NOTICE

The upcoming release of Featuretools 1.0.0 contains several breaking changes. Users are encouraged to test this version prior to release by installing from GitHub:

pip install https://github.com/alteryx/featuretools/archive/woodwork-integration.zip

For details on migrating to the new version, refer to Transitioning to Featuretools Version 1.0. Please report any issues in the Featuretools GitHub repo or by messaging in Alteryx Open Source Slack.


Source code for featuretools.feature_base.feature_base

from featuretools import Relationship, Timedelta, primitives
from featuretools.entityset.relationship import RelationshipPath
from featuretools.primitives.base import (
    AggregationPrimitive,
    PrimitiveBase,
    TransformPrimitive
)
from featuretools.primitives.utils import serialize_primitive
from featuretools.utils.wrangle import (
    _check_time_against_column,
    _check_timedelta
)
from featuretools.variable_types import (
    Boolean,
    Categorical,
    Datetime,
    DatetimeTimeIndex,
    Discrete,
    Id,
    Index,
    Numeric,
    NumericTimeIndex,
    Variable
)


class FeatureBase(object):
    def __init__(self, entity, base_features, relationship_path, primitive, name=None, names=None):
        """Base class for all features

        Args:
            entity (Entity): entity this feature is being calculated for
            base_features (list[FeatureBase]): list of base features for primitive
            relationship_path (RelationshipPath): path from this entity to the
                entity of the base features.
            primitive (:class:`.PrimitiveBase`): primitive to calculate. if not initialized when passed, gets initialized with no arguments
        """
        assert all(isinstance(f, FeatureBase) for f in base_features), \
            "All base features must be features"

        self.entity_id = entity.id
        self.entityset = entity.entityset.metadata

        self.base_features = base_features

        # initialize if not already initialized
        if not isinstance(primitive, PrimitiveBase):
            primitive = primitive()
        self.primitive = primitive

        self.relationship_path = relationship_path

        self._name = name

        self._names = names

        assert self._check_input_types(), ("Provided inputs don't match input "
                                           "type requirements")

    def __getitem__(self, key):
        assert self.number_output_features > 1, \
            'can only access slice of multi-output feature'
        assert self.number_output_features > key, \
            'index is higher than the number of outputs'
        return FeatureOutputSlice(self, key)

    @classmethod
    def from_dictionary(cls, arguments, entityset, dependencies, primitives_deserializer):
        raise NotImplementedError("Must define from_dictionary on FeatureBase subclass")

