Source code for woodwork.column_schema

import warnings
from inspect import isclass

import woodwork as ww
from woodwork.exceptions import DuplicateTagsWarning, StandardTagsChangedWarning
from woodwork.logical_types import (
    Boolean,
    BooleanNullable,
    Datetime,
    LatLong,
    NaturalLanguage,
    Ordinal,
    Unknown,
)
from woodwork.utils import _convert_input_to_set


[docs]class ColumnSchema(object):
[docs] def __init__( self, logical_type=None, semantic_tags=None, use_standard_tags=False, description=None, origin=None, metadata=None, validate=True, ): """Create ColumnSchema Args: logical_type (LogicalType, optional): The column's LogicalType. semantic_tags (str, list, set, optional): The semantic tag(s) specified for the column. use_standard_tags (boolean, optional): If True, will add standard semantic tags to the column based on the specified logical type if a logical type is defined for the column. Defaults to False. description (str, optional): User description of the column. origin (str, optional): Origin of the column (i.e. "base" or "engineered"). metadata (dict[str -> json serializable], optional): Extra metadata provided by the user. The dictionary must contain data types that are JSON serializable such as string, integers, and floats. DataFrame and Series types are not supported. validate (bool, optional): Whether to perform parameter validation. Defaults to True. """ metadata = metadata or {} if isclass(logical_type): logical_type = logical_type() if validate: if logical_type is not None: _validate_logical_type(logical_type) _validate_description(description) _validate_origin(origin) _validate_metadata(metadata) self._metadata = metadata self._description = description self._origin = origin self.logical_type = logical_type self.use_standard_tags = use_standard_tags semantic_tags = self._get_column_tags(semantic_tags, validate) self.semantic_tags = semantic_tags
def __eq__(self, other, deep=True): if self.use_standard_tags != other.use_standard_tags: return False if self.logical_type != other.logical_type: return False if self.semantic_tags != other.semantic_tags: return False if self.description != other.description: return False if self.origin != other.origin: return False if deep and self.metadata != other.metadata: return False return True def __repr__(self): msg = "<ColumnSchema" if self.logical_type is not None: msg += " (Logical Type = {})".format(self.logical_type) if self.semantic_tags: msg += " (Semantic Tags = {})".format(sorted(list(self.semantic_tags))) msg += ">" return msg def _get_column_tags(self, semantic_tags, validate): semantic_tags = _convert_input_to_set( semantic_tags, error_language="semantic_tags", validate=validate, ) if self.use_standard_tags: if self.logical_type is None: raise ValueError("Cannot use standard tags when logical_type is None") semantic_tags = semantic_tags.union(self.logical_type.standard_tags) return semantic_tags @property def description(self): """Description of the column""" return self._description @description.setter def description(self, description): _validate_description(description) self._description = description @property def origin(self): """Origin of the column""" return self._origin @origin.setter def origin(self, origin): _validate_origin(origin) self._origin = origin @property def metadata(self): """Metadata of the column""" return self._metadata @metadata.setter def metadata(self, metadata): metadata = metadata or {} _validate_metadata(metadata) self._metadata = metadata @property def is_numeric(self): """Whether the ColumnSchema is numeric in nature""" return ( self.logical_type is not None and "numeric" in self.logical_type.standard_tags ) @property def is_categorical(self): """Whether the ColumnSchema is categorical in nature""" return ( self.logical_type is not None and "category" in self.logical_type.standard_tags ) @property def is_datetime(self): """Whether the ColumnSchema is a Datetime column""" return type(self.logical_type) == Datetime @property def is_latlong(self): """Whether the ColumnSchema is a LatLong column""" return type(self.logical_type) == LatLong @property def is_boolean(self): """Whether the ColumnSchema is a Boolean column""" ltype_class = type(self.logical_type) return ltype_class == Boolean or ltype_class == BooleanNullable @property def is_natural_language(self): """Whether the ColumnSchema is a Natural Language column""" return type(self.logical_type) == NaturalLanguage @property def is_unknown(self): """Whether the ColumnSchema is a Unknown column""" return type(self.logical_type) == Unknown @property def is_ordinal(self): """Whether the ColumnSchema is a Ordinal column""" return type(self.logical_type) == Ordinal def _add_semantic_tags(self, new_tags, name): """Add the specified semantic tags to the current set of tags Args: new_tags (str/list/set): The new tags to add name (str): Name of the column to use in warning """ new_tags = _convert_input_to_set(new_tags) duplicate_tags = sorted(list(self.semantic_tags.intersection(new_tags))) if duplicate_tags: warnings.warn( DuplicateTagsWarning().get_warning_message(duplicate_tags, name), DuplicateTagsWarning, ) self.semantic_tags = self.semantic_tags.union(new_tags) def _remove_semantic_tags(self, tags_to_remove, name): """Removes specified semantic tags from from the current set of tags Args: tags_to_remove (str/list/set): The tags to remove name (str): Name of the column to use in warning """ tags_to_remove = _convert_input_to_set(tags_to_remove) invalid_tags = sorted(list(tags_to_remove.difference(self.semantic_tags))) if invalid_tags: raise LookupError( f"Semantic tag(s) '{', '.join(invalid_tags)}' not present on column '{name}'", ) if self.use_standard_tags and sorted( list(tags_to_remove.intersection(self.logical_type.standard_tags)), ): warnings.warn( StandardTagsChangedWarning().get_warning_message( not self.use_standard_tags, name, ), StandardTagsChangedWarning, ) self.semantic_tags = self.semantic_tags.difference(tags_to_remove) def _reset_semantic_tags(self): """Reset the set of semantic tags to the default values. The default values will be either an empty set or the standard tags, controlled by the use_standard_tags boolean. """ new_tags = set() if self.use_standard_tags: new_tags = set(self.logical_type.standard_tags) self.semantic_tags = new_tags def _set_semantic_tags(self, semantic_tags): """Replace current semantic tags with new values. If use_standard_tags is set to True, standard tags will be added as well. Args: semantic_tags (str/list/set): New semantic tag(s) to set """ semantic_tags = _convert_input_to_set(semantic_tags) if self.use_standard_tags: semantic_tags = semantic_tags.union(self.logical_type.standard_tags) self.semantic_tags = semantic_tags @property def custom_tags(self): """The custom semantic tag(s) specified for the column.""" standard_tags = set() if self.use_standard_tags: standard_tags |= self.logical_type.standard_tags return self.semantic_tags - standard_tags - {"index", "time_index"}
def _validate_logical_type(logical_type): if type(logical_type) not in ww.type_system.registered_types: raise TypeError(f"logical_type {logical_type} is not a registered LogicalType.") def _validate_description(column_description): if column_description is not None and not isinstance(column_description, str): raise TypeError("Column description must be a string") def _validate_origin(origin): if origin is not None and not isinstance(origin, str): raise TypeError("Column origin must be a string") def _validate_metadata(column_metadata): if not isinstance(column_metadata, dict): raise TypeError("Column metadata must be a dictionary")