-Ph9dZddlmZddlmZddlmZddlmZm Z m Z m Z ddl m Z mZmZer'ddlmZmZddlZddlZdd lmZdd lmZeeefZneZd gZGd d eZdS) zxSchema. Adapted from Polars implementation at: https://github.com/pola-rs/polars/blob/main/py-polars/polars/schema.py. ) annotations) OrderedDict)partial) TYPE_CHECKINGIterableMappingcast)ImplementationVersion parse_version)AnyClassVarN)DType) DTypeBackendSchemacveZdZUdZejZded< ddfd Zdd Z dd Z ddZ ddZ dddZ ddZxZS) ra<Ordered 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]_versionNschema8Mapping[str, DType] | Iterable[tuple[str, DType]] | NonereturnNonecR|pi}t|dSN)super__init__)selfr __class__s O/var/www/html/test/jupyter/venv/lib/python3.11/site-packages/narwhals/schema.pyrzSchema.__init__@s,2      list[str]cDt|S)zXGet the column names of the schema. Returns: Column names. )listkeysrs rnamesz Schema.namesFs DIIKK   r list[DType]cDt|S)z^Get the data types of the schema. Returns: Data types of schema. )r"valuesr$s rdtypesz Schema.dtypesNs DKKMM"""rintc t|S)zbGet the number of columns in the schema. Returns: Number of columns. )lenr$s rr,z Schema.lenVs 4yyr pa.Schemacxddl}ddlm|jfdDS)a7Convert 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_dtypec3DK|]\}}||jfVdSrr).0namedtyper0rs r z"Schema.to_arrow..osP  e++E4=AA B      r)pyarrownarwhals._arrow.utilsr0ritems)rpar0s` @rto_arrowzSchema.to_arrow^sm BBBBBBry     #zz||      r dtype_backend%DTypeBackend | Iterable[DTypeBackend]dict[str, Any]c  ddl}ddlm}t|tjt ||j ttr! fd| DSt}t|t|krddl m}m}m}t|t|} }t|||||| | } d|d| d |d |dd | d } t%|  fd t'|||DS)aConvert 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]'} rNr/)implementationbackend_versionversionc2i|]\}}||S)r5r<)r3r4r5r<to_native_dtypes r z$Schema.to_pandas..s>D%ooEOOOr)chainislicerepeatz Provided z) `dtype_backend`(s), but schema contains z1 field(s). Hint: instead of schema.to_pandas(z+) you may want to use schema.to_pandas(z) or schema.to_pandas()c4i|]\}}}|||SrDrE)r3r4r5backendrFs rrGz$Schema.to_pandas..s@(D%ooEIIIr)pandasnarwhals._pandas_like.utilsr0rr PANDASr r isinstancestrr9tupler, itertoolsrHrIrJ from_iterable ValueErrorzipr#r() rr<pdr0backendsrHrIrJn_usern_actual suggestionmsgrFs ` @r to_pandaszSchema.to_pandasts* HHHHHH! $)0)"--M      J}c$B$B #'::<<  ]++H8}}D ));;;;;;;;;;#&x==#d))"F++FF66(3C3CX,N,NOOQY :::S[::,4::-5QK :: -7 :::!oo%,/ T[[]]H,U,U r pl.Schemacddl}ddlmt|fdD}dkr|j|nt dt|S)axConvert Schema to a polars Schema. Returns: A polars Schema or plain dict (prior to polars 1.0). Examples: >>> 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/c3HK|]\}}||jfVdS))rANr2)r3r4r5r0 pl_versionrs rr6z#Schema.to_polars..s`  e ((4=*       r)rrr_)polarsnarwhals._polars.utilsr0r r9rr dict)rplrr0rbs` @@r to_polarszSchema.to_polarss CCCCCC"2&&        $zz||   Y&& BIf   k4<<00 rr)rrrr)rr )rr&)rr*)rr-)r<r=rr>)rr_)__name__ __module__ __qualname____doc__r MAINr__annotations__rr%r)r,r;r^rh __classcell__)rs@rrr s:#*,H....RV!!!!!!! !!!!####    .FJ<<<<<|        r)rl __future__r collectionsr functoolsrtypingrrrr narwhals._utilsr r r r rrdrgr7r:narwhals.dtypesrnarwhals.typingrrR BaseSchema__all__rrErrrysA #"""""######999999999999BBBBBBBBBB $$$$$$$$%%%%%%,,,,,,S%Z(JJJ *p p p p p Zp p p p p r