datopy.modeling.apply_recursive#

apply_recursive( func: Callable[[...], Any], obj, ) → dict[str | int, Any] | Any[source]#

Convert a nested data structure (with explicit or implied key/value pairs) into a tree-like dictionary, applying a given function to terminal values.

Parameters:

func (Callable[…, Any]) – _description_
obj – _description_

Returns:

_description_

Return type:

dict

Examples

>>> from datopy.modeling import apply_recursive

Define the data

>>> nested_data =  {'type': 'album', 'url': 'link.com', 'audio_features': [
...     {'loudness': -11.4, 'duration_ms': 251},
...     {'loudness': -15.5, 'duration_ms': 284}]}
>>> print(nested_data)
{'type': 'album', 'url': 'link.com', 'audio_features': [{'loudness': -11.4, 'duration_ms': 251}, {'loudness': -15.5, 'duration_ms': 284}]}

Convert to json-friendly representation

>>> serialized = apply_recursive(str, nested_data)
>>> print(serialized)
{'type': 'album', 'url': 'link.com', 'audio_features': {1: {'loudness': '-11.4', 'duration_ms': '251'}, 2: {'loudness': '-15.5', 'duration_ms': '284'}}}

Convert to field/type pairs

>>> schema = apply_recursive(lambda x: type(x).__name__, nested_data)
>>> print(schema)
{'type': 'str', 'url': 'str', 'audio_features': {1: {'loudness': 'float', 'duration_ms': 'int'}, 2: {'loudness': 'float', 'duration_ms': 'int'}}}