bhf_smarthealth.parse.healthapp_parser

This module contains functions to process raw Health App daily summary data ingressed to the Smart Health pipeline

Attributes

logger

Functions

load_json(→ dict[str, Any])	Load the raw JSON file, reshape it into a flat dictionary, and validate
validate_data(...)	Uses Pydantic model to convert and validate the dictionary containig the raw data.
create_dataframes(→ dict[str, pandas.DataFrame])	Creates the metrics and workouts dataframes from the Pydantic model.

Module Contents

bhf_smarthealth.parse.healthapp_parser.logger

bhf_smarthealth.parse.healthapp_parser.load_json(json_path: str | pathlib.Path) → dict[str, Any]

Load the raw JSON file, reshape it into a flat dictionary, and validate data consistency against filename metadata.

The function extracts the sheffield_id and date from the filename and validates the metadata.

Parameters:

json_path (str | Path) – Path to the data file to be processed.

Returns:

A dictionary containing the raw, unvalidated Health App daily summary data, with the extracted file metadata (sheffield_id and date) appended

Return type:

dict[str, Any]

Raises:

JSONStructureError – Raised if the JSON file does not contain the expected keys

bhf_smarthealth.parse.healthapp_parser.validate_data(data_dict: dict[str, Any]) → bhf_smarthealth.validate.healthapp_schema.HealthAppSummaryData

Uses Pydantic model to convert and validate the dictionary containig the raw data.

Parameters:

data_dict (dict[str, Any]) – Dictionary of the raw data

Returns:

Pydantic model class containing the validated data

Return type:

HealthAppSummaryData

Raises:

DataValidationError – Raised if the pydantic schema validation fails

bhf_smarthealth.parse.healthapp_parser.create_dataframes(validated_data: bhf_smarthealth.validate.healthapp_schema.HealthAppSummaryData) → dict[str, pandas.DataFrame]

Creates the metrics and workouts dataframes from the Pydantic model.

Parameters:

validated_data (HealthAppSummaryData) – Pydantic model class containing the validated data

Returns:

A dictionary containing the “metrics” and “workouts” DataFrames

Return type:

dict[str, pd.DataFrame]