!h6dZddlmZddlZddlZddlmZddlm Z m Z m Z ddl Z ejrddlmZiddd d d d d dddddddddddddddddddd d!d"d#d$d%d&d'd(d)d*d+d,d-d.d/d0d1d2d3d4d5 ZGd6d7ZGd8d9ZdDd>ZdEdCZdS)FzE 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]c^eZdZdZdZdZdZdZdZdZ dZ d Z d Z d Z d Zd ZdZdZdZdZdZdZdZdS) ArrowCTypesz 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____doc__NULLBOOLINT8UINT8INT16UINT16INT32UINT32INT64UINT64FLOAT16FLOAT32FLOAT64STRING LARGE_STRINGDATE32DATE64 TIMESTAMPTIMEWc:\xampp_lite_8_4\www\timesheet\venv\Lib\site-packages\pandas/core/interchange/utils.pyr3r3=s{ D D D E E F E F E FGGG FL F F &I DDDrMr3c"eZdZdZdZdZdZdZdS) Endiannessz.Enum indicating the byte-order of a data-type.<>=|N)r5r6r7r8LITTLEBIGNATIVENArLrMrNrPrP_s(88 F C F BBBrMrPdtyperreturnstrct|tr tjS|t jdkr tjSt|trddl}|j }|j |rd|j d|j S|j |r|jd|jdd|jSt"t'|d}||St)t|jd}||St/j|drAt j|dd}tj|d St|t8r1tj|jd|j St|t:jr tjStAd |d ) a  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.)! isinstancerr3rAnprYrFrpyarrow pyarrow_dtypetypes is_decimal precisionscale is_timestamprdunitPYARROW_CTYPESgetr[getattrnameupperr is_np_dtype datetime_datarJformatrpd BooleanDtyper:NotImplementedError)rYpapa_type format_strrcs rNdtype_to_arrow_c_fmtr}hs%)**  "(3--  !! E: & & % 8  w ' ' 7;);;GM;; ; X " "7 + + 7 0F6 Q66'*66 6#''G d;;  ! ej&6&6&8&8$??J uc""  %e,,Q/2 $++zb+III E? + + $++uz!}+RRR E2? + +  MMMM  rMseries pd.Series allow_copypd.Series | Nonec(t|jtjsdS|jj}t |jdkrdS|std| }tj ||j|j |j S)a Rechunk a multi-chunk pyarrow array into a single-chunk array, if necessary. - Returns `None` if the input series is not backed by a multi-chunk pyarrow array (and so doesn't need rechunking) - Returns a single-chunk-backed-Series if the input is backed by a multi-chunk pyarrow array and `allow_copy` is `True`. - Raises a `RuntimeError` if `allow_copy` is `False` and input is a based by a multi-chunk pyarrow array. NzFound multi-chunk pyarrow array, but `allow_copy` is False. Please rechunk the array before calling this function, or set `allow_copy=True`.)rYrrindex) rerYrwrarray _pa_arraylenchunks RuntimeErrorcombine_chunksSeriesrrr)r~r chunked_arrayarrs rN maybe_rechunkrs flBM 2 2tL*M =   A%%t   !    & & ( (C 9S 6;fl S S SSrM)rYrrZr[)r~rrr rZr)r8 __future__rtypingnumpyrf pandas._libsrpandas.core.dtypes.dtypesrrrpandasrw TYPE_CHECKINGpandas._typingrror3rPr}rrLrMrNrs9#"""""   (''''''  C C S c   c   c  C S S S S c cC  c!"#$=DD        0000fTTTTTTrM