We use pyproject.toml
with pip
to "deploy" fireatlas locally inside your environment:
$ git clone <this-repo> fireatlas
$ cd fireatlas/
# note that '-e' allows you to edit your code and all changes will be available without reinstall
$ pip install -e .
# or if you need testing infrastructure too
$ pip install -e '.[test]'
There are two different environments where you can run all algorithm steps: JupyterHub and MAAP-DPS
-
If you have accesss to JupyterHub then you can interactively walk through the notebooks in the
/notebooks
directory (see Notebook Docs) -
Or if you'd rather just run one script that coordinates all the work for you in the right order with dask parallelism then you can run
fireatlas/FireRunDaskCoordinator.py
DPS is an async task runner. For more info read the docs
-
You can run individual steps asynchronously on DPS via the notebook at
/maap_runtime/dps-interactive-coordinator.ipynb
-
Or you can kick off all steps in a single DPS job via the last step in the notebook at
/maap_runtime/dps-coordinator.ipynb