mt_metadata.utils.summarize

Created on Tue Feb 23 11:52:35 2021

copyright:: Jared Peacock (jpeacock@usgs.gov)
license:: MIT

This module provides functionality to summarize metadata standards from both legacy BaseDict-based objects and modern Pydantic v2 MetadataBase objects.

The main functions are: - summarize_timeseries_standards(): Legacy function for BaseDict objects - summarize_pydantic_standards(): New function for Pydantic v2 MetadataBase objects - extract_metadata_fields_from_pydantic(): Extract fields from individual Pydantic classes - summarize_standards(): Unified interface supporting both legacy and Pydantic systems

Example usage:

# For Pydantic v2 objects (recommended) >>> df = summarize_standards(metadata_type=”pydantic”)

# Extract fields from individual class >>> from mt_metadata.timeseries import Survey >>> fields = extract_metadata_fields_from_pydantic(Survey)

# Get BaseDict-compatible summary >>> summary = summarize_pydantic_standards()

Attributes

SUMMARIZE_DTYPE

Functions

`extract_metadata_fields_from_pydantic`(metadata_class)	Extract field information from a Pydantic v2 MetadataBase class definition
`collect_basemodel_objects`(module)	Collect all MetadataBase subclasses from a given module.
`summarize_pydantic_standards`([module])	Summarize the standards for metadata using Pydantic v2 MetadataBase classes.
`summary_to_array`(summary_dict[, dtype])	Summarize all metadata from a summarized dictionary of standards
`summary_to_dataframe`(summary_dict)	Convert a summary dictionary to a pandas DataFrame.
`summarize_standards`([module, csv_fn, output_type, dtype])	Summarize standards into a numpy array and write a csv if specified

Module Contents

mt_metadata.utils.summarize.SUMMARIZE_DTYPE

mt_metadata.utils.summarize.extract_metadata_fields_from_pydantic(metadata_class)

Extract field information from a Pydantic v2 MetadataBase class definition and convert it to a format compatible with BaseDict.

Parameters:: metadata_class (type) – A MetadataBase class (not instance)
Returns:: Dictionary with field information compatible with BaseDict
Return type:: dict

mt_metadata.utils.summarize.collect_basemodel_objects(module)

Collect all MetadataBase subclasses from a given module.

Parameters:: module (str) – The module to inspect (e.g., ‘mt_metadata.timeseries’)
Returns:: Dictionary mapping class objects to their names
Return type:: dict[type[MetadataBase], str]

mt_metadata.utils.summarize.summarize_pydantic_standards(module='timeseries')

Summarize the standards for metadata using Pydantic v2 MetadataBase classes. Similar to summarize_timeseries_standards but works with the new Pydantic structure.

Parameters:: module (str, optional) – The module to inspect, by default “timeseries”
Returns:: BaseDict object containing summarized field information
Return type:: BaseDict

mt_metadata.utils.summarize.summary_to_array(summary_dict, dtype=SUMMARIZE_DTYPE)

Summarize all metadata from a summarized dictionary of standards

Parameters:: summary_dict (dict) – Dictionary of summarized standards
Returns:: numpy structured array
Return type:: np.array

mt_metadata.utils.summarize.summary_to_dataframe(summary_dict)

Convert a summary dictionary to a pandas DataFrame.

Parameters:: summary_dict (dict) – Dictionary of summarized standards
Returns:: DataFrame containing the summarized standards
Return type:: pd.DataFrame

mt_metadata.utils.summarize.summarize_standards(module='timeseries', csv_fn=None, output_type='dataframe', dtype=SUMMARIZE_DTYPE)

Summarize standards into a numpy array and write a csv if specified

Parameters:

module (str, optional) – Module to summarize, by default “timeseries”
csv_fn (str or Path, optional) – Full path to write a csv file, by default None

Returns:

If output_type is “array”, returns a numpy structured array. If output_type is “dataframe”, returns a pandas DataFrame.

Return type:

numpy.ndarray | pd.DataFrame