ɯeiFUddlZddlZddlZddlZddlZddlZddlZddlZddlZddl Z ddl Z ddl Z ddl Z ddl Z ddlZddlZddlZddlZddlZddlZddlZddlZddlmZmZmZmZddlmZmZddl mZddlmZddlm Z ddl m!Z!ddl"m#Z#m$Z$m%Z%m&Z&m'Z'm(Z(m)Z)m*Z*m+Z+m,Z,m-Z-m.Z.m/Z/m0Z0m1Z1m2Z2ddl3Z4dd l5m6Z6dd l7m8Z8m9Z9dd l:m;Z;mZ>m?Z?dd l@mAZBddlCmDZDddlEmFZFdd lGmAZHe$rddlImJZJmKZKddlLmMZMddlNmOZO ddl7mPZPe jdZSdZTdZUdZVeTeUgZWeWeVgzZXdZYdZZdZ[deZde[dZ\dZ]dZ^ejd e\d!e\d"e\d#Z`eje]Zaeje^Zbd$e\dZcd%ZdejejzZgejd&ejZiejd'ejZjid(d)d*d+d,d-d.d/d0d1d2d3d4d5d6d7d8d9d:d;dd?d@dAdBdCdDdEdFdGdHdIdJdKdLdMdNdOdPdQdRdS ZkekjDcic]\}}|| c}}ZmdTZndUZohdVZphdWZqhdXZrdYZsdZZte jje jjexd[Zyd\Zzd]ezd^Z{d_d`dadbdcddZ|e jje jjexdeZ}dfZ~dgZdZdhZdiZgdjZdkZeZeee> ZGdldmeZidnhdodphdqdrhdsdthdudvhdwdxhdydzhd{d|hd}d~hddhddhddhddhddhddhdddhddhhdddhddhddhddhddhdZeejZejDcic]\}}|D]}||c}}}ZeejZdZdede/eeffdZdefdZdedefdZedefdZedefdZedefdZedefdZedefdZedefdZdedefdZdedefdZdedefdZdedefdZdZdedefdZdededefdZdedefdZdeddfdZdedefdZdedefdZdede/eeffdZdedefdZdedefdZdedefdZdefdZejX dkdede-ededede#ef d„Zde%de*fdĄZde%de/e*effdńZdddededefdʄZ dldededede-edededefd̈́Zdede0ededefdфZdmdedefdӄZ dnde-e'eefde-ededede'eeff dׄZdd؜dededeeeffdڄZdedefdۄZd܄ZdedefdބZdodedefdZdZde1e*e8e*dfde/e-e*ee-e*e&ffdZ dpde*e%de-e1e*e8e*dfdede*eFfdZ dpde9de-e*e8dede)eFfdZGddeZGddZiZe'eefed<dqdedededdfdZGddZGddZdede1ejeffdZdede1ejeffdZeGddeZeGddeZeGddeZGddZeΫaeeÐd<defdZАde̐deddfdZe2de&ZҐdedefdZӐd e+d d ed ed ede&f dZԐd e+d d ede&fdZՐdddd ed ed ede&fdZ֐dddd ed ed ede&fdZאd ede&fdZؐdddd ed ed ede&fdZِdededefdZ drde-e*e1ee/eeffdeddfdZېde1de(edfddfdZܐde'ee%fd e.ede/e'ee%fe'ee%fffd!Zݐde'ee%fde/e'ee%fe'ee%fffd"Zސde'ee%fde/e'ee%fe'ee%fffd#Zߐd$ed%e'eefdefd&Zd'edefd(Zd'ede*efd)ZdZd*Zejd+ejZejd,Zdsded-edefd.Zdedefd/Zd0edefd1Zd2edefd3Zejd4Zd2edefd5Zd6d7d8ed9d:d;e-e1e(d<d7fd=e-d<f d>Zd?eddfd@ZdAe%defdBZdCe1eefdefdDZdEe1dFe/dGefe'eefffdHZGdIdJe>Zde/e?effdKZGdLdMZeZeeÐdN<GdOdPeZdQe*dRdefdSZdTZdUZdVefdWZdXedYe*edefdZZGd[d\e,Zd]ed^e*ed_ede*d`fdaZ dtdbedce1e'edFfe*dFfddeddFfdeZdfe1dgdheddRfdiZejXde&geffdjZy#eQ$re8ZPYwxYwcc}}wcc}}}w(uN)EnumIntEnumautounique) lru_cachewraps)count) JSONEncoder perf_counter)Random)IO TYPE_CHECKINGAnyCallableDictIterableIteratorListLiteral NamedTupleOptionalSetTupleTypeUnionTypeVar)FIELD_ID_TO_NAME)ResultMetadataSnowflakeCursor)OPERATING_SYSTEMPLATFORM)MissingOptionalDependencyModuleLikeObject)VERSION)SnowparkClientExceptionMessagesRow) SnowflakePlanQueryLineInterval Selectable)TimestampTimeZone)ResultMetadataV2zsnowflake.snowpark@zsnow:///z([a-zA-Z_][\w\$]{0,255})z("([^"]|""){1,255}")(|)z("([A-Z_][A-Z0-9_\$]{0,255})")z([a-zA-Z0-9_\$]{0,255})z^((z \.){0,2}|(z\.\.))$z(%?SNOWPARK_TEMP_z^(\s|\()*(select|with)z^\s*with\s+\w+\s+as\s+procedurezabsl-pyabslz async-timeout async_timeoutattrsattrbrotlipybrotlizcharset-normalizercharset_normalizerz google-authz google.authzgoogle-auth-oauthlibgoogle_auth_oauthlibz google-pastapastagrpciogrpczimportlib-metadataimportlib_metadatancursescursesz py-xgboostxgboostzpyasn1-modulespyasn1_modulespyjwtjwt pyopensslOpenSSLpysockssockszpython-dateutildateutil flatbufferstorchyamlrequests_oauthlibsklearnsqlite3tensorboard_plugin_wittensorflow_estimatortyping_extensions) zpython-flatbufferspytorchpyyamlzrequests-oauthlibz scikit-learnsqliteztensorboard-plugin-witztensorflow-estimatorztyping-extensions)z.pycz.pyoz.pydz.pyi)PARQUETORCAVROJSONCSV> FORCEPURGEON_ERROR SIZE_LIMITENFORCE_LENGTHTRUNCATECOLUMNSRETURN_FAILED_ONLYLOAD_UNCERTAIN_FILESMATCH_BY_COLUMN_NAME>SINGLE OVERWRITE MAX_FILE_SIZEDETAILED_OUTPUTINCLUDE_QUERY_ID> FILESPATTERNTRY_CAST FILE_FORMAT FORMAT_NAME COPY_OPTIONS INFER_SCHEMATARGET_COLUMNSTRANSFORMATIONSVALIDATION_MODEFORMAT_TYPE_OPTIONSINFER_SCHEMA_OPTIONSENFORCE_EXISTING_FILE_FORMATROWTAGROW_DATAz xml_reader.pyzDataFrameReader.xml[rowTag]z/* Python:snowflake.snowpark.z */xpath_array_handlerxpath_string_handlerxpath_boolean_handlerxpath_int_handlerxpath_float_handler)arraystringbooleanintfloatzxpath_handlers.py QUERY_TAG TEMPORARYzSCOPED TEMPORARY)temp temporary transientcxddlm}|} tjd}ddlm}|S#t $rY|SwxYw)zRHelper function to lazily import pandas and return MissingPandas if not installed.r) MissingPandaspandas DataFrame)snowflake.connector.optionsr importlib import_modulerr ImportError)rrrs d/var/www/html/glpi_dashboard/venv/lib/python3.12/site-packages/snowflake/snowpark/_internal/utils.py_pandas_importerrsD9 _F ((2$ M   M s , 99c<eZdZdZdZdZdZdZdZdZ dZ d Z d Z d Z d Zy )TempObjectTypeTABLEVIEWSTAGEFUNCTIONrprCOLUMN PROCEDURETABLE_FUNCTION DYNAMIC_TABLEAGGREGATE_FUNCTIONCTEN)__name__ __module__ __qualname__rrrrrprrrrrrrrrrs? E D EHKI FI%N#M- Crryear>yyryyyrsyyyryyyyyearsquarter>qqtrqtrsrquartersmonth>mmmonmonsrmonthsweek>wwkwywoyr weekofyearday>dddrdays dayofmonthhour>hhhhrhrsrhoursminute>mmiminminsrminutessecond>ssecsecsrseconds millisecond>msmsecr milliseconds microsecond>ususecr microseconds nanosecond>nsnsecnanosecnsecondnanosecsnsecondsr