[docs] def rename(self, name): """Rename Feature, returns copy""" feature_copy = self.copy() feature_copy._name = name feature_copy._names = None return feature_copy
def copy(self): raise NotImplementedError("Must define copy on FeatureBase subclass") def get_name(self): if not self._name: self._name = self.generate_name() return self._name def get_feature_names(self): if not self._names: if self.number_output_features == 1: self._names = [self.get_name()] else: self._names = self.generate_names() if self.get_name() != self.generate_name(): self._names = [self.get_name() + '[{}]'.format(i) for i in range(len(self._names))] return self._names def get_function(self, **kwargs): return self.primitive.get_function(**kwargs) def get_dependencies(self, deep=False, ignored=None, copy=True): """Returns features that are used to calculate this feature ..note:: If you only want the features that make up the input to the feature function use the base_features attribute instead. """ deps = [] for d in self.base_features[:]: deps += [d] if hasattr(self, "where") and self.where: deps += [self.where] if ignored is None: ignored = set([]) deps = [d for d in deps if d.unique_name() not in ignored] if deep: for dep in deps[:]: # copy so we don't modify list we iterate over deep_deps = dep.get_dependencies(deep, ignored) deps += deep_deps return deps
[docs] def get_depth(self, stop_at=None): """Returns depth of feature""" max_depth = 0 stop_at_set = set() if stop_at is not None: stop_at_set = set([i.unique_name() for i in stop_at]) if self.unique_name() in stop_at_set: return 0 for dep in self.get_dependencies(deep=True, ignored=stop_at_set): max_depth = max(dep.get_depth(stop_at=stop_at), max_depth) return max_depth + 1
def _check_input_types(self): if len(self.base_features) == 0: return True input_types = self.primitive.input_types if input_types is not None: if type(input_types[0]) != list: input_types = [input_types] for t in input_types: zipped = list(zip(t, self.base_features)) if all([issubclass(f.variable_type, v) for v, f in zipped]): return True else: return True return False @property def entity(self): """Entity this feature belongs too""" return self.entityset[self.entity_id] @property def number_output_features(self): return self.primitive.number_output_features def __repr__(self): return "<Feature: %s>" % (self.get_name()) def hash(self): return hash(self.get_name() + self.entity.id) def __hash__(self): return self.hash() @property def variable_type(self): feature = self variable_type = self.primitive.return_type while variable_type is None: # get variable_type of first base feature base_feature = feature.base_features[0] variable_type = base_feature.variable_type # only the original time index should exist # so make this feature's return type just a Datetime if variable_type == DatetimeTimeIndex: variable_type = Datetime elif variable_type == NumericTimeIndex: variable_type = Numeric elif variable_type == Index: variable_type = Categorical # direct features should keep the Id return type, but all other features should get # converted to Categorical if not isinstance(feature, DirectFeature) and variable_type == Id: variable_type = Categorical feature = base_feature return variable_type @property def default_value(self): return self.primitive.default_value def get_arguments(self): raise NotImplementedError("Must define get_arguments on FeatureBase subclass") def to_dictionary(self): return { 'type': type(self).__name__, 'dependencies': [dep.unique_name() for dep in self.get_dependencies()], 'arguments': self.get_arguments(), } def _handle_binary_comparision(self, other, Primitive, PrimitiveScalar): if isinstance(other, FeatureBase): return Feature([self, other], primitive=Primitive) return Feature([self], primitive=PrimitiveScalar(other)) def __eq__(self, other): """Compares to other by equality""" return self._handle_binary_comparision(other, primitives.Equal, primitives.EqualScalar) def __ne__(self, other): """Compares to other by non-equality""" return self._handle_binary_comparision(other, primitives.NotEqual, primitives.NotEqualScalar) def __gt__(self, other): """Compares if greater than other""" return self._handle_binary_comparision(other, primitives.GreaterThan, primitives.GreaterThanScalar) def __ge__(self, other): """Compares if greater than or equal to other""" return self._handle_binary_comparision(other, primitives.GreaterThanEqualTo, primitives.GreaterThanEqualToScalar) def __lt__(self, other): """Compares if less than other""" return self._handle_binary_comparision(other, primitives.LessThan, primitives.LessThanScalar) def __le__(self, other): """Compares if less than or equal to other""" return self._handle_binary_comparision(other, primitives.LessThanEqualTo, primitives.LessThanEqualToScalar) def __add__(self, other): """Add other""" return self._handle_binary_comparision(other, primitives.AddNumeric, primitives.AddNumericScalar) def __radd__(self, other): return self.