New Tethys App Project

Last Updated: May 2022

1. Generate Scaffold

Tethys Platform provides an easy way to create new app projects called a scaffold. The scaffold generates a Tethys app project with the minimum files and the folder structure that is required (see App Project Structure).

Create a new app for this tutorial as follows:

  1. Activate the Tethys conda environment:

    conda activate tethys
  2. Scaffold a new app named dask_tutorial:

    tethys scaffold dask_tutorial

2. Add App Dependencies to install.yml

App dependencies should be managed using the install.yml instead of the This app will require the dask and tethys_dask_scheduler packages. Both packages are available on conda-forge, which is the preferred Conda channel for Tethys. Open tethysapp-dask_tutorial/install.yml and add these dependencies to the requirements.conda section of the file:

# This file should be committed to your app code.
version: 1.0
# This should match the app - package name in your
name: dask_tutorial

  # Putting in a skip true param will skip the entire section. Ignoring the option will assume it be set to False
  skip: false
      - conda-forge
      - dask
      - tethys_dask_scheduler



3. Development Installation

Install the app and it's dependencies into your development Tethys Portal. In a terminal, change into the tethysapp-dask_tutorial directory and execute the tethys install -d command.

cd tethysapp-dask_tutorial
tethys install -d

5. View Your New App

  1. Start up the development server to view the new app:

tethys manage start


To stop the development server press CTRL-C.

If you get errors related to Tethys not being able to connect to the database, start the database by running:

tethys db start

You can also stop the Tethys database by running:

tethys db stop
  1. Browse to in a web browser and login. The default portal user is:

  • username: admin

  • password: pass

6. Dask

Documentation for Dask may be found at

Dask is a tool for natively scaling and parallelizing python. It can broadly be categorized into dynamic task scheduling, and "big data" collections.

Dask Delayed tasks operate lazily. This means that execution is split onto a separate thread for completion and then return.

Dask Distributed is a tool for managing a medium sized cluster. See