'eddlZddlmZddlmZddlZddlmZddlm Z ddl Z ddl Z ddl Z ddl Z ddlZddlZddlmZddlZddlmZmZiadZd Zejd ejd ejd ejd ej dej!dej"dej#dej$dej%dej&dddej'dej(diZ)dZ*dZ+dZ,dZ-dZ.dZ/dZ0d Z1d!Z2d"Z3d#Z4d$Z5d%Z6d&Z7dEd'Z8 dFd*Z9d+Z:dGd,Z;d-Z< dHd/Z=d0ed1ed2zed3zd4d gzDZ>dEd5Z?d6Z@d7ZAdEd8ZB dEd9ZCd:ZDd;ZEddZHd?ZId@ZJdAZKdBZLdCZMdDZNdS)IN)Sequence)futures)deepcopy) zip_longest)sctypes) _pandas_api frombytesc "tstitjjdtjjdtjjdtjjdtjjdtjj dtjj dtjj dtjj d tjj d tjjd tjjd tjjd tjjdtjjdtjjdtjjdtjjdtjjdtjjditS)Nemptyboolint8int16int32int64uint8uint16uint32uint64float16float32float64datetimebytesunicode)_logical_type_mapupdatepalibType_NA Type_BOOL Type_INT8 Type_INT16 Type_INT32 Type_INT64 Type_UINT8 Type_UINT16 Type_UINT32 Type_UINT64Type_HALF_FLOAT Type_FLOAT Type_DOUBLE Type_DATE32 Type_DATE64 Type_TIME32 Type_TIME64 Type_BINARYType_FIXED_SIZE_BINARY Type_STRING5/croot/pyarrow_1707330824290/_h_env_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold/lib/python3.11/site-packages/pyarrow/pandas_compat.pyget_logical_type_mapr7+sw    " FNG" F f"  F f"  F w " F w " F w "  F w"  F "  F "  F "  F "I"  F y"  F  "  F "  F " F !" " F #" $ F  F )7 F  )" "    , r5ct} ||jS#t$rt|tjjrYdSt|tjjr)dt|j cYSt|tjj r |j dndcYSt|tjj rYdSYdSwxYw)N categoricalzlist[{}] datetimetzdatetimedecimalobject)r7idKeyError isinstancerrDictionaryTypeListTypeformatget_logical_type value_type TimestampTypetzDecimal128Type) arrow_typelogical_type_maps r6rDrDHs+--  ..     j"&"7 8 8  ==  BFO 4 4 $$%5j6K%L%LMM M M M  BF$8 9 9 #-=#<<<* L L L  BF$9 : : 99xx s" )C# AC#*C#=C#"C#r r rrrrrrrrrz datetime64[D]rstringrc t|jjS#t$rUt |jdrYdSt |jdkrYdSt j|}|dkrYdS|cYSwxYw)NrGr:datetime64[ns]rKr)_numpy_logical_type_mapdtypetyper?hasattrstrr infer_dtype)pandas_collectionresults r6get_logical_type_from_numpyrVks &'8'>'CDD     $*D 1 1 <<  & ' '+; ; ;###():;; X  99  s A8A8A83A87A8ch|j}t|dkrKt|d|}|Jt|j|jd}t|jj}nJt|dr)dtj |j i}d}nd}t|}||fS)Ncategorycat)num_categoriesorderedrGtimezonerM) rOrRgetattrlen categoriesr[codesrQrrtzinfo_to_stringrG)columnrOcatsmetadataphysical_dtypes r6get_extension_dtype_inforfzs LE 5zzZvuf--!$/22|  TZ-..   $ 7 7 A AB)U 8 ##r5ct|}t|\}}|dkr|j|jd}d}|Jt |t s5t d|t|j |9t |t s$Jt t|||dn||||dS)aConstruct the metadata for a given column Parameters ---------- column : pandas.Series or pandas.Index name : str arrow_type : pyarrow.DataType field_name : str Equivalent to `name` when `column` is a `Series`, otherwise if `column` is a pandas Index then `field_name` will not be the same as `name`. This is the name of the field in the arrow Table's schema. Returns ------- dict r<) precisionscaler=Nz6Column name must be a string. Got column {} of type {}Nonename field_name pandas_type numpy_typerd) rDrfrhrir@rR TypeErrorrCrP__name__)rbrlrIrm logical_type string_dtypeextra_metadatas r6get_column_metadatarus"$J//L#;F#C#C L.y  #-%     4 5 5 