__add__(other) def __sub__(self, other): """Subtract other""" return self._handle_binary_comparision(other, primitives.SubtractNumeric, primitives.SubtractNumericScalar) def __rsub__(self, other): return Feature([self], primitive=primitives.ScalarSubtractNumericFeature(other)) def __div__(self, other): """Divide by other""" return self._handle_binary_comparision(other, primitives.DivideNumeric, primitives.DivideNumericScalar) def __truediv__(self, other): return self.__div__(other) def __rtruediv__(self, other): return self.__rdiv__(other) def __rdiv__(self, other): return Feature([self], primitive=primitives.DivideByFeature(other)) def __mul__(self, other): """Multiply by other""" if isinstance(other, FeatureBase): if self.variable_type == Boolean and other.variable_type == Boolean: return Feature([self, other], primitive=primitives.MultiplyBoolean) return self._handle_binary_comparision(other, primitives.MultiplyNumeric, primitives.MultiplyNumericScalar) def __rmul__(self, other): return self.__mul__(other) def __mod__(self, other): """Take modulus of other""" return self._handle_binary_comparision(other, primitives.ModuloNumeric, primitives.ModuloNumericScalar) def __rmod__(self, other): return Feature([self], primitive=primitives.ModuloByFeature(other)) def __and__(self, other): return self.AND(other) def __rand__(self, other): return Feature([other, self], primitive=primitives.And) def __or__(self, other): return self.OR(other) def __ror__(self, other): return Feature([other, self], primitive=primitives.Or) def __not__(self, other): return self.NOT(other) def __abs__(self): return Feature([self], primitive=primitives.Absolute) def __neg__(self): return Feature([self], primitive=primitives.Negate) def AND(self, other_feature): """Logical AND with other_feature""" return Feature([self, other_feature], primitive=primitives.And) def OR(self, other_feature): """Logical OR with other_feature""" return Feature([self, other_feature], primitive=primitives.Or) def NOT(self): """Creates inverse of feature""" return Feature([self], primitive=primitives.Not) def isin(self, list_of_output): return Feature([self], primitive=primitives.IsIn(list_of_outputs=list_of_output)) def is_null(self): """Compares feature to null by equality""" return Feature([self], primitive=primitives.IsNull) def __invert__(self): return self.NOT() def unique_name(self): return u"%s: %s" % (self.entity_id, self.get_name()) def relationship_path_name(self): return self.relationship_path.name class IdentityFeature(FeatureBase): """Feature for entity that is equivalent to underlying variable""" def __init__(self, variable, name=None): entity_id = variable.entity_id self.variable = variable.entityset.metadata[entity_id][variable.id] self.return_type = type(variable) super(IdentityFeature, self).__init__(entity=variable.entity, base_features=[], relationship_path=RelationshipPath([]), primitive=PrimitiveBase, name=name) @classmethod def from_dictionary(cls, arguments, entityset, dependencies, primitives_deserializer): entity_id = arguments['entity_id'] variable_id = arguments['variable_id'] variable = entityset[entity_id][variable_id] return cls(variable=variable, name=arguments['name']) def copy(self): """Return copy of feature""" return IdentityFeature(self.variable) def generate_name(self): return self.variable.name def get_depth(self, stop_at=None): return 0 def get_arguments(self): return { 'name': self._name, 'variable_id': self.variable.id, 'entity_id': self.variable.entity_id, } @property def variable_type(self): return type(self.variable) class DirectFeature(FeatureBase): """Feature for child entity that inherits a feature value from a parent entity""" input_types = [Variable] return_type = None def __init__(self, base_feature, child_entity, relationship=None, name=None): base_feature = _check_feature(base_feature) self.parent_entity = base_feature.entity relationship = self._handle_relationship(child_entity, relationship) super(DirectFeature, self).