nanoseconds dayofweek>dwdowweekdayr dayofweekiso>dw_isodow_iso weekday_isor dayofyear>dydoyyeardayrweekiso>rweek_iso weekofyearisoweekofyear_iso yearofweek yearofweekiso>epoch epoch_second epoch_secondsepoch_millisecondepoch_millisecondsepoch_microsecondepoch_microsecondsepoch_nanosecondepoch_nanoseconds timezone_hourtzhtimezone_minutetzm)rrrrrrc`|j}|tvr t|St|d)Nz' is not a recognized date or time part.)lowerDATETIME_ALIASESALIASES_TO_DATETIME_PART ValueError)part lowered_parts runalias_datetime_partr =s4::>#&LFD [F  &D 4<rnamecXtj|stj|yN)SNOWFLAKE_OBJECT_RE_PATTERNmatchr&GENERAL_INVALID_OBJECT_NAMErs rvalidate_object_namerLs& & , ,T 2-II$OO 3rstage_locationcf|j}|s td|ddk(r td|S)Nzzstage_location cannot be empty. It must be a full stage path with prefix and file name like @mystage/stage/prefix/filenamer0zRstage_location should end with target filename like @mystage/prefix/stage/filename)stripr )rs rvalidate_stage_locationr!QsM#))+N  I  bS  `   rcjdjtDcgc]}|t|c}Scc}wN.)joinsnowpark_versionstrrs r get_versionr)^s( 88%5GSVG HHG0 0c*tjSr)platformpython_versionrrrget_python_versionr.cs  " " $$rcttdxs.tjjxsdtjvS)Nps1snowbook)hasattrsysflags interactivemodulesrrris_interactiver7hs, 3  T#))"7"7 T:;TTrcjdjtDcgc]}|t|c}Scc}wr#)r%connector_versionr'r(s rget_connector_versionr:ms( 88%6H!-SVH IIHr*c*tjSr)r,systemrrr get_os_namer=rs ?? rcy)NPythonSnowparkrrrrget_application_namer@ws rcJ|jdxr|jdS)N') startswithendswithrs ris_single_quotedrE|s ??3  6DMM#$66rc0tj|duSr)/SNOWFLAKE_CASE_INSENSITIVE_QUOTED_ID_RE_PATTERN fullmatchrs r'is_snowflake_quoted_id_case_insensitiverIs : D DT JRV VVrc0tj|duSr)5SNOWFLAKE_CASE_INSENSITIVE_UNQUOTED_SUFFIX_RE_PATTERNrHrs r-is_snowflake_unquoted_suffix_case_insensitiverLs=GGM rcj|j}t|r|dd}|jdd}|S)Nr\'rB)r rEreplacernew_names runwrap_single_quoterSs7zz|H!Ab>s+H Orc&|jddS)NrBrO)rP) input_strs rescape_single_quotesrVs   S% ((rsqlcbtj|duxrtj|duSr)#SNOWFLAKE_SELECT_SQL_PREFIX_PATTERNr%SNOWFLAKE_ANONYMOUS_CALL_WITH_PATTERN)rWs ris_sql_select_statementr[s3+11#6dB E 1 7 7 < Drpathis_localc|rdgnt}trS|rtdk(rjddj jddt fd|Ds |dddS) a| Get a normalized path of a local file or remote stage location for PUT/GET commands. If there are any special characters including spaces in the path, it needs to be quoted with single quote. For example, 'file:///tmp/load data' for a path containing a directory named "load data". Therefore, if `path` is already wrapped by single quotes, we do nothing. file://Windows\r0rBrOc3@K|]}j|ywrrC).0prefixr\s r z!normalize_path..s>6tv&>r)SNOWFLAKE_PATH_PREFIXES_FOR_GETrEr!rPr any)r\r]prefixess` rnormalize_pathrks' {,KH $ 1||D#& ::<  U +D >X> >1+tf% tfA;rc|jdxsJ|jdxs7|jdxs$|jdxs|jdS)Nzs3://z s3china://zs3gov://zazure://zgcs://rcr\s r is_cloud_pathrns[   % ??< ( % ??: & % ??: & % ??8 $ rconfigcftjdkDrtjd|dyy)NrNzQYou might have more than one threads sharing the Session object trying to update z. Updating this while other tasks are running can potentially cause unexpected behavior. Please update the session configuration before starting the threads.) threading active_count_loggerwarning)ros r0warn_session_config_update_in_multithreaded_moderus8!# _hh h $rct|dS)NFr]rkrs rnormalize_remote_file_or_dirrys $ //rfilect|dS)NTrwrx)rzs rnormalize_local_filer|s $ ..rc>t|}|jddS)z/Split a file path into directory and file name.r0rN)maxsplit)rSrsplitrms r split_pathrs t $D ;;sQ; ''rcbt|tfdtDrStS)Nc3@K|]}j|ywrrc)rdrerRs rrfz5unwrap_stage_location_single_quote..s U68  v & Urg)rSrirh STAGE_PREFIXrQs @r"unwrap_stage_location_single_quoters0"4(H U5T UU^H: &&rcr|j}t|r|dd}|jdr|ddS|S)NrNrr_)r rErC)rz trim_files rget_local_file_pathrs@ I "aO I&} rudf_namectjd|r|Sdjtjdd|t t |S)z0Get the valid stage prefix when uploading a UDF.z[\w]+$z{}_{}z\W)rerformatsubabshash)rs rget_udf_upload_prefixrs< xx 8$~~bffUB93tH~;NOOrc.tjddS)zGet a random unsigned integer.rl)randomrandintrrr random_numberrs >>!U ##rF leading_path add_init_pyignore_generated_py_filec #Ktjj|st|d|r!|j |st |d||r|ntjj |d}tj}tj|dtj5}tjj|}tjj|tjj|k7r|jtjj||ddtjj|}tjj|tjj|k7rtjj!|rtj"|D]\}} } |rd|vr|j%|tjj||| D]j} |r| j't(rtjj || } |j%| tjj| |ln0|j%|tjj||d d d ||j+y #1swYxYww) avCompresses the file or directory as a zip file to a binary stream. Args: path: The absolute path to a file or directory. leading_path: This argument is used to determine where directory should start in the zip file. Basically, this argument works as the role of `start` argument in os.path.relpath(path, start), i.e., absolute path = [leading path]/[relative path]. For example, when the path is "/tmp/dir1/dir2/test.py", and the leading path is "/tmp/dir1", the generated filesystem structure in the zip file will be "dir2/test.py". The leading path will compose a namespace package that is used for zipimport on the server side. ignore_generated_py_file: Whether to ignore some generated python files in the