D K Kd4jj)      J!z&construct_metadata..s='G'G'G.8.E.E'Gu'G'G'Gr5N)rlrIrmFrz&The DataFrame has non-str index name `z@` which will be converted to string and not roundtrip correctly. stacklevellevelsnamesspandaspyarrow)libraryversion) index_columnscolumn_indexescolumnscreatorpandas_versionutf8)r^zipruappendr@rxrlrR_column_name_to_stringswarningswarn UserWarningr]r_get_simple_index_descriptorjsondumpsr __version__rrencode)columns_to_convertdf column_names index_levelsindex_descriptorspreserve_indextypesnum_serialized_index_levelsntypesdf_types index_typescolumn_metadatacolsanitized_namerIrdindex_column_metadatanon_str_index_nameslevel descriptorrrrrls r6construct_metadatars$#&'G'G:K'G'G'G#H#HZZF:f:::;H!<<==>KO+./A/;X,G,G))'^Z&s2<2@BBB x((((U"" -0{1B.D.D 3 3 )E:z*d++ z%jS.I.I%#**5:666*,UZ88%% H " ( ( 2 2 2 2 " # #a ' ' M09L000  + + + + X |<< Gbjo->??vu-- , ,KE43E4@@H  ! !( + + + + ,FHGG1N 4:.,&)>>$>*1      6&>>  r5ct|\}}t|}d|vrtjdtd|dkr|rJddi}|||||dS) NmixedzlThe DataFrame has column names of mixed type. They will be converted to strings and not roundtrip correctly.r|r}rencodingUTF-8rk)rfrVrrr)rrlrsrtrns r6rrs#;E#B#B L.-e44K+  @ A ' ' ' 'i!!!!$g."""   r5czt|tr|St|tr|dSt|tr/tt t t |St|trtd|dSt|S)a!Convert a column name (or level) to either a string or a recursive collection of strings. Parameters ---------- name : str or tuple Returns ------- value : str or tuple Examples -------- >>> name = 'foo' >>> _column_name_to_strings(name) 'foo' >>> name = ('foo', 'bar') >>> _column_name_to_strings(name) "('foo', 'bar')" >>> import pandas as pd >>> name = (1, pd.Timestamp('2017-02-01 00:00:00')) >>> _column_name_to_strings(name) "('1', '2017-02-01 00:00:00')" rz%Unsupported type for MultiIndex levelN) r@rRrdecodetuplemaprrrprls r6rr$s2$  D% {{6""" D% 54d;;<<=== D( # #?@@@ t t99r5ct|j|j|vrt|jSd|S)zReturn the name of an index level or a default name if `index.name` is None or is already a column name. Parameters ---------- index : pandas.Index i : int Returns ------- name : str Nz__index_level_{:d}__)rlrrC)indexirs r6_index_level_namerKs< z%*L"@"@&uz222%,,Q///r5ct|||}|jjs4tdt |j|t |||Sg}|durt|jng}g}g}|D]}||} t|}tj | r"td|| | | d| |g} g} t|D]\} } t| | |}t!| tjjr|t'| }nA| | | d|}| || ||| z}||| | |||fS)Nz Duplicate column names found: {}F-Sparse pandas data (column {}) not supported.)_resolve_columns_of_interestr is_unique ValueErrorrClist$_get_columns_to_convert_given_schema_get_index_level_valuesrrr is_sparserpr enumeraterr@pd RangeIndex_get_range_index_descriptor)rschemarrrrrconvert_fieldsrlrrindex_column_namesr index_levelrz all_namess r6_get_columns_to_convertr^s$*2vw??G :   . 5 5d2:6F6F G G   3BOOOL.<5-H-H)))  N " "h&t,,   % % N?FFtLLNN N !!#&&&d###D!!!!#L11 ( (; a>> {KN$= > > ,&/ <>r5cg}g}g}g}g}g}|jD]} || } d} n#t$r t|| } n7#ttf$r#td| wxYw|dur"t d| |At | tjj r"t d| d} YnwxYwt| } tj | r"td| | | } || || || | r?