__init__(entity=child_entity, base_features=[base_feature], relationship_path=RelationshipPath([(True, relationship)]), primitive=PrimitiveBase, name=name) def _handle_relationship(self, child_entity, relationship): if relationship: relationship_child = relationship.child_entity assert child_entity.id == relationship_child.id, \ 'child_entity must be the relationship child entity' assert self.parent_entity.id == relationship.parent_entity.id, \ 'Base feature must be defined on the relationship parent entity' else: child_relationships = child_entity.entityset.get_forward_relationships(child_entity.id) possible_relationships = (r for r in child_relationships if r.parent_entity.id == self.parent_entity.id) relationship = next(possible_relationships, None) if not relationship: raise RuntimeError('No relationship from "%s" to "%s" found.' % (child_entity.id, self.parent_entity.id)) # Check for another path. elif next(possible_relationships, None): message = "There are multiple relationships to the base entity. " \ "You must specify a relationship." raise RuntimeError(message) return relationship @classmethod def from_dictionary(cls, arguments, entityset, dependencies, primitives_deserializer): base_feature = dependencies[arguments['base_feature']] relationship = Relationship.from_dictionary(arguments['relationship'], entityset) child_entity = relationship.child_entity return cls(base_feature=base_feature, child_entity=child_entity, relationship=relationship, name=arguments['name']) @property def variable(self): return self.base_features[0].variable @property def number_output_features(self): return self.base_features[0].number_output_features @property def default_value(self): return self.base_features[0].default_value def copy(self): """Return copy of feature""" _is_forward, relationship = self.relationship_path[0] return DirectFeature(self.base_features[0], self.entity, relationship=relationship) @property def variable_type(self): return self.base_features[0].variable_type def generate_name(self): return self._name_from_base(self.base_features[0].get_name()) def generate_names(self): return [self._name_from_base(base_name) for base_name in self.base_features[0].get_feature_names()] def get_arguments(self): _is_forward, relationship = self.relationship_path[0] return { 'name': self._name, 'base_feature': self.base_features[0].unique_name(), 'relationship': relationship.to_dictionary(), } def _name_from_base(self, base_name): return u"%s.%s" % (self.relationship_path_name(), base_name) class AggregationFeature(FeatureBase): # Feature to condition this feature by in # computation (e.g. take the Count of products where the product_id is # "basketball".) where = None #: (str or :class:`.Timedelta`): Use only some amount of previous data from # each time point during calculation use_previous = None def __init__(self, base_features, parent_entity, primitive, relationship_path=None, use_previous=None, where=None, name=None): if hasattr(base_features, '__iter__'): base_features = [_check_feature(bf) for bf in base_features] msg = "all base features must share the same entity" assert len(set([bf.entity for bf in base_features])) == 1, msg else: base_features = [_check_feature(base_features)] for bf in base_features: if bf.number_output_features > 1: raise ValueError("Cannot stack on whole multi-output feature.") self.child_entity = base_features[0].entity relationship_path, self._path_is_unique = \ self._handle_relationship_path(parent_entity, relationship_path) self.parent_entity = parent_entity.entityset.metadata[parent_entity.id] if where is not None: self.where = _check_feature(where) msg = "Where feature must be defined on child entity {}".format( self.child_entity.id) assert self.where.entity.id == self.child_entity.id, msg if use_previous: assert self.child_entity.time_index is not None, ( "Applying function that requires time index to entity that " "doesn't have one") self.use_previous = _check_timedelta(use_previous) assert len(base_features) > 0 time_index = base_features[0].entity.time_index time_col = base_features[0].entity[time_index] assert time_index is not None, ("Use previous can only be defined " "on entities with a time index") assert _check_time_against_column(self.use_previous, time_col) super(AggregationFeature, self).__init__(entity=parent_entity, base_features=base_features, relationship_path=relationship_path, primitive=primitive, name=name) def _handle_relationship_path(self, parent_entity, relationship_path): if relationship_path: assert all(not is_forward for is_forward, _r in relationship_path), \ 'All relationships in path must be backward' _is_forward, first_relationship = relationship_path[0] first_parent = first_relationship.parent_entity assert parent_entity.id == first_parent.id, \ 'parent_entity must match first relationship in path.' _is_forward, last_relationship = relationship_path[-1] assert self.child_entity.id == last_relationship.child_entity.id, \ 'Base feature must be defined on the entity at the end of relationship_path' path_is_unique = parent_entity.entityset \ .has_unique_forward_path(self.child_entity.id, parent_entity.id) else: paths = parent_entity.entityset \ .find_backward_paths(parent_entity.id, self.child_entity.id) first_path = next(paths, None) if not first_path: raise RuntimeError('No backward path from "%s" to "%s" found.' % (parent_entity.id, self.child_entity.id)) # Check for another path. elif next(paths, None): message = "There are multiple possible paths to the base entity. " \ "You must specify a relationship path." raise RuntimeError(message) relationship_path = RelationshipPath([(False, r) for r in first_path]) path_is_unique = True return relationship_path, path_is_unique @classmethod def from_dictionary(cls, arguments, entityset, dependencies, primitives_deserializer): base_features = [dependencies[name] for name in arguments['base_features']] relationship_path = [Relationship.from_dictionary(r, entityset) for r in arguments['relationship_path']] parent_entity = relationship_path[0].parent_entity relationship_path = RelationshipPath([(False, r) for r in relationship_path]) primitive = primitives_deserializer.deserialize_primitive(arguments['primitive']) use_previous_data = arguments['use_previous'] use_previous = use_previous_data and Timedelta.from_dictionary(use_previous_data) where_name = arguments['where'] where = where_name and dependencies[where_name] return cls(base_features=base_features, parent_entity=parent_entity, primitive=primitive, relationship_path=relationship_path, use_previous=use_previous, where=where, name=arguments['name']) def copy(self): return AggregationFeature(self.base_features, parent_entity=self.parent_entity, relationship_path=self.relationship_path, primitive=self.primitive, use_previous=self.use_previous, where=self.where) def _where_str(self): if self.where is not None: where_str = u" WHERE " + self.where.get_name() else: where_str = '' return where_str def _use_prev_str(self): if self.use_previous is not None and hasattr(self.use_previous, 'get_name'): use_prev_str = u", Last {}".format(self.use_previous.get_name()) else: use_prev_str = u'' return use_prev_str def generate_name(self): return self.primitive.generate_name(base_feature_names=[bf.get_name() for bf in self.base_features], relationship_path_name=self.relationship_path_name(), parent_entity_id=self.parent_entity.id, where_str=self._where_str(), use_prev_str=self._use_prev_str()) def generate_names(self): return self.primitive.generate_names(base_feature_names=[bf.get_name() for bf in self.base_features], relationship_path_name=self.relationship_path_name(), parent_entity_id=self.parent_entity.id, where_str=self._where_str(), use_prev_str=self._use_prev_str()) def get_arguments(self): return { 'name': self._name, 'base_features': [feat.unique_name() for feat in self.base_features], 'relationship_path': [r.to_dictionary() for _, r in self.relationship_path], 'primitive': serialize_primitive(self.primitive), 'where': self.where and self.where.unique_name(), 'use_previous': self.use_previous and self.use_previous.get_arguments(), } def relationship_path_name(self): if self._path_is_unique: return self.child_entity.id else: return self.relationship_path.name class TransformFeature(FeatureBase): def __init__(self, base_features, primitive, name=None): # Any edits made to this method should also be made to the # new_class_init method in make_trans_primitive if hasattr(base_features, '__iter__'): base_features = [_check_feature(bf) for bf in base_features] msg = "all base features must share the same entity" assert len(set([bf.entity for bf in base_features])) == 1, msg else: base_features = [_check_feature(base_features)] for bf in base_features: if bf.number_output_features > 1: raise ValueError("Cannot stack on whole multi-output feature.") super(TransformFeature, self).__init__(entity=base_features[0].entity, base_features=base_features, relationship_path=RelationshipPath([]), primitive=primitive, name=name) @classmethod def from_dictionary(cls, arguments, entityset, dependencies, primitives_deserializer): base_features = [dependencies[name] for name in arguments['base_features']] primitive = primitives_deserializer.deserialize_primitive(arguments['primitive']) return cls(base_features=base_features, primitive=primitive, name=arguments['name']) def copy(self): return TransformFeature(self.base_features, self.primitive) def generate_name(self): return self.primitive.generate_name(base_feature_names=[bf.get_name() for bf in self.base_features]) def generate_names(self): return self.primitive.generate_names(base_feature_names=[bf.get_name() for bf in self.base_features]) def get_arguments(self): return { 'name': self._name, 'base_features': [feat.unique_name() for feat in self.base_features], 'primitive': serialize_primitive(self.primitive) } class GroupByTransformFeature(TransformFeature): def __init__(self, base_features, primitive, groupby, name=None): if not isinstance(groupby, FeatureBase): groupby = IdentityFeature(groupby) assert issubclass(groupby.variable_type, Discrete) self.groupby = groupby if hasattr(base_features, '__iter__'): base_features.append(groupby) else: base_features = [base_features, groupby] super(GroupByTransformFeature, self).