directory. Returns: A byte stream. is not foundz doesn't lead to z..r)mode compressionr0r __pycache__N)osr\existsFileNotFoundErrorrCr r%ioBytesIOzipfileZipFile ZIP_DEFLATEDdirnamerealpathwritestrrelpathisdirwalkwriterDGENERATED_PY_FILE_EXTclose) r\rrr start_path input_streamzfcur_pathr_filesrzfilenames rzip_file_or_directory_to_streamrs"0 77>>$ 4& 677DOOL9L>):4&ABB".277<<d3KJ:: 77??4(ggx(BGG,<,6 9>>s&B/K1C0K"DK6KKKinputsc|t|dk(r+t|dtttfrg|dS|dgSg|S)z+Convert the positional arguments to a list.rNrlen isinstancelisttuplesetrs rparse_positional_args_to_listr/sM 6{a&vay42DELfQiL LRSTI; yrcxt|dk(r't|dtttfr g|ddfSg|dfS)zmConvert the positional arguments to a list, indicating whether to treat the argument list as a variadic list.rNrFTrrs r&parse_positional_args_to_list_variadicr9sD 6{aJvay42DE&) e$$& 4  r hash_algozhashlib._hashlib.HASH chunk_sizewhole_file_hashct|d5}|j|}|j||r)|r'|j|}|j||r|r'dddy#1swYyxYw)ad Reads from a file and updates the given hash algorithm with the read text. Args: hash_algo: The hash algorithm to updated. path: The path to the file to be read. chunk_size: How much of the file to read at a time. whole_file_hash: When True the whole file is hashed rather than stopping after the first chunk. rbN)openreadupdate)rr\rrfdatas r _hash_filerAsi dD #Qvvj!66*%D   T "###s A A$$A-additional_info algorithmctjj|st|dt j |}tjj |rt||||nUtjj|r'd}tj|D] \}} } |rd|vrt| D]*} |r| dk(r |j| jd,t| D]} |r| jtr|j| jdtjj|| } tjj!| }|rt|| ||||z }||kst#|||z }||z }t|| |dnt%|d|r |j|jd|j'S)aCalculates the checksum of a file or a directory. Args: path: the path to a local file or directory. If it points to a file, we read a small chunk from the file and calculate the checksum based on it. If it points to a directory, the names of all files and subdirectories in this directory will also be included for checksum computation. chunk_size: The size in byte we will read from the file/directory for checksum computation. ignore_generated_py_file: Whether to ignore some generated python files in the directory. additional_info: Any additional information we might want to include for checksum computation. algorithm: the hash algorithm. whole_file_hash: When set to True the files will be completely read while hashing. Returns: The result checksum. rrrutf8Fz/ can only be calculated for a file or directory)rr\rrhashlibnewisfilerrrsortedrencoderDrr%getsizerr  hexdigest)r\rrrrrr current_sizerdirsrdirrzr file_size read_sizes rcalculate_checksumrXs8 77>>$ 4& 677 I&I ww~~d9dJ@ t  $&GGDM F GT5'MW,Dd| 5+}0D  F!34 5u  F+ >S0T  V!4577<<6GGOOH5 "y(JP I-L!J. #IzL/H II I-Ly(IuE! F F6I;&UVWW//78     rvalue enum_class except_strc  ||S#t$r>t|ddj|Dcgc]}|jncc}wc}wxYw)Nz must be one of , )r r%r)rrres r str_to_enumrsY %   l*499z5R!agg5R5R+S*T U   s A>A skip_levelscvtjt|z}dj|r |d| S|S)N)limitr) traceback format_stackQUERY_TAG_TRACEBACK_LIMITr%)rstacks rcreate_statement_query_tagrs:  " ")B[)P QE 77;5;,' BBE BBrstatement_paramsexists_session_query_tagcollect_stacktracec\|s |rt|vs|s|S|xsi}t|dz|t<|SNrN)QUERY_TAG_STRINGr)rrrrrets r0create_or_update_statement_params_with_query_tagrs? ! !15E!E!  bC6{QGC Jr)return_full_stage_namercpt|}|jds|d}|jtdrd|ddfSd}t |D]f\}}|dk(r| }|dk(s|r|d|}||dzd}|r|j d|fcSt jt|}|sy |dd } | |fcSy ) Nr0~r1F"rNr/rrNN) rrDrCr enumerate removeprefixrfindallSNOWFLAKE_STAGE_NAME_PATTERN) rr normalized is_quotedicfull_stage_namer\res stage_names rget_stage_partsrs4NCJ   s #"|1%  ~Q/0JqrN""I*%$1 8% I #Xi)!nOa!eg&D%&33C8$>>**9?KC  RJt# #'$* rct|\}}|dk(r t|S|rE|jdr t|St|t|jdzdzSt d|)Nr%rrNzInvalid stage )rrrCr r )rrr\s rget_stage_file_prefix_lengthr s&~6JS4y$$S) I TS!1!1#!677!; ~n%56 77rctdk(S)NXP)r"rrris_in_stored_procedurer s t r object_typec\t|jdtjS)Nr)TEMP_OBJECT_NAME_PREFIXrgenerate_random_alphanumericupper)r s rrandom_name_for_temp_objectrs-% &{'8'8&9;W;Y;_;_;a:b ccrrcDdjdt|DS)Nrc3VK|]!}tjt#ywr)r choice ALPHANUMERIC)rdrs rrfz/generate_random_alphanumeric..sHQ68??<0Hs'))r%range)rs rrrs 77H%-H HHrcbt|tjjryt |S)aA replacement to bool(col_) to check if ``col_`` is None or Empty. ``Column.__bool__` raises an exception to remind users to use &, |, ~ instead of and, or, not for logical operations. The side-effect is the implicit call like ``if col_`` also raises an exception. Our internal code sometimes needs to check an input column is None, "", or []. So this method will help it by writeint ``if column_to_bool(col_): ...`` T)r snowflakesnowparkColumnbool)col_s rcolumn_to_boolrs'$ **112 :r result_metar.cddlm}|syg}g}|D]j}|j|j|r5t|j dk(r|j |jdZ|jdl||fS)a Takes a list of result metadata objects and returns a list containing the names of all fields as well as a list of functions that wrap specific columns. A column type may need to be wrapped if the connector is unable to provide the columns data in an expected format. For example StructType columns are returned as dict objects, but are better represented as Row objects. r)%_should_use_structured_type_semanticsrOBJECTNctdi|S)Nrr')xs rz$_parse_result_meta..