|| || || ||z} | ||||||fS)z Specialized version of _get_columns_to_convert in case a Schema is specified. In that case, the Schema is used as the single point of truth for the table structure (types, which columns are included, order of columns, ...). FzNname '{}' present in the specified schema is not found in the columns or indexzlname '{}' present in the specified schema corresponds to the index, but 'preserve_index=False' was specifiedNaname '{}' is present in the schema, but it is a RangeIndex which will not be converted as a column in the Table, but saved as metadata-only not in columns. Specify 'preserve_index=True' to force it being added as a column, or remove it from the specified schemaTr)rr?_get_index_level IndexErrorrCrr@rrrrrrpfieldr)rrrrrrrrrrlris_indexrrs r6rrs@LNL *%*% T(CHH    <&r400j) < < <..4fTll<<< < &&  &t ...!(sKN$=>>) ' (.vd|| 555HHH- 0't,,   % % N?FFtLLNN N T""!!#&&&e$$$D!!!  %  % %d + + +  $ $T * * *    $ $ $11I |%79J ,n >>s$ # C$?C$4A33A.C$#C$c|}||jjvr3t|r$t|t dd}|j|S)z_ Get the index level of a DataFrame given 'name' (column name in an arrow Schema). __index_level_)rr_is_generated_index_nameintr^get_level_values)rrlkeys r6rrs^ C 28>!!&>t&D&D!$s+,,R/011 8 $ $S ) ))r5cn tj||S#t$rt|cYSwxYwN)rrrprRrs r6 _level_namersI 4 4yys 44cdt|jtj|dtj|dtj|ddS)Nrangestartstopstep)kindrlrrr)rrlrget_rangeindex_attribute)rs r6rrsSEJ''5eWEE4UFCC4UFCC   r5cxttdg}fdt|DS)Nrc:g|]}|Sr4)r)ryrrs r6r{z+_get_index_level_values..s' 8 8 8!E " "1 % % 8 8 8r5)r^r]r)rns` r6rrs> GE8eW - -..A 8 8 8 8uQxx 8 8 88r5cr||td||j}n|fd|D}nj}|S)NzJSchema and columns arguments are mutually exclusive, pass only one of themc&g|] }|jv |Sr4)r)rycrs r6r{z0_resolve_columns_of_interest.. s 999bj1r5)rrr)rrrs` r6rrsa g1<== =  ,  9999g999* Nr5c t|d||\}}}}}}}g} |D]} | j} tj| rt j| dj} ntj| rZt| tj j r| dn | dd} t j| dj} nVt| | j d\} } tj| | } | t j| dj} | | t#||||||| }|| |fS)NT) from_pandasr)rvaluesris_categoricalrarrayrPis_extension_array_dtyper@rSeriesheadget_datetimetz_typerOr_ndarray_to_arrow_typerr)rrrrr_rrrrrrtype_r rds r6dataframe_to_typesrsh ""dNG D D Y E     %f - - ;HQD1116EE  1& 9 9 ;!+;>("*"*5AFF1III/0!u HU555:EE/FFMFEF11&%@@E}555: U!B m>5H eX %%r5Tc !t||||\}}}} } } } |Ht|t|j}} | |dzkr|dkrtj}nd}fd!d}|dkr!fdt | | D}ng}t j|5}t | | D]_\}}||jr | !||5| | !||` dddn #1swxYwYt|D]6\}}t|t j r|||<7d|D}|Zg}t ||D]3\}}||nd}| tj||4tj|}t#| ||| | ||}|jrt'|jn t)}||||}d}t|dkrn | dd }|d krH| dd }| dd }| dd } tt/||| }n#t0$rYnwxYw|||fS)Ndrc|d}d}n|j}|j} tj||d}n_#tjtjtjf$r6}|xjd|j |j fz c_|d}~wwxYw|s@|j dkr5tdt||j |S)NT)rPrsafez0Conversion failed for column {!s} with type {!s}rz>Field {} was non-nullable but pandas column had {} null values)nullablerPrr ArrowInvalidArrowNotImplementedErrorArrowTypeErrorargsrCrlrO null_countrrR)rrfield_nullablerrUers r6convert_columnz+dataframe_to_arrays..convert_columnIs =!NEE"^NJE Xc4dKKKFF+!