tempor.models.clairvoyance2.data.df_constraints module¶

tempor.models.clairvoyance2.data.df_constraints.cast_to_index_constraints_dtypes(dtypes_tuple: tuple[type, ...]) → tuple[type, ...][source]¶

class tempor.models.clairvoyance2.data.df_constraints.IndexConstraints(types: collections.abc.Sequence[pandas.core.indexes.base.Index] | NoneType = None, dtypes: collections.abc.Sequence[type] | NoneType = None, dtype_object_constrain_types: collections.abc.Sequence[type] | NoneType = None, enforce_monotonic_increasing: bool = False, enforce_unique: bool = False, enforce_not_multi_index: bool = False)[source]¶

Bases: object

types : Sequence[Index] | None = None¶

dtypes : Sequence[type] | None = None¶

dtype_object_constrain_types : Sequence[type] | None = None¶

enforce_monotonic_increasing : bool = False¶

enforce_unique : bool = False¶

enforce_not_multi_index : bool = False¶

class tempor.models.clairvoyance2.data.df_constraints.ElementConstraints(dtypes: collections.abc.Sequence[type] | NoneType = None, dtype_object_constrain_types: collections.abc.Sequence[type] | NoneType = None, enforce_homogenous_type_per_column: bool | NoneType = None)[source]¶

Bases: object

dtypes : Sequence[type] | None = None¶

dtype_object_constrain_types : Sequence[type] | None = None¶

enforce_homogenous_type_per_column : bool | None = None¶

class tempor.models.clairvoyance2.data.df_constraints.Constraints(on_index: tempor.models.clairvoyance2.data.df_constraints.IndexConstraints | NoneType = None, on_columns: tempor.models.clairvoyance2.data.df_constraints.IndexConstraints | NoneType = None, on_elements: tempor.models.clairvoyance2.data.df_constraints.ElementConstraints | NoneType = None)[source]¶

Bases: object

on_index : IndexConstraints | None = None¶

on_columns : IndexConstraints | None = None¶

on_elements : ElementConstraints | None = None¶

class tempor.models.clairvoyance2.data.df_constraints.ConstraintsChecker(constraints: Constraints)[source]¶

Bases: object

check(df: DataFrame) → bool[source]¶