$s chAhr)snowflake.snowpark.contextr!appendrr type_codefields)rr! col_nameswrapperscols r_parse_result_metar- sQ IH "" 1 3 /8; & OO. / OOD ! " h r result_setcase_sensitivecdt|xsg\}}g}t}|r9tjj|j |j }|D]O}|r(t ||D cgc]\}} |r|| n| }}} | td||} |j| Q|Scc} }wNz-Result returned from Python connector is None) r-r(_builderbuildset_case_sensitiveto_rowzipr r') r.rr/r*r+rows row_structrwraprrows rresult_set_to_rowsr;*s -[->B?Ix DJ LL   * = =n M T T V  :=h:MNwtQtDG*NDN <LM M$ C K Os,B,c#DKt|\}}t}|r9tjj|j |j }|D]B}| t d|r(t||Dcgc]\}}|r||n|}}}||} | Dycc}}wwr1)r-r(r2r3r4r5r r6) r.rr/r*r+r8rr9rr:s rresult_set_to_iterr=As -[9IxJ LL   * = =n M T T V  <LM M :=h:MNwtQtDG*NDN$ OsA3B 5B B c"eZdZdZfdZxZS)PythonObjJSONEncoderzO>OP Q??$ $ u{{ +<<> !7?5) )r)rrr__doc__rL __classcell__rNs@rr?r?UsF * *rr?c,eZdZdeddfdZdeddfdZy) WarningHelper warning_timesrNc ||_d|_yNr)rTr )rMrTs r__init__zWarningHelper.__init__fs* rtextc|j|jkrtj||xjdz c_yr)r rTrsrt)rMrXs rrtzWarningHelper.warningjs- ::** * OOD ! a r)rrrrrWr'rtrrrrSrSes(cdCDrrS warning_dictrXrTch|tvrt|t|<t|j|yr)rZrSrt)rrXrTs rrtrtss, <*=9 Tt$rc(eZdZdZdZdZdZdZy) DummyRLockzbThis is a dummy lock that is used in place of threading.Rlock when multithreading is disabled.cyrrrMs r __enter__zDummyRLock.__enter__~ rcyrr)rMexc_typeexc_valexc_tbs r__exit__zDummyRLock.__exit__rarcyrrrMargskwargss racquirezDummyRLock.acquirerarcyrrrhs rreleasezDummyRLock.releaserarN)rrrrOr`rfrkrmrrrr]r]zs    rr]ceZdZdZy)DummyThreadLocalzpThis is a dummy thread local class that is used in place of threading.local when multithreading is disabled.N)rrrrOrrrroros # rrothread_safe_session_enabledcB|rtjStSr)rqlocalrorps rcreate_thread_localrts#   rcB|rtjStSr)rqRLockr]rss r create_rlockrws#  <rceZdZdZdZdZdZy)AstModezp Describes the ast modes that instruct the client to send sql and/or dataframe AST to snowflake server. rrNrN)rrrrOSQL_ONLY SQL_AND_ASTAST_ONLYrrrryrysHKHrrycNeZdZdZeZ eZ eZ eZy) AstFlagSourcez Describes the source of the AST feature flag value. This is not just an annotation! The enum value determines the precedence of the value. N) rrrrOrLOCALSERVERUSERTESTrrrr~r~s3 FEu VF# 6DI 6Drr~c^eZdZdZeZ eZ eZ eZ eZ y) _AstFlagStatez< Describes the state of the AST feature flag value. N) rrrrOrNEW TENTATIVE SERVER_SETUSER_SET FINALIZEDrrrrrs; &CYInJ*vH(I=rrcBeZdZdZd dZedefdZdededdfdZ y) _AstStatea Tracks the state of the ast_enabled feature flag. This class is thread-safe. The most important role of this class is to prevent the flag from flip-flopping. In particular, once the feature is disabled (for any reason), nothing can re-enable it. rNcntj|_d|_tj |_y)z!Creates an instance of _AstState.TN)rqLock_mutex _ast_enabledrr_stater_s rrWz_AstState.__init__s'nn& !#'' rc|j5|jtjk(r5tj d|j tj|_|j cdddS#1swYyxYw)/Gets the value of the ast_enabled feature flag.zFAST state has not been set explicitly. Defaulting to ast_enabled = %s.N)rrrrrsinforrr_s renabledz_AstState.enabledsd[[ %{{m/// \%%,55 $$ % % %s AA55A>sourceenablec  |j5tjd|j|j|||t j k(r&tj|_||_ dddy|jtjk(r:|j|k7r+tjd|j| dddy|t jk(r&||_tj|_ dddy|jtjk(xr|j xr| }|t jk(r5|r||_ntjdtj|_ns|t jk(r5|r||_ntjdtj|_n+t!d|jd|jd|d |dddy#1swYyxYw) a Sets the value of the ast_enabled feature flag. The method may ignore the change request if the requested transition is unsafe, or if the flag was already set at a precedence level not greater than the precedence level of "source". Flip-flopping the flag (enabled -> disabled -> enabled) is unsafe. The AST feature can be disabled only once, and stays disabled no matter what happens afterward. The feature can be enabled transiently, and once something (server setting or test configuration) makes a final decision, that decision is permanent for the life of the process. Args: source: The source of the request. Using SERVER or TEST will finalize the flag. enable: The new value of the flag. zbSetting AST state. Current state: ast_enabled = %s, state = %s. Request: source = %s, enable = %s.Nz`Cannot change AST state after it has been finalized. Frozen ast_enabled = %s. Ignoring value %s.zQServer cannot enable AST after treating it as disabled locally. Ignoring request.zVCannot enable AST by local preference after treating it as disabled. Ignoring request.z3Unhandled transition. Current state: ast_enabled = z , state = z. Request: source = z , enable = )rrsdebugrrr~rrrrtrrrrrrNotImplementedError)rMrrsafe_transitions r set_statez_AstState.set_states [[:  MMt!!   +++,55 $*!: : {{m555$:K:Kv:Uv%% ): : 2+++%+!+44 =: : F }666)))%O ---"(.D%OOk,66 =..."