Pipeline Code Hooks

Each pipeline base class provides certain methods which the developer can override if desired to customize pipeline functionality. In your template repository, your Pipeline class will come with all the hook methods stubbed out automatically (i.e., they will be included with an empty definition).

The following hook methods (which can be easily identified because they all start with the hook_ prefix) are provided in the pipeline-template found in the pipelines/<ingest_name>/pipeline.py file.

1. hook_customize_dataset
2. hook_finalize_dataset
3. hook_plot_dataset

Code hooks are executed according to this image:

Most users will only want to customize the plotting hook (hook_plot_dataset). This hook creates plots and saves them to the storage area. Below is a simple example:

def hook_plot_dataset(self, dataset: xr.Dataset):
    with plt.style.context("shared/style.mplstyle"): # (1)!
        fig, ax = plt.subplots()
        dataset["example_var"].plot(ax=ax, x="time")  # type: ignore
        fig.savefig(self.get_ancillary_filepath(title="example_plot"))
        plt.close(fig)

1. Optional: You can use plt.style.context() with a matplotlib stylesheet or the path to your own stylesheet to temporarily clear other styles and set the styles / rcParams for your plots.

Note

Be sure to use the self.get_ancillary_filepath() method to ensure that:

• the plot filename is standardized according to your storage configurations
• the pipeline knows to save this file when it syncs with the storage area later