health_tracking package

Submodules

health_tracking.constants module

health_tracking.workouts module

class health_tracking.workouts.Workouts(zip_dump_path: str = '../data/raw/export.zip', unzip_path: str = '../data/interim/apple_health_export', force_unzip: bool = False)

Bases: object

Parse and gives access to Workout data of a Apple Health App dump data. Provides plotting functionalities.

Parameters:

• zip_dump_path (str, optional) – Path to the zipped data dump. Defaults to constants.ZIP_PATH.
• unzip_path (str, optional) – Path to the unzipped data dump. Defaults to constants.UNZIP_PATH.
• force_unzip (bool, optional) – Flag to force unzipping the data again. Can be useful for new data. Defaults to False.

plot(x: str, y: str, plot_type: str, workout_type: str = 'runnings', outlier: (<class 'int'>, <class 'int'>) = None, z: str = None, kind: str = 'reg', xlim: (<class 'int'>, <class 'int'>) = 0.01, show_new_years: bool = True, legend: str = 'brief')

health_tracking.workouts.calc_minutes_per_km(row: pandas.core.frame.DataFrame) → pandas.core.series.Series

Helper function that calculates the pace as minutes per kilometer. Apply via: data_frame.applyc(alc_minutes_per_km, axis=1).

Parameters:row (pd.DataFrame) – Row of workouts pd.DataFrame as pd.Series Returns:New column for workflow DataFrame Return type:pd.Series

health_tracking.workouts.get_new_years_offsets(workout_data_frame: pandas.core.frame.DataFrame) → list

Helper function that computes the offsets for new years since the first workout, in days.

Parameters:workout_data_frame (pd.DataFrame) – Workouts pd.DataFrame Returns:elements are the offsets for new years in days Return type:list

Module contents

class health_tracking.AppleHealthParser(zip_dump_path: str = '../data/raw/export.zip', unzip_path: str = '../data/interim/apple_health_export', force_unzip: bool = False)

Bases: object

Parse and gives access to Apple Health App dump data.

Parameters:

• zip_dump_path (str, optional) – Path to the zipped data dump. Defaults to constants.ZIP_PATH.
• unzip_path (str, optional) – Path to the unzipped data dump. Defaults to constants.UNZIP_PATH.
• force_unzip (bool, optional) – Flag to force unzipping the data again. Can be useful for new data. Defaults to False.

extract_activity_summaries() → pandas.core.frame.DataFrame

Returns ActivitySummary elements.

Returns:of type ActivitySummary or None if empty Return type:pd.DataFrame

extract_clinical_records() → pandas.core.frame.DataFrame

Returns ClinicalRecord elements.

Returns:of type ClinicalRecord or None if empty Return type:pd.DataFrame

extract_correlations() → pandas.core.frame.DataFrame

Returns Correlation elements.

Returns:of type Correlation or None if empty Return type:pd.DataFrame

extract_me() → pandas.core.frame.DataFrame

Returns Me elements.

Returns:of type Me or None if empty Return type:pd.DataFrame

extract_records() → pandas.core.frame.DataFrame

Returns Record elements.

Returns:of type Record or None if empty Return type:pd.DataFrame

extract_workouts() -> (<class 'pandas.core.frame.DataFrame'>, <class 'set'>)

Returns Workout elements and set of all workout existing types. Shortens the workout types.

Returns:of type Workout or None if empty and set of available workout types Return type:(pd.DataFrame, set)

get_export_date() → pandas._libs.tslibs.timestamps.Timestamp

Returns the pd.Timestamp of exporting.

Returns:Export timestamp Return type:pd.Timestamp

class health_tracking.Singleton

Bases: type

Is used as metaclass to achieve a singleton pattern.