(.D%OOp,55 )I$J[J[I\\fgkgrgrfstHIOHPP[\b[cdq: : : s AG94AG9 0G9C,G99HrN) rrrrOrWpropertyrrr~rrrrrrsE ( % % %J JtJJrr _ast_statec"tjS)r)rrrrris_ast_enabledrHs   rrrc.tj||S)zl Sets the value of the ast_enabled feature flag. See _AstState.set_state for more information. )rr)rrs r set_ast_staterNs    00r CallableT)boundfunccvdjjvtjfd}|S)z=decorator to safeguard public APIs with global feature flags. _emit_astcZs|i|Sd|vr|i|St|d<|i|S)Nr)r)rirjr has_emit_asts r call_wrapperzpublicapi..call_wrapperlsO(( ( & (( (,.{T$V$$r)__code__ co_varnames functoolsr)rrrs` @r publicapirfs<% (A(AAL__T%%" rdecorator_type) deprecated experimentalin private previewversionextra_warning_textextra_doc_stringcfd}|S)Ncjddddvrdnddddd}jxsdd d |d _tjfd }|S) Nz() is  since . rrDo not use it in production. rzThis function or method is z z z  c@tj|i|Sr)rtr)rirjr warning_texts rfunc_call_wrapperz:func_decorator..wrapper..func_call_wrappers# D%%| 4(( (r)rrOrr)rdoc_string_textrrrrrrs` @rwrapperzfunc_decorator..wrappers  !'7wwir2@Dj2j.prs!" $  87GwwiWYZjYkkpq,,,"-T%8IL   )  )! rr)rrrrrs```` rfunc_decoratorrs! Nrcfd}|S)Nc djddddvrdndtjfd}|S) Nz Parameter z is rrrrrc@tj|i|Sr)rtr)rirjparam_setter_functionrs rrz;param_decorator..wrapper..func_call_wrappers$ )22L A($9&9 9r)rrr)rrrrrs` @rrz param_decorator..wrappersg.778^.sm 3$sE*0CA 0"3q63/0#3q63/  sA&A(za import can only be a file path (str) or a tuple of the file path (str) and the import path (str))rrall TypeError)rrs rcheck_imports_typersN  w % #  fu v    r output_schema StructTypePandasDataFrameTypecddlm}trddlm}nt}t ||s>rc"t|tS)ztMethod that extracts options for COPY INTO LOCATION command into file format type options and copy options. )rCOPY_INTO_LOCATION_COPY_OPTIONSrs rget_copy_into_location_optionsr*s !@ AArkey alias_mapc|jj}|j||}||k7rtj d|d|d|S)zMethod that takes a key and an option alias map as arguments and returns the aliased key if the key is present in the alias map. Also raise a warning if alias key is applied. zOption 'z' is aliased to 'z`'. You may see unexpected behavior. Please refer to format specific options for more information)r rrrsrt)rr upper_key aliased_keys rget_aliased_option_namer3s^ !!#I-- 95Kise,[M:L L r table_namec|rt|dkr|S|jdd}|d|dcxk(rdk(rnn|ddS|S)z this function is used by method _table_exists to handle double quotes in table name when calling SHOW TABLES LIKE rz""rrrrN)rrP)rs r3strip_double_quotes_in_like_statement_in_table_namerFsT Z1, ##D#.J *!} 2E#E:a U:Urc t|t|}g}d}d}d}||krV||}|dk(r!|r||dz kr||dzdk(r|dz }n&d}n#d}n |dk(r|s|j||||dz}|dz }||krV|j||||S)u{ This function implements the algorithm to parse a table name. We parse the table name according to the following rules: https://docs.snowflake.com/en/sql-reference/identifiers-syntax - Unquoted object identifiers: - Start with a letter (A-Z, a-z) or an underscore (“_”). - Contain only letters, underscores, decimal digits (0-9), and dollar signs (“$”). - Are stored and resolved as uppercase characters (e.g. id is stored and resolved as ID). - If you put double quotes around an identifier (e.g. “My identifier with blanks and punctuation.”), the following rules apply: - The case of the identifier is preserved when storing and resolving the identifier (e.g. "id" is stored and resolved as id). - The identifier can contain and start with ASCII, extended ASCII, and non-ASCII characters. FrrrNTr$)rrr')rstr_lenrin_double_quotesrcur_word_start_idxcur_chars rparse_table_namerWs$$*oG C A g+a= s?w{?z!a%'8C'?FA(-$$( _# :&8;<%&U" Q7 g+:JJz,Q/0 Jrrz^(".+")$z^([_A-Za-z]+[_A-Za-z0-9$]*)$ keep_casectj|r t|Stj|r)|s'tt |j ztzStt |ztzSr)ALREADY_QUOTEDrvalidate_quoted_nameUNQUOTED_CASE_INSENSITIVE DOUBLE_QUOTE escape_quotesr)rrs r quote_namers[D!#D)) " ( ( .ymDJJL99LHHmD11L@@rct|ddjttztvrtj||S)NrNr)r rP EMPTY_STRINGr& PLAN_ANALYZER_INVALID_IDENTIFIERrs rr r s8tAbz)),*E|TT-NNtTT r unescapedcD|jtttzSr)rPr )rs rr r s   \<,+F GGrrcNtjdj|}|S)a Splits the Snowflake identifier by dots that are not within double-quoted parts. Tokens that appear quoted in the input remain unchanged (quotes are kept). See details in https://docs.snowflake.com/en/sql-reference/identifiers-syntax. Examples: 'foo.bar."hello.world".baz' -> ['foo', 'bar', '"hello.world"', 'baz'] '"a.b".c."d.e.f".g' -> ['"a.b"', 'c', '"d.e.f"', 'g'] z"(?:[^"]|"")*"|[^.]+)rcompiler)rpartss r#split_snowflake_identifier_with_dotrs# JJ. / 7 7 :E Lrzj[\u1100-\u115F\u2E80-\uA4CF\uAC00-\uD7A3\uF900-\uFAFF\uFE10-\uFE19\uFE30-\uFE6F\uFF00-\uFF60\uFFE0-\uFFE6]c`|yttj|}t||zS)z Calculate the half-width of a string by adding 1 for each character and adding an extra 1 for each full-width character. :param s: The input string :return: The calculated width r)rfull_width_regexr)rfull_width_counts rstring_half_widthrs3 y+33A67 q6$ $$rdfzsnowflake.snowpark.DataFramedf_name pivot_colz4snowflake.snowpark._internal.type_utils.ColumnOrNamevaluesz3snowflake.snowpark._internal.type_utils.LiteralTypedefault_on_nullcddlm}| |s td|j|d|}ddlm}m}ddlm} t|tr.|D cgc]"} t| | r | jn|| $} } nYt||r||j} nd} t|jjdgdkDr|j!