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filtering_algorithm

Algorithm for filtering data records based on configurable strategies.

Classes​

AgeRangeFilterArgs​

class AgeRangeFilterArgs(*args, **kwargs):

Arguments for AGE_RANGE filter strategy.

This filtering strategy keeps only records within a specified age range in a given column.

Ancestors​

  • builtins.dict

Variables​

  • static birth_date_column : str
  • static max_age : int
  • static min_age : int

FilterStrategy​

class FilterStrategy(    value, names=None, *, module=None, qualname=None, type=None, start=1,):

Enumeration of available filtering strategies.

Inherits from str to allow for easy conversion to string and comparison with other strings. The ordering of the inheritance is important (first str then Enum). This replicates the strEnum behaviour in Python 3.11+. TODO: [Python 3.11] Convert to strEnum when Python 3.11 is the minimum version.

Ancestors​

Variables​

  • static AGE_RANGE
  • static FREQUENCY
  • static LATEST

FilterStrategyClass​

class FilterStrategyClass(    value, names=None, *, module=None, qualname=None, type=None, start=1,):

Enumeration map of filter strategies to TypedDict and classes.

Ancestors​

Variables​

  • static AGE_RANGE
  • static FREQUENCY
  • static LATEST

FrequencyFilterArgs​

class FrequencyFilterArgs(*args, **kwargs):

Arguments for FREQUENCY filter strategy.

This filtering strategy keeps only records with a specified frequency of ID occurrence.

Ancestors​

  • builtins.dict

Variables​

  • static id_column : Union[str, list[str]]
  • static max_frequency : int
  • static min_frequency : int

LatestFilterArgs​

class LatestFilterArgs(*args, **kwargs):

Arguments for LATEST filter strategy.

This filtering strategy keeps only the latest records per ID.

Ancestors​

  • builtins.dict

Variables​

  • static date_column : str
  • static id_column : Union[str, list[str]]
  • static num_latest : int

RecordFilterAlgorithm​

class RecordFilterAlgorithm(    datastructure: DataStructure,    strategies: Sequence[Union[FilterStrategy, str]],    filter_args_list: list[FilterArgs],):

Algorithm factory for filtering records based on various strategies.

Arguments

  • ****kwargs**: Additional keyword arguments.
  • datastructure: The data structure to use for the algorithm.
  • filter_args_list: List of strategy-specific arguments
  • strategies: List of filtering strategies

Attributes

  • class_name: The name of the algorithm class.
  • datastructure: The data structure to use for the algorithm
  • fields_dict: A dictionary mapping all attributes that will be serialized in the class to their marshamllow field type. (e.g. fields_dict = {"class_name": fields.Str()}).
  • filter_args_list: List of strategy-specific arguments
  • nested_fields: A dictionary mapping all nested attributes to a registry that contains class names mapped to the respective classes. (e.g. nested_fields = {"datastructure": datastructure.registry})
  • strategies: List of filtering strategies

Raises

  • ValueError: If required parameters for a strategy are missing

Ancestors​

Variables​

  • static fields_dict : ClassVar[T_FIELDS_DICT]

Methods​

create​

def create(self, role: Union[str, Role], **kwargs: Any) ‑> Any:

Create an instance representing the role specified.

modeller​

def modeller(    self, **kwargs: Any,) ‑> NoResultsModellerAlgorithm:

Modeller-side of the algorithm.

worker​

def worker(    self, **kwargs: Any,) ‑> bitfount.federated.algorithms.filtering_algorithm._WorkerSide:

Worker-side of the algorithm.