phSrSSKJr SSKJr SSKJr SSKJrJ r SSK J r J r \(a,SSK JrJr SSKJrJr SS KrSS KrSS KJr SS KJr \\\4rO\rS /r"S S \5rg )zxSchema. Adapted from Polars implementation at: https://github.com/pola-rs/polars/blob/main/py-polars/polars/schema.py. ) annotations) OrderedDict)partial) TYPE_CHECKINGcast)ImplementationVersion)IterableMapping)AnyClassVarN)DType) DTypeBackendSchemac^\rSrSr%Sr\R rS\S'S SU4Sjjjr SSjr SSjr SSjr SS jr S SS jjrSS jrS rU=r$)r!aOrdered mapping of column names to their data type. Arguments: schema: The schema definition given by column names and their associated *instantiated* Narwhals data type. Accepts a mapping or an iterable of tuples. Examples: Define a schema by passing *instantiated* data types. >>> import narwhals as nw >>> schema = nw.Schema({"foo": nw.Int8(), "bar": nw.String()}) >>> schema Schema({'foo': Int8, 'bar': String}) Access the data type associated with a specific column name. >>> schema["foo"] Int8 Access various schema properties using the `names`, `dtypes`, and `len` methods. >>> schema.names() ['foo', 'bar'] >>> schema.dtypes() [Int8, String] >>> schema.len() 2 zClassVar[Version]_versionc:>U=(d 0n[TU]U5 gN)super__init__)selfschema __class__s gC:\Users\julio\OneDrive\Documentos\Trabajo\IdeasFrscas\Cabanna\env\Lib\site-packages\narwhals/schema.pyrSchema.__init__As2  c4[UR55$)z@Get the column names of the schema. Returns: Column names. )listkeysrs rnames Schema.namesGs DIIK  rc4[UR55$)zFGet the data types of the schema. Returns: Data types of schema. )rvaluesr!s rdtypes Schema.dtypesOs DKKM""rc[U5$)zJGet the number of columns in the schema. Returns: Number of columns. )lenr!s rr) Schema.lenWs 4yrcp^^SSKnSSKJm UR"UU4SjTR 555$)zConvert Schema to a pyarrow Schema. Returns: A pyarrow Schema. Examples: >>> import narwhals as nw >>> schema = nw.Schema({"a": nw.Int64(), "b": nw.Datetime("ns")}) >>> schema.to_arrow() a: int64 b: timestamp[ns] rNnarwhals_to_native_dtypec3R># UHupUT"UTR54v M g7frr.0namedtyper-rs r "Schema.to_arrow..ps+ + +E4==A B+$')pyarrownarwhals._arrow.utilsr-ritems)rpar-s` @rto_arrowSchema.to_arrow_s/ Byy #zz|   rc SSKJn [U[RUR S9nUb[ U[5(a)UR5VVs0sH upEXC"XQS9_M snn$[U5n[U5[U5:waoSSK J nJ nJn [U5[U5p[U"URU"U "U5U 55U 55n SU <SU <SUS USS U S 3 n [!U 5e[#UR%5UR'5U5VVVs0sH upEnXC"X^S9_M snnn$s snnfs snnnf) aaConvert Schema to an ordered mapping of column names to their pandas data type. Arguments: dtype_backend: Backend(s) used for the native types. When providing more than one, the length of the iterable must be equal to the length of the schema. Returns: An ordered mapping of column names to their pandas data type. Examples: >>> import narwhals as nw >>> schema = nw.Schema({"a": nw.Int64(), "b": nw.Datetime("ns")}) >>> schema.to_pandas() {'a': 'int64', 'b': 'datetime64[ns]'} >>> schema.to_pandas("pyarrow") {'a': 'Int64[pyarrow]', 'b': 'timestamp[ns][pyarrow]'} rr,)implementationversion)r3 dtype_backend)chainislicerepeatz Provided z) `dtype_backend`(s), but schema contains z1 field(s). Hint: instead of schema.to_pandas(z+) you may want to use schema.to_pandas(z) or schema.to_pandas())narwhals._pandas_like.utilsr-rrPANDASr isinstancestrr9tupler) itertoolsrArBrC from_iterable ValueErrorzipr r%)rr@r-to_native_dtyper2r3backendsrArBrCn_usern_actual suggestionmsgbackends r to_pandasSchema.to_pandasusj* I! $)00MM   J}c$B$B$(::<#/KDoEOO#/  ]+H8}D );;#&x=#d)"++F6(3CX,NOQY  z)RS[R^_,,4:6,,4QK=9,,6>> import narwhals as nw >>> schema = nw.Schema({"a": nw.Int64(), "b": nw.Datetime("ns")}) >>> schema.to_polars() Schema({'a': Int64, 'b': Datetime(time_unit='ns', time_zone=None)}) rNr,c3R># UHupUT"UTR54v M g7frr/r0s rr4#Schema.to_polars..s+ + +E4==A B+r6)rr pl.Schema) polarsnarwhals._polars.utilsr-rPOLARS_backend_versionr9rrdict)rpl pl_versionrr-s` @r to_polarsSchema.to_polarssf C#**;;=  #zz|  Y& IIf  k4<0 rr)rz8Mapping[str, DType] | Iterable[tuple[str, DType]] | NonereturnNone)rfz list[str])rfz list[DType])rfint)rfz pa.Schema)r@z%DTypeBackend | Iterable[DTypeBackend]rfzdict[str, Any])rfr[)__name__ __module__ __qualname____firstlineno____doc__r MAINr__annotations__rr"r&r)r;rUrc__static_attributes__ __classcell__)rs@rrr!su:#*,,H.RV!N! !! !# .FJ9B9 9v  r)rm __future__r collectionsr functoolsrtypingrrnarwhals._utilsrr collections.abcr r r r r\rar7r:narwhals.dtypesrnarwhals.typingrrH BaseSchema__all__rrerrr|sZ ##&31$%,S%Z(JJ *h Zh r