}| t|| r |jn||}||| |fScc} w) a Prepare dataframe pivot arguments to use in the underlying pivot call. This includes issuing any applicable warnings, ensuring column types and valid arguments. Returns: DateFrame, pivot column, pivot_values and default_on_null value. rrNzvalues cannot be emptyz())rScalarSubqueryr post_actions)snowflake.snowpark.dataframerr _convert_cols_to_exprs0snowflake.snowpark._internal.analyzer.expressionrr"snowflake.snowpark.columnrrr _expression_planrqueriesr cache_result) rrrrr rpcrr"rr pivot_valuess rprepare_pivot_argumentsr/s$7 &122 " "gYb>9 =BX0&(#LR GHZ62AMM B   fi ()&,,7LL rzz~~nb1 2Q 6"B"/62  ' ')  r< 00' s 'C8rc^t|tr|jdvr tdy)N)r"ARRAYBOTHz/mode must be one of ('OBJECT', 'ARRAY', 'BOTH'))rr'rr )rs rcheck_flatten_moder3 s, dC DJJL8S$SJKK%TrcolscRd}t|dk(r>|d}t|ttfs#t |j t|t|dzdk(s#t |j t|t|dk(xrt|ttfS)z@Helper function to check parameter cols for create_map function.z[The 'create_map' function requires an even number of parameters but the actual number is {}rNrr)rrrrr r)r4 error_messages rcheck_create_map_parameterr7srM 4yA~Aw$ .]11#d)<= = t9q=A --c$i899 t9> =jt}==rrcddlm}t|dk(xr*t|d|tfxrt|dtS)Nrr#rrN)snowflake.snowparkrrrr')rrs ris_valid_tuple_for_aggr:"s8) q6Q; T:adVSM: Tz!A$PS?TTrexprszsnowflake.snowpark.Columnzsnowflake.snowpark.ColumnOrNamecddlm}t|\}}t|r|g}t |dkDrqt |dt r^|djD]G\}}t |trt |tr'tdt|t|fy|D];}t ||rt |ttfr t|r2tdy)zHHelper function to raise exceptions when invalid exprs have been passed.rr#zDictionary passed to DataFrame.agg() or RelationalGroupedDataFrame.agg() should contain only strings: got key-value pair with types zList passed to DataFrame.agg() or RelationalGroupedDataFrame.agg() should contain only Column objects, or pairs of Column object (or column name) and strings.N) r9rrr:rrdictrr'rrrr)r;rrrrrs rcheck_agg_exprsr>(s*5u=HE1e$ 5zA~*U1Xt4!HNN$ DAqq#&:a+=RRVWXRY[_`a[bRbQce  A1f%q4-05KA5Nk  rceZdZdZdZy) MissingModinz8The class is specifically for modin optional dependency.modinN)rrrrO _dep_namerrrr@r@Ks BIrr@cl tjd}|dfS#t$rtdfcYSwxYw)zThis function tries importing the following packages: modin.pandas If available it returns modin package with a flag of whether it was imported. z modin.pandasTF)rrrr@)rAs rimport_or_missing_modin_pandasrDQs= %''7d{ %~u$$%s 33c&eZdZddZdZdefdZy) GlobalCounterrNchtj|_tj|_yr)rqr_lock itertoolsr _counterr_s rrWzGlobalCounter.__init__^s^^% $-OO$5 rcx|j5tj|_dddy#1swYyxYwr)rHrIr rJr_s rresetzGlobalCounter.resetbs, ZZ .%OO-DM . . .s09cp|j5t|jcdddS#1swYyxYwr)rHnextrJr_s rrNzGlobalCounter.nextfs* ZZ ' & ' ' 's,5r)rrrrWrLrrNrrrrFrF]s6.'c'rrFglobal_counterceZdZdZdeej efdeeee fefffd Z deffd Z ddeffd Z fdZ fd Zdeeffd Zd Zdd Zdd ZddZxZS)ExprAliasUpdateDicta A specialized dictionary for mapping expressions (UUID keys) to alias names updates tracking. This is used to resolve ambiguous column names in join operations. This dictionary is designed to store aliases as string values while also tracking whether each alias was inherited from child DataFrame plan. The values are stored as tuples of the form `(alias: str, updated_from_inherited: bool)`, where: - `alias` (str): The alias name for the expression. - `updated_from_inheritance` (bool): A flag indicating whether the expr alias was updated because it's inherited from child plan (True) or not (False). Below is an example for resolving alias mapping: data = [25, 30] columns = ["age"] df1 = session.createDataFrame(data, columns) df2 = session.createDataFrame(data, columns) df3 = df1.join(df2) # in DF3: # df1.age expr_id -> (age_alias_left, False) # comes from df1 due to being disambiguated in the join condition # df2.age expr_id -> (age_alias_right, False) # comes from df2 due to being disambiguated in the join condition df4 = df3.select(df1.age.alias("age")) # in DF4: # df1.age.expr_id -> (age, False) # comes from df3 explict alias # df2.age.expr_id -> (age_alias_right, False) # unchanged, inherited from df3 df5 = df1.join(df4, df1["age"] == df4["age"]) # in the middle of df1.join(df2) operation, we have the following expr_to_alias mapping: # DF4 intermediate expr_to_alias: # df4.age.expr_id -> (age_alias_right2, False) # comes from df4 due to being disambiguated in the join condition, note here df4.age is not the same as df1.age, it's a new attribute # df1.age.expr_id -> (age_alias_right2, True) # comes from df4, updated due to inheritance # DF1 intermediate expr_to_alias: # df1.age.expr_id -> (age_alias_left2, False) # comes from df1 due to being disambiguated in the join condition # when executing merge_multiple_snowflake_plan_expr_to_alias, we drop df1.age.expr_id -> (age_alias_right2, True) # in DF5: # df4.age.expr_id -> (age_alias_right2, False) # df1.age.expr_id -> (age_alias_left2, False) rrct|tr|df}t|tr4t|dk(r&t|dtrt|dts t dt |||y)zIf a string value is provided, it is automatically stored as `(value, False)`. If a tuple `(str, bool)` is provided, it must conform to the expected format. FrrrNz$Value must be a tuple of (str, bool)N)rr'rrrr rK __setitem__rMrrrNs rrSzExprAliasUpdateDict.