#    FFIsx336 6FFG    M&"3a"7"7228&U9?9J3L3LMM M s1&B 1BB ct|tjo/|jjo#t |jjtjSr) r@npndarrayflags contiguous issubclassrOrPinteger)arrs r6_can_definitely_zero_copyz6dataframe_to_arrays.._can_definitely_zero_copy_s;3 ++7 $739>2:66 8r5c.g|]\}}||Sr4r4)ryrfrs r6r{z'dataframe_to_arrays..es?GGGa!.A&&GGGr5cg|] }|j Sr4rPryxs r6r{z'dataframe_to_arrays..ts $ $ $QV $ $ $r5rjrrrrrr)rr^rr cpu_countrrThreadPoolExecutorrrsubmitrr@FuturerUrrrrdrrxr with_metadatarr)"rrrnthreadsrrrrrrrrrnrowsncolsrarraysexecutorrr r maybe_futrfieldsrlrpandas_metadatardn_rowsrrrrrs" ` @r6dataframe_to_arraysr4s/r6>/688 Y 2wwBJu 53;  5199|~~HHH,888 1}}GGGG!"4nEEGGG  ' 1 1 IX.?? I I1,,QX66IMM..A"6"67777MM(//.!Q"G"GHHHH  I I I I I I I I I I I I I I I I&f-- / /LAy)W^44 /%,,..q $ $V $ $ $E ~y%00 1 1KD%+44D MM"(4// 0 0 0 06""(B m>5O-3OGx(((H OOO$$$  ! !( + +FF 6{{a $Q'/Dw)!,W5(+F3(+F3U5$5566    D  66 !!s&(A1D&&D*-D*AJ:: KKc|jjtjkr||fSt j|r&|$|j}|j}tj ||}n|tj |j}||fSr) rOrPr datetime64r is_datetimetzrGunitr timestampfrom_numpy_dtype)rrOrrGr s r6rrsw |BM))u} ''2EM Xz T2&& #FL11 5=r5c$ddlmcm}|dd}|d}d|vrGtj||d|d}|||}nd |vrQtj |j \}} t||d } ||||j | }nd |vr*|tj||}nd |vr|d } t|d ksJ||d} || } t!| dst#d| | }|||}n|||}|S)a Construct a pandas Block from the `item` dictionary coming from pyarrow's serialization or returned by arrow::python::ConvertTableToPandas. This function takes care of converting dictionary types to pandas categorical, Timestamp-with-timezones to the proper pandas Block, and conversion to pandas ExtensionBlock Parameters ---------- item : dict For basic types, this is a dictionary in the form of {'block': np.ndarray of values, 'placement': pandas block placement}. Additional keys are present for other types (dictionary, timezone, object). columns : Column names of the table being constructed, used for extension types extension_columns : dict Dictionary of {column_name: pandas_dtype} that includes all columns and corresponding dtypes that will be converted to a pandas ExtensionBlock. Returns ------- pandas Block rNblock placement dictionaryr[)r_r[)r%r\)r%klassrOr=py_arrayr__from_arrow__zGThis column does not support to be converted to a pandas ExtensionArray)pandas.core.internalscore internalsgetrcategorical_type from_codes make_blockr datetime_datarOmake_datetimetzDatetimeTZBlockpickleloadsr^rQrr))itemrextension_columns_int block_arrr%rYr$r rrOrrl pandas_dtype pd_ext_arrs r6_reconstruct_blockr<s8)(((((((($''I[!It*55 $|"4O6%%y99 t  "9?33ad:&677 Y&*&:&+ -- T   Y 7 7*3 55 t  :9~~""""y|$(. |%566 ;:;; ;!0055  i@@ Y?? Lr5ctjrd}tj|}tj||S)NnsrG)ris_v1rrstring_to_tzinfodatetimetz_type)r rGs r6r2r2sC   $ $B  &t 3 3 33r5Fcbddlm}ddlm}g}g}|jj} |s_| ]| d}| dg}| d} t|| }t|| ||\}} t|||} n5tj |j } t|g|} t|t|||} t!