MetadataMapper#

class dtcg.datacube.update_metadata.MetadataMapper(metadata_mapping_file_path=None)[source]#

Bases: object

Class for applying CF-compliant metadata to xarray Datasets.

Parameters:

metadata_mapping_file_path (str)

METADATA_SCHEMA#

Validation schema for variable metadata.

Type:

schema.Schema

metadata_mappings#

Dictionary of metadata mappings loaded from a YAML file.

Type:

dict

Attributes

metadata_mappings

Methods

__init__([metadata_mapping_file_path])

Initialise MetadataMapper with a given or default mapping file.

read_metadata_mappings(...)

Load and validate metadata mappings from a YAML file.

update_metadata(dataset, ds_name)

Apply variable and shared metadata to an xarray Dataset.
__init__(metadata_mapping_file_path=None)[source]#

Initialise MetadataMapper with a given or default mapping file.

Parameters:

  • metadata_mapping_file_path (str, optional) – Path to the YAML file containing variable metadata mappings. If None, defaults to ‘metadata_mapping.yaml’ in the current directory.

  • self (MetadataMapper)

read_metadata_mappings(
metadata_mapping_file_path,
)[source]#

Load and validate metadata mappings from a YAML file.

Parameters:

  • metadata_mapping_file_path (str) – Path to the YAML file containing metadata mappings.

  • self (MetadataMapper)

Raises:

schema.SchemaError – If any of the metadata entries fail schema validation.

Return type:

None

update_metadata(dataset, ds_name)[source]#

Apply variable and shared metadata to an xarray Dataset.

Parameters:

  • dataset (xarray.Dataset) – Dataset to which the metadata should be applied.

  • ds_name (str) – Name of dataset.

  • self (MetadataMapper)

Returns:

The input dataset with updated metadata.

Return type:

xarray.Dataset

Warns:

UserWarning – If any dataset variables are missing in the metadata mapping.

Notes

This function adds both per-variable and global metadata attributes. Missing variable mappings are reported as warnings, not errors.