__setitem__sd eS !ENE ue $E a58S)58T*CD D C'rrc,t||}|dS)zEReturns only the alias string (`str`), omitting the inheritance flag.r)rK __getitem__)rMitemrrNs rrVzExprAliasUpdateDict.__getitem__s#D)Qxrc6t||d}||dS|SrVrKr)rMrrLrrNs rrzExprAliasUpdateDict.gets' C&  8Orc4t||d}||dSy)z8Returns whether a key was inherited (`True` or `False`).NrNFrYrTs rwas_updated_due_to_inheritancez2ExprAliasUpdateDict.was_updated_due_to_inheritances% C&  8Orc.dt|DS)z.sBJCeAhBs)rKrrMrNs rrzExprAliasUpdateDict.itemssB%'-/BBrc.dt|DS)zCReturn only the string parts of the tuple in the dictionary values.c3&K|] }|d ywr^r)rdrs rrfz-ExprAliasUpdateDict.values..s7Ua7s)rKrr_s rrzExprAliasUpdateDict.valuess7egn&677rcht|tsJ|D]}|||j|f||<yr)rrQr[)rMotherrs rrzExprAliasUpdateDict.updatesA%!4555 JAQx!E!Ea!HIDG Jrc"|jS)zTReturn a shallow copy of the dictionary, preserving the (str, bool) tuple structure.__copy__r_s rcopyzExprAliasUpdateDict.copy}}rc<t}|j||S)z+Shallow copy implementation for copy.copy())rQr)rMnew_copys rrfzExprAliasUpdateDict.__copy__s&(rc"|jS)z,Deep copy implementation for copy.deepcopy()re)rMmemos r __deepcopy__z ExprAliasUpdateDict.__deepcopy__rhrr)rrQ)rrrrOruuidUUIDr'rrrSrVrr[rrrrrgrfrmrPrQs@rrQrQns*X(C((16uS$Y7G7L1M($3  C8 8J  rrQsnowflake_plansr)c j|Dcgc]}|j}}t}tj|}i}|D]O}t |Dchc]}||vr|||j |fc}}t |dk(r |d||<K|||<Q|s|S|D] }t} |D]}g} |j#|jD cgc]} | j} } |j||jj |} } | | vs| ret | dk(r2tt| \}}|| k(r|xr| } | j| j| | ft | dk(r| j||<tjd|d|| |Scc}wcc}wcc} w)a Merges expression-to-alias mappings from multiple Snowflake plans, resolving conflicts where possible. The conflict resolution strategy is as follows: 1) If they map to the same alias: * Retain the expression in the final expr_to_alias map. 2) If they map to different aliases: a) If one appears in the output attributes of the plan and the other does not: * Retain the one present in the output attributes and discard the other. This is because I. The one that shows up in the output attribute can be referenced by users to perform dataframe column operations. II. The one that does not show up in the output is an intermediate alias mapping and can not be referenced directly by users. b) If both appear in the output attributes: * Discard both expressions as this constitutes a valid ambiguous case that cannot be resolved. 3) If neither appears in the output attributes: * Discard both expressions since they will no longer be referenced. taking our example from the class docstring, the conflicting df1.age in df5: # df1.age -> (age_alias_right2, True) # comes from df4, updated due to inheritance # df1.age -> (age_alias_left2, False) # comes from df1 due to being disambiguated in the join condition we are going to: DROP: df1.age -> (age_alias_right2, True) because it's not directly in the output and can not be referenced KEEP: df1.age -> (age_alias_left2, False) is going to be kept because it's directly in the output and can be referenced Args: snowflake_plans (List[SnowflakePlan]): List of SnowflakePlan objects. Returns: Dict[Any, str]: Merged expression-to-alias mapping. rNrz Expression 'zz' is associated with multiple aliases across different plans. Unable to determine which alias to use. Conflicting values: ) expr_to_aliasrQrunionrr[r schema_queryoutputrrNiterpopaddrsr)rpplanall_expr_to_alias_dicts merged_dict all_expr_idsconflicted_expr_idsexpr_idrrexpr_id_alias_candidatesoutput_columnsr:tmp_alias_nametmp_updated_due_to_inheritancecandidate_name$candidate_updated_due_to_inheritances r+merge_multiple_snowflake_plan_expr_to_aliasrs(F?NNdt11NN&'K35;; 78L 21 a<7Q==gFG   v;! #)!9K +1  ( 2 &&#&5 # DN  ,8< !D$))!D!D=A=O=O>!!@@I;N^37U+,1GK12HD D"^3 =;:3-002 $ ( (!?@ 3 : ' (A -#;#?#?#AK  MMwi(OObcjOkNln G&P GO ("EsF& !F+ F0c@ttjd|S)zSReturn True if ver contains alphabet, e.g., 1a1; otherwise, return False, e.g., 112z[a-zA-Z])rrsearch)vers rstr_contains_alphabetrDs  *c* ++rcDtd|jdDS)zGenerate a key to sort versions. Note if a version component is not a number, e.g., "1a1", we will treat it as -1. E.g., 1.11.1a1 will be treated as 1.11.-1c3LK|]}t|rdn t|yw)rN)rr)rdnums rrfz-get_sorted_key_for_version..Ks&;>#C(c#h6s"$r$)rr) version_strs rget_sorted_key_for_versionrIs( BMBSBSTWBX r ttl_secondscfd}|S)a A decorator that caches function results with a time-to-live (TTL) expiration. The decorator expects the first argument to be the ttl_key which should be hashable. Args: ttl_seconds (float): Time-to-live in seconds for cached items cigtjdtffd fd}tfd}|_||_|S)N current_timecfr.d\}}||k\rytj|vr|=r-yy)z+Remove expired entries from cache and heap.rN)heapqheappop)r expiry_time cache_keycache expiry_heaps r_cleanup_expiredz6ttl_cache..decorator.._cleanup_expired^sB)4Q& Y,. k*%i( rct5jjdddy#1swYyxYwr)clear)r cache_lockrsr _clear_cachez2ttl_cache..decorator.._clear_cacheis0 $ !!