]j@SrSSKJr SSKrSSKrSSKJr SSKJ r J r J r SSK r \R(aSSKJr 0SS_S S _S S _S S_SS_SS_SS_SS_SS_SS_SS_SS_SS_S S!_S"S#_S$S%_S&S'_S(S)S*S+S,S-S.S/S0S1S2S3S4S5. Er"S6S75r"S8S95rSzE Utility functions and objects for implementing the interchange API. ) annotationsN)lib) ArrowDtypeCategoricalDtypeDatetimeTZDtype)DtypeObjnullnboolbuint8Cuint16Suint32Iuint64Lint8cint16int32iint64l halffloatefloatfdoublegstringu large_stringUbinaryzz time32[s]ttsttmttuttntdDtdmztss:ztsm:ztsu:ztsn:tDstDmtDutDn) z time32[ms]z time64[us]z time64[ns]z date32[day]z date64[ms]z timestamp[s]z timestamp[ms]z timestamp[us]z timestamp[ns]z duration[s]z duration[ms]z duration[us]z duration[ns]cd\rSrSrSrSrSrSrSrSr Sr S r S r S r S rS rSrSrSrSrSrSrSrSrSrg) ArrowCTypes=z Enum for Apache Arrow C type format strings. The Arrow C data interface: https://arrow.apache.org/docs/format/CDataInterface.html#data-type-description-format-strings r r rrsrrrrrrrr!r#r%r,r-zts{resolution}:{tz}ztt{resolution}N)__name__ __module__ __qualname____firstlineno____doc__NULLBOOLINT8UINT8INT16UINT16INT32UINT32INT64UINT64FLOAT16FLOAT32FLOAT64STRING LARGE_STRINGDATE32DATE64 TIMESTAMPTIME__static_attributes__r6Z/home/mande/repo/quber/.venv/lib/python3.13/site-packages/pandas/core/interchange/utils.pyr3r3=sj D D D E E F E F E FGGG FL F F &I DrPr3c(\rSrSrSrSrSrSrSrSr g) Endianness_z.Enum indicating the byte-order of a data-type.<>=|r6N) r7r8r9r:r;LITTLEBIGNATIVENArOr6rPrQrSrS_s8 F C F BrPrSc[U[5(a[R$U[R "S5:Xa[R $[U[5(aSSKnURnURRU5(aSURSUR3$URRU5(a,URbSUR SSUR3$["R%['U5S5nUbU$[)[UR*R-5S5nUbU$[U[.R05(a[R $[2R4"US5(a:[R6"U5SSn[R8R;US S 9$[U[<5(a5[R8R;UR SURS 9$[U[.R>5(a[R@$[CS US 35e) z Represent pandas `dtype` as a format string in Apache Arrow C notation. Parameters ---------- dtype : np.dtype Datatype of pandas DataFrame to represent. Returns ------- str Format string in Apache Arrow C notation of the given `dtype`. OrNzd:,ts:M) resolutiontzzConversion of z- to Arrow C format string is not implemented.)" isinstancerr3rDnpdtyperIrpyarrow pyarrow_dtypetypes is_decimal precisionscale is_timestampreunitPYARROW_CTYPESgetstrgetattrnameupperpd StringDtyper is_np_dtype datetime_datarMformatr BooleanDtyper=NotImplementedError)rhpapa_type format_strrds rQdtype_to_arrow_c_fmtrhs%)**   "((3- !!! E: & &%% 88  w ' '))*!GMM?; ; XX " "7 + + 0F Q('**6 6#''G d;  ! ejj&6&6&8$?J%((!!!  $ $%%e,Q/2 $$++zb+II E? + +$$++uzz!}+RR E2?? + +  LM rPcb[UR[R5(dgURR n[ UR5S:XagU(d [S5eUR5n[R"X0RURURS9$)a Rechunk a multi-chunk pyarrow array into a single-chunk array, if necessary. - Returns `None` if the input series is not backed by a multi-chunk pyarrow array (and so doesn't need rechunking) - Returns a single-chunk-backed-Series if the input is backed by a multi-chunk pyarrow array and `allow_copy` is `True`. - Raises a `RuntimeError` if `allow_copy` is `False` and input is a based by a multi-chunk pyarrow array. NzFound multi-chunk pyarrow array, but `allow_copy` is False. Please rechunk the array before calling this function, or set `allow_copy=True`.)rhruindex) rfrhrwrarray _pa_arraylenchunks RuntimeErrorcombine_chunksSeriesrur)series allow_copy chunked_arrayarrs rQ maybe_rechunkrs fllBMM 2 2LL**M =   A%  !   & & (C 99S 6;;fll SSrP)rhrreturnrs)rz pd.Seriesrr rzpd.Series | None)r; __future__rtypingnumpyrg pandas._libsrpandas.core.dtypes.dtypesrrrpandasrw TYPE_CHECKINGpandas._typingrrqr3rSrrr6rPrQrsR#   '  C C S c   c   c  C S S S S c cC  c!"#$=DD  5pTrP