o hQ@sdZddlmZddlmZddlmZddlmZddlm Z ddlm Z ddlm Z dd l m Z dd l mZdd l mZergdd lmZdd lmZddlZddlZddlmZddlmZeeefZneZdgZGdddeZdS)zxSchema. Adapted from Polars implementation at: https://github.com/pola-rs/polars/blob/main/py-polars/polars/schema.py. ) annotations) OrderedDict)partial) TYPE_CHECKING)Iterable)Mapping)cast)Implementation)Version) parse_version)Any)ClassVarN)DType) DTypeBackendSchemacsveZdZUdZejZded< dd fd d Zd!d d Z d"ddZ d#ddZ d$ddZ dd%ddZ d&ddZZS)'raOrdered mapping of column names to their data type. Arguments: schema: Mapping[str, DType] | Iterable[tuple[str, DType]] | None The schema definition given by column names and their associated. *instantiated* Narwhals data type. Accepts a mapping or an iterable of tuples. Examples: Define a schema by passing *instantiated* data types. >>> import narwhals as nw >>> schema = nw.Schema({"foo": nw.Int8(), "bar": nw.String()}) >>> schema Schema({'foo': Int8, 'bar': String}) Access the data type associated with a specific column name. >>> schema["foo"] Int8 Access various schema properties using the `names`, `dtypes`, and `len` methods. >>> schema.names() ['foo', 'bar'] >>> schema.dtypes() [Int8, String] >>> schema.len() 2 zClassVar[Version]_versionNschema8Mapping[str, DType] | Iterable[tuple[str, DType]] | NonereturnNonecs|pi}t|dSN)super__init__)selfr __class__C/var/www/vscode/kcb/lib/python3.10/site-packages/narwhals/schema.pyrGszSchema.__init__ list[str]cC t|S)zXGet the column names of the schema. Returns: Column names. )listkeysrrrrnamesN z Schema.names list[DType]cCr)z^Get the data types of the schema. Returns: Data types of schema. )r valuesr"rrrdtypesVr$z Schema.dtypesintcCst|S)zbGet the number of columns in the schema. Returns: Number of columns. )lenr"rrrr)^sz Schema.len pa.Schemacs2ddl}ddlm|fddDS)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_dtypec3s$|] \}}||jfVqdSrr.0namedtyper,rrr ws  z"Schema.to_arrow..)pyarrownarwhals._arrow.utilsr,ritems)rparr2rto_arrowfs  zSchema.to_arrow dtype_backend%DTypeBackend | Iterable[DTypeBackend]dict[str, Any]c sddl}ddlm}t|tjt||jddustt r+fdd| DSt }t |t |kryddl m}ddl m}dd l m}t |t |}} t |||||| | } d |d | d |d |dd| d } t| fddt|||DS)aConvert Schema to an ordered mapping of column names to their pandas data type. Arguments: dtype_backend: Backend(s) used for the native types. When providing more than one, the length of the iterable must be equal to the length of the schema. Returns: An ordered mapping of column names to their pandas data type. Examples: >>> import narwhals as nw >>> schema = nw.Schema({"a": nw.Int64(), "b": nw.Datetime("ns")}) >>> schema.to_pandas() {'a': 'int64', 'b': 'datetime64[ns]'} >>> schema.to_pandas("pyarrow") {'a': 'Int64[pyarrow]', 'b': 'timestamp[ns][pyarrow]'} rNr+)implementationbackend_versionversioncsi|] \}}||dqS)r1r9rr.r9to_native_dtyperr s z$Schema.to_pandas..)chain)islice)repeatz 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()cs i|] \}}}|||dqSr?r)r/r0r1backend)rArrrBs )pandasnarwhals._pandas_like.utilsr,rr PANDASr r isinstancestrr6tupler) itertoolsrCrDrE from_iterable ValueErrorzipr!r&) rr9pdr,backendsrCrDrEn_usern_actual suggestionmsgrr@r to_pandas|sF      zSchema.to_pandas pl.SchemacsVddl}ddlmt|fddD}dkr$||Stdt|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+c3s(|]\}}||jdfVqdS))r=Nr-r.r, pl_versionrrrr3s z#Schema.to_polars..)rrrY)polarsnarwhals._polars.utilsr,r r6rrdict)rplrrrZr to_polarss   zSchema.to_polarsr)rrrr)rr)rr%)rr()rr*)r9r:rr;)rrY)__name__ __module__ __qualname____doc__r MAINr__annotations__rr#r'r)r8rXra __classcell__rrrrr&s      @)re __future__r collectionsr functoolsrtypingrrrrnarwhals.utilsr r r r r r]r`r4r7narwhals.dtypesrnarwhals.typingrrL BaseSchema__all__rrrrrs,