|||| }| | g}|||}tjr|||j}n ||}|S)Nr) BlockManager) DataFramerrr)r*rDpandasrErrr-_add_any_metadata_reconstruct_index_get_extension_dtypesrrrnum_rows'_check_data_column_metadata_consistency_deserialize_column_index_table_to_blocks is_ge_v21 _from_mgraxes)optionstabler_ignore_metadata types_mapperrDrE all_columnsrrrrext_columns_dtypesrblocksrPmgrrs r6table_to_dataframerYsr322222      KNl2O  L:%i0 (,,-=rBB+O<!%99)%1B*5|EE u2 ; ..))%.9925"lKK+K888'{NKKG guj:L M MF U D ,vt $ $C  ch / / Ys^^ Ir5cPh|]#}ttj|$Sr4)rRrrO)rytyps r6 r\s8!!!  !!!r5ruintfloatr=c&i}tj|S|D]x} |d}n#t$r |d}YnwxYw|d}|tvrCtj|}t |tjrt |dr|||<y|jD]S}|j} t | tj r0 | }|||j <C#t$rYOwxYwT|r(|jD] }|j} || }| |||j <!|S)a Based on the stored column pandas metadata and the extension types in the arrow schema, infer which columns should be converted to a pandas extension dtype. The 'numpy_type' field in the column metadata stores the string representation of the original pandas dtype (and, despite its name, not the 'pandas_type' field). Based on this string representation, a pandas/numpy dtype is constructed and then we can check if this dtype supports conversion from arrow. Nrmrlror))rextension_dtyper?_pandas_supported_numpy_typesr:r@rQrrPrBaseExtensionTypeto_pandas_dtyperlNotImplementedError) rRcolumns_metadatarT ext_columnscol_metarlrOr:rr[s r6rIrIsK"*% 5 5 $L)DD $ $ $F#DDD $& 5 5 5'3E::L, (CDD 5<)9::5(4K%77j c2/ 0 0 7 7"2244 +7 EJ'''     77\ 7 7E*C'<,,L'*6 EJ' s447C C#"C#c<td|DsJdS)Nc3FK|]}|ddurd|vp |dduVdS)rlNrmr4ryrs r6 z:_check_data_column_metadata_consistency..ZsW  6d  0|q0JQvYd5Jr5)all)rUs r6rKrKUsF   r5cd|jD}|rd|Dfd|D}n|}t|dkr tjnd}|s tj|}nMtjjtt||d|Dpd}t|dkrt||}t|}|S) NcZg|](}t|trt|n|)Sr4)r@rr r s r6r{z-_deserialize_column_index..asA999'1E&:&:Ailll999r5c ni|]2}|dt|d|d3Srmrl)r-rrjs r6 z-_deserialize_column_index..dsI    EE, 7& B B C CQvY   r5c<g|]}||Sr4r-)ryrlcolumns_name_dicts r6r{z-_deserialize_column_index..hs7   26  ! !$ - -   r5rc|fSrr4)r s r6z+_deserialize_column_index..qs!r5cg|] }|d Srr4)ry col_indexs r6r{z-_deserialize_column_index..{sEEE9V$EEEr5rr) rr^ast literal_evalrrIndex MultiIndex from_tuplesrr"_reconstruct_columns_from_metadata _flatten_single_level_multiindex) block_tablerUrcolumn_stringscolumns_valuesto_pairrrts @r6rLrL`sB99*7999N (          :H   ( #&n"5"5"9"9c~~G  .&&~66.+77 Wn-- . .EEnEEEM8    >Q4WnMM/w77G Nr5cZd|D}g}g}|}|D]}t|trt|||||\}} } | 1n|ddkr_|d} tj|d|d|d| } t | t |krn(td |d| | | | tj} t |d kr| j || } nht |d kr;|d } t| | j s| | |d  } n| |j } || fS)NcHi|]}|d|d| Srprsrjs r6rqz&_reconstruct_index..s<  lAfI&&r5rrrlrrr)rrlzUnrecognized index kind: {}rryrr)r@rR_extract_index_levelrrrr^rrCrr} from_arraysr|rJ) rRrrUrTfield_name_to_metadata index_arrays index_names result_tablerzr index_namerrs r6rHrHs LKL"'' eS ! ! 