__init__(base_features=base_features, primitive=primitive, name=name) @classmethod def from_dictionary(cls, arguments, entityset, dependencies, primitives_deserializer): base_features = [dependencies[name] for name in arguments['base_features']] primitive = primitives_deserializer.deserialize_primitive(arguments['primitive']) groupby = dependencies[arguments['groupby']] return cls(base_features=base_features, primitive=primitive, groupby=groupby, name=arguments['name']) def copy(self): # the groupby feature is appended to base_features in the __init__ # so here we separate them again return GroupByTransformFeature(self.base_features[:-1], self.primitive, self.groupby) def generate_name(self): # exclude the groupby feature from base_names since it has a special # place in the feature name base_names = [bf.get_name() for bf in self.base_features[:-1]] _name = self.primitive.generate_name(base_names) return u"{} by {}".format(_name, self.groupby.get_name()) def generate_names(self): base_names = [bf.get_name() for bf in self.base_features[:-1]] _names = self.primitive.generate_names(base_names) names = [name + " by {}".format(self.groupby.get_name()) for name in _names] return names def get_arguments(self): # Do not include groupby in base_features. feature_names = [feat.unique_name() for feat in self.base_features if feat.unique_name() != self.groupby.unique_name()] return { 'name': self._name, 'base_features': feature_names, 'primitive': serialize_primitive(self.primitive), 'groupby': self.groupby.unique_name(), } class Feature(object): """ Alias to create feature. Infers the feature type based on init parameters. """ def __new__(self, base, entity=None, groupby=None, parent_entity=None, primitive=None, use_previous=None, where=None): # either direct or identity if primitive is None and entity is None: return IdentityFeature(base) elif primitive is None and entity is not None: return DirectFeature(base, entity) elif primitive is not None and parent_entity is not None: assert isinstance(primitive, AggregationPrimitive) or issubclass(primitive, AggregationPrimitive) return AggregationFeature(base, parent_entity=parent_entity, use_previous=use_previous, where=where, primitive=primitive) elif primitive is not None: assert (isinstance(primitive, TransformPrimitive) or issubclass(primitive, TransformPrimitive)) if groupby is not None: return GroupByTransformFeature(base, primitive=primitive, groupby=groupby) return TransformFeature(base, primitive=primitive) raise Exception("Unrecognized feature initialization") class FeatureOutputSlice(FeatureBase): """ Class to access specific multi output feature column """ def __init__(self, base_feature, n, name=None): base_features = [base_feature] self.num_output_parent = base_feature.number_output_features msg = "cannot access slice from single output feature" assert(self.num_output_parent > 1), msg msg = "cannot access column that is not between 0 and " + str(self.num_output_parent - 1) assert(n < self.num_output_parent), msg self.n = n self._name = name self._names = [name] if name else None self.base_features = base_features self.base_feature = base_features[0] self.entity_id = base_feature.entity_id self.entityset = base_feature.entityset self.primitive = base_feature.primitive self.relationship_path = base_feature.relationship_path def __getitem__(self, key): raise ValueError("Cannot get item from slice of multi output feature") def generate_name(self): return self.base_feature.get_feature_names()[self.n] @property def number_output_features(self): return 1 def get_arguments(self): return { 'name': self._name, 'base_feature': self.base_feature.unique_name(), 'n': self.n } @classmethod def from_dictionary(cls, arguments, entityset, dependencies, primitives_deserializer): base_feature_name = arguments['base_feature'] base_feature = dependencies[base_feature_name] n = arguments['n'] name = arguments['name'] return cls(base_feature=base_feature, n=n, name=name) def copy(self): return FeatureOutputSlice(self.base_feature, self.n) def _check_feature(feature): if isinstance(feature, Variable): return IdentityFeature(feature) elif isinstance(feature, FeatureBase): return feature raise Exception("Not a feature")