climepi.app.run_app#

climepi.app.run_app(clim_dataset_example_base_dir=None, clim_dataset_example_names=None, enable_custom_clim_dataset=False, custom_clim_data_dir=None, epi_model_example_names=None, enable_custom_epi_model=True, dask_distributed=False, **kwargs)[source]#

Run the climepi front-end application locally.

Parameters:

  • clim_dataset_example_base_dir (str or pathlib.Path) – Base directory for the example climate datasets, optional. If None, the datasets will be downloaded to and accessed from the OS cache.

  • clim_dataset_example_names (list of str) – List of example names for climate datasets, optional. If None, the default list in climdata.EXAMPLE_NAMES is used.

  • enable_custom_clim_dataset (bool) – Whether to enable the option to load a custom climate dataset. Default is False. If True, xarray.open_mfdataset() will be called on all netCDF files in the directory specified by custom_clim_data_dir if the loading of custom data is triggered.

  • custom_clim_data_dir (str or pathlib.Path) – Directory containing the custom climate dataset. Must be specified if enable_custom_clim_dataset is True.

  • epi_model_example_names (list of str) – List of example names for epidemiological models, optional. If None, the default list in epimod.EXAMPLE_NAMES is used.

  • enable_custom_epi_model (bool) – Whether to enable the option to specify a custom temperature range in which transmission can occur. Default is True.

  • dask_distributed (bool) – Whether to use the Dask distributed scheduler. Default is False. If False, the Dask single-machine scheduler using threads will be used. To use the distributed scheduler, a Dask local cluster must be started from a separate terminal by running python -m climepi.app.cluster before starting the app.

  • **kwargs – Additional keyword arguments to pass to panel.serve().

Returns:

panel.io.server.Server or panel.io.threads.StoppableThread – The server or thread running the app (return value of panel.serve()).