see above.) Here's how to test the machine learning course:

kosu test geocomp-ml

There is an option --environment that will also generate an environment file called environment-all.yml. (This is used for automated testing on GitHub.)

In general, if a course does not build, the script will throw an error. It does not try to deal with or interpret the error or explain what's wrong.

Example control file

A course must have a YAML control file containing something like the following example of a 2-day course:

yaml title: Introduction to Python for Geologists environment: geogeol # Only if different from course name. conda: # Extra conda packages, as well as all of standard geocomp env. - verde pip: # Extra pip packages. - striplog data: - sussex.zip # Will be unzipped. - B-41_tops.txt data_url: https://geocomp.s3.amazonaws.com/data/ # This is the default value. scripts: - utils.py # Added to `master` and `notebooks` folders (not `demos`). curriculum: 1: # Day 1. - Course overview - The Python interpreter and the IPython environment - Jupyter Notebooks - Intro_to_Python.ipynb - Check out and feedback 2: # Day 2. - Check in and review - Intro_to_Python.ipynb # .ipynb files will be added to `notebooks`. - Check out and feedback extras: # These will be added to `notebooks` and listed in the Curriculum. - Intro_to_NumPy.ipynb - Seismic_data_basics.ipynb - Pandas_for_data_management.ipynb - Read_and_write_LAS.ipynb demos: # These will be added to `demos` and NOT listed in the Curriculum. - Birthquake.ipynb - Volumetrics_and_units.ipynb

Only title and curriculum are required fields.