54H|U,BL5R5R 1L+z"#6]g % %vJ%.33E'N49&M9>v9C4EEK;3u::--.:$fU6]3355 5K(((:&&&& B <1 )),k)JJ \  a  Q%** 9HHUQH88E en--  r5c||d}t||}|j|}|dkr|ddfStj}||} | |j} t| dr | j j s| } t| j tjjr<| j j0t%|| d| j j} n|| | jd} ||j|}|| |fS)Nrl)rTrF)copy)rOr) _backwards_compatible_index_namerget_field_indexrrrb to_pandasrrQr writeablerr@rPrrrFrG make_tz_awarerrO remove_column) rRrrmrrT logical_namerrrrrrs r6rrs=)*5f=L1*lKKJ $$Z00ABwwT4'' B ,,q//C ]] ] 5 5 #(BF011Hchk6M#BIIf5I$A$A38;OO iifliGG --++J77L j 00r5c4||krt|rdS|S)a1Compute the name of an index column that is compatible with older versions of :mod:`pyarrow`. Parameters ---------- raw_name : str logical_name : str Returns ------- result : str Notes ----- * Part of :func:`~pyarrow.pandas_compat.table_to_blockmanager` N)r)raw_namers r6rrs($<$.=s8000&+ c%jj!!000r5c g|]D\}}||dt|j|ddfES)rnroN)r-rRrO)ryrrxs r6r{z6_reconstruct_columns_from_metadata..Bs^ E9  mS-=-=>> |T * * ,r5) fillvaluerrr:rrdr\T)utcry)rrr]rroperator methodcallerrrbytes_rrrrA to_datetime tz_convertrOastyperr}r) rrrlabels levels_dtypes new_levelsencoderrr: numpy_dtyperOrGrs @r6rr#s, BWh - - :'F "7 + +0000/5000F !, Nb! ! ! MJ#Hg66G,9!!(|[*<88 BI  IIg&&E < ' '((q!*-j9;;BNN5dN33>>rBBEE [E ! !LL''E ;+ % %,,*F*FLL--E%    ==V7== A AAr5c |jtj|||t }fd|DS)Nc2g|]}t|Sr4)r<)ryr6rr7s r6r{z$_table_to_blocks..ks6    tW.? @ @   r5)rrrtable_to_blocksrkeys)rQrr_r7rUrs ` @r6rMrMdsu&G V # #G[*$():)?)?)A)A$B$BDDF         r5c,tj}t||jrq|jdkrf|j\t |\}j}|jstd| fd|D||j dS|S)NrzFound non-unique column indexc0g|]}|dkr|ndS)rNr4)ry_labelrs r6r{z4_flatten_single_level_multiindex..|s) K K K&v||VF^^ K K Kr5r)rOrl) rrr@r}nlevelsrrrOrrr|r)rrrrOrs @r6rros B%'' EMQ,>,>,'..  ><== =xx K K K KF K K KQ   Lr5ci}i}|j}|d}d|D}t|}t|d|z }t|dD]3\}} | d} | s| d} ||kr |||z } | d} || } | dkr| dd kr|| } t | jtjj s| d } | s| d }|r|| jj krs| }tj d | }tj ||}tj|| j||| <||| <5t|dkrg}g}t#t|jD]x}||vr7||||||=|||||j|ytj|tj|S|S)Nrc<g|]}t|t|Sr4)r@rR)ryidx_cols r6r{z%_add_any_metadata..s6222"7C002W222r5rrmrlrjrrnr:rdr\r>r?r r)r)rr^rr-rr@rPrrrFrGrr!ArrayrrrlrrTabler)rRrmodified_columnsmodified_fieldsrrn_index_levels n_columnsrrgridxrrd metadata_tz converted tz_aware_typerrrs r6rGrGsO \F#O4M22M222M''NOI.//.@I!!;<<:: 8<< -- "'HI~~(Y7!$$X.. "99 &,66Cj!#(BF,@AA#J/&ll:66 :;#(+#=#= # I$&L+$F$F$FM$&H$8$8>K%9%M%MM,.8F3K4D4A,C,COC(,9$S) q  s5<(()) / /A$$$/2333 oa01111uQx((( el1o....x##GBIf4E4E#FFF r5ctj|}|jdj|}|S)zB Make a datetime64 Series timezone-aware for the given tz r)rrrAdt tz_localizer)seriesrGs r6rrsC   $ $Bi##E** 2 Mr5r)rNT)NN)NFN)Orzcollections.abcr concurrentrconcurrent.futures.threadrr itertoolsrrrr4rrnumpyrnumpy.core.numerictypesr _np_sctypesrr pyarrow.librr rr7rDbool_r rrrrrrrrrstr_rrNrVrfrurrrrrrrrrrrrrrr<r2rYrarIrKrLrHrrrrrrrrrMrrGrr4r5r6rs:& $$$$$$! !!!!!!  ::::::........:$HfGVHgHgHgHgIxIxIxJ J VGXIw$   $$$&***ZSSSl($$$N000&=>=>=>@=>=>=>@ * * *999   &&&&DIM!_"_"_"_"D   &<<<<~444JN!!!!L!!E"[%88;w;OO6"#!!!6666r%%%P3333n?C1111<0///  "w Ygx Z  %%%,>B>B>BB   (:::Br5