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. They are listed in the order that they are executed (see image in Configuring Tsdat).

hook_customize_dataset	User-overrideable code hook that runs after the retriever has retrieved the dataset from the specified input keys, but before the pipeline has applied any quality checks or corrections to the dataset.
hook_finalize_dataset	User-overrideable code hook that runs after the dataset quality has been managed but before the dataset has been sent to the storage API to be saved.
hook_plot_dataset	User-overrideable code hook that runs after the dataset has been saved by the storage API.

The plotting hook (hook_plot_dataset) is likely to be the most useful for users. This hook creates plots and saves them to the storage directory with the output dataset and is a good way to check the pipeline output. Below is shown a custom plotting example:

def hook_plot_dataset(self, dataset: xr.Dataset):
    # DEVELOPER: (Optional, recommended) Create plots.
    location = self.dataset_config.attrs.location_id
    datastream: str = self.dataset_config.attrs.datastream

    date, time = get_start_date_and_time_str(dataset)

    plt.style.use("default")  # clear any styles that were set before
    plt.style.use("shared/styling.mplstyle")

    with self.storage.uploadable_dir(datastream) as tmp_dir:

        fig, ax = plt.subplots()
        dataset["example_var"].plot(ax=ax, x="time")  # type: ignore
        fig.suptitle(f"Example Variable at {location} on {date} {time}")
        format_time_xticks(ax)
        plot_file = get_filename(dataset, title="example_plot", extension="png")
        fig.savefig(tmp_dir / plot_file)
        plt.close(fig)

class tsdat.pipeline.pipelines.IngestPipeline(*, parameters: Any = {}, settings: Any = None, triggers: List[Pattern] = [], retriever: tsdat.io.base.Retriever, dataset: tsdat.config.dataset.DatasetConfig, quality: tsdat.qc.base.QualityManagement, storage: tsdat.io.base.Storage)

Pipeline class designed to read in raw, unstandardized time series data and enhance its quality and usability by converting it into a standard format, embedding metadata, applying quality checks and controls, generating reference plots, and saving the data in an accessible format so it can be used later in scientific analyses or in higher-level tsdat Pipelines.

hook_customize_dataset(dataset: xarray.core.dataset.Dataset) → xarray.core.dataset.Dataset

User-overrideable code hook that runs after the retriever has retrieved the dataset from the specified input keys, but before the pipeline has applied any quality checks or corrections to the dataset.

Parameters

• dataset (xr.Dataset) – The output dataset structure returned by the retriever

• API. –

Returns

The customized dataset.

Return type

xr.Dataset

hook_finalize_dataset(dataset: xarray.core.dataset.Dataset) → xarray.core.dataset.Dataset

User-overrideable code hook that runs after the dataset quality has been managed but before the dataset has been sent to the storage API to be saved.

Parameters

• dataset (xr.Dataset) – The output dataset returned by the retriever API and

• by the hook_customize_retrieved_dataset user code hook. (modified) –

Returns

The finalized dataset, ready to be saved.

Return type

xr.Dataset

hook_plot_dataset(dataset: xarray.core.dataset.Dataset)

User-overrideable code hook that runs after the dataset has been saved by the storage API.

Parameters

dataset (xr.Dataset) – The dataset to plot.