# $ $ $s!.7ct|}tj} 5||vr|cdddS |g|i|}||<| z}tj ||f|cdddS#1swYyxYwr)rrHrheappush) hashable_ttl_keyrirjrrresultrrrrrrrs rrz-ttl_cache..decorator..wrapperns-.I99;L  .% +   .@@@#)i *[8 {[),DE   sA7/A77B)rqrvrr_cache clear_cache)rrrrrrrrs` @@@@r decoratorzttl_cache..decoratorYs] __&  )5 ) $ t    &*rr)rrs` r ttl_cacherPs,\ r sql_queryuuidscddlm}|Dchc]}|j|dc}djfd|j dDScc}w)z7Removes comments associated with child uuids in a queryranalyzer_utilsF with_new_linerc34K|]}|vr |dk7r|yw)rNr)rdlinecomment_placeholderss rrfz"remove_comments..s(  + +  s)%snowflake.snowpark._internal.analyzerr format_uuidr%r)rrrrnrs @rremove_commentsrs^DKPBF""4u"= 99OOD) sAc eZdZUdZeed<dZeeed<dZee ed<dZ eeed<dZ eeed<dZ eeed<e ddeed deedee deeeej fdeeed fdeed edfd Zd efd Zy)TimeTravelConfigz)Configuration for time travel operations.time_travel_modeN statementoffset timestamptimestamp_typestreamatbeforer-rc td||||fD}||dk(rytd|jdvrtd|d|dk7r td d}|Ct|j }t |t j r|j|d }|[t|d r,|jd k7r|jjnd }n|j}|dvrtd|dt||||||S)u Validates and normalizes time travel parameters. timestamp_type handling: - datetime with timezone + timestamp_type NOT provided → auto-sets to 'TZ' - datetime with timezone + timestamp_type explicitly provided → uses provided timestamp_type - datetime without timezone (naive) + timestamp_type NOT provided → no casting, raw string (timestamp_type=None) - datetime without timezone (naive) + timestamp_type explicitly provided → uses provided timestamp_type - string timestamps + timestamp_type NOT provided → no casting, raw string (timestamp_type=None, Snowflake native handling) - string timestamps + timestamp_type explicitly provided → uses TO_TIMESTAMP_XXX casting This behavior preserves timezone information for datetime objects, provides sensible defaults for naive datetime objects, and lets Snowflake handle string timestamp formats natively unless explicit casting is requested. Returns: TimeTravelConfig if time travel is specified, None otherwise. Raises: ValueError: If parameters are invalid. c3$K|]}|du ywrr)rdargs rrfzATimeTravelConfig.validate_and_normalize_params..s$ #CtO$ sNrz^Must specify time travel mode 'at' or 'before' if any other time travel parameter is provided.rzInvalid time travel mode: z. Must be 'at' or 'before'.rNzPExactly one of 'statement', 'offset', 'timestamp', or 'stream' must be provided.TZrrLNTZ)rLTZrz'timestamp_type' value z. must be None or one of 'NTZ', 'LTZ', or 'TZ'.)rrrrrr) sumr rr'r rrFtzinfor2rrr)rrrrrrtime_travel_arg_countnormalized_timestamps rvalidate_and_normalize_paramsz.TimeTravelConfig.validate_and_normalize_paramssl:!$$ (169f'M$ !   #$) t  ! ! #+; ;,-=,>>YZ  !A %b  $  #&y>#7#7#9 )X%6%67##/N4J%)N  %~w/&++y8#((..0 "0!5!5!7%99 -n-==kl -*)   rcd|jjd}|j|d|jdz }|S|j|d|jdz }|S|j|d|jdz }|S|j k|j L|j j}|dk(rd}n|d k(rd }n |d k(rd }nd }|d|d|j dz }|S|d|j dz }|S)z Generates the time travel SQL clause. Args: config: Time travel configuration. Returns: SQL clause like " AT (TIMESTAMP => TO_TIMESTAMP_NTZ('...'))" rz(STATEMENT => 'z')z (OFFSET => r4z (STREAM => 'rTO_TIMESTAMP_NTZrTO_TIMESTAMP_LTZrTO_TIMESTAMP_TZ TO_TIMESTAMPz(TIMESTAMP => z('z'))z(TIMESTAMP => ')rrrrrrr)rMclauser func_names rgenerate_sql_clausez$TimeTravelConfig.generate_sql_clauses;T**002315 >> % '7r: :F( '[[ $  DKK=2 2F$ #[[ $  T[[M4 4F  ^^ '"".!%!4!4!:!:!<!U* 2I#u, 2I#t+ 1I .IN9+R7GsKK ODNN+;2>> r)NNNNNN)rrrrOr'__annotations__rrrrrrr staticmethodrrrFrrrrrrrs3#Ix}# FHSM #Ix}#$(NHSM( FHSM >B#' $=ADH $ S "7>#:;S C=S  S E#x'8'8"89: S !s,?'?!@A S  S  $ %S S jSrrcommented_sql_query child_uuids parent_uuidr*c2ddlm}ddlm}|j d}|Dcic]}|j |d|}}d}g} d} d} d} |D]C} | |vr2| r#| r!| j || |d z | d} d} ,| r/d } |} || } 9| d k7s?|d z }Ed}g}| D]W}||jkr&|j |||jd z ||j ||jd z}Y||kr|j |||d z ||Scc}w) aa Helper function to get line numbers associated with child uuids in a query The commented_sql_query is a sql query with comments associated with child uuids. For example, it may look like: ``` SELECT col1 FROM -- child-uuid-1: table1 -- child-uuid-1: WHERE col1 > 0 -- child-uuid-2: ORDER BY col1 -- child-uuid-2: ``` For this query, we want to return a list of QueryLineInterval objects with the following intervals: - (0, 1, "parent-uuid") - (2, 2, "child-uuid-1") - (3, 3, "parent-uuid") - (4, 4, "child-uuid-2") To do so, we split the commented_sql_query into lines and check for comments associated with child uuids. We find all intervals associated with child uuids and associate the remaining lines with the parent uuid. r)r*rrFrrNrNTr) 4snowflake.snowpark._internal.analyzer.snowflake_planr*rrrrr'startend)rrrr*r sql_linesrnridxchild_intervals child_start found_startcurrent_child_uuidr current_pos new_intervalsintervals rget_line_numbersrsx8WD#))$/I   ""4u"=tC COKK  ' '1&&%k37.replace_placeholders${{1~ '<< %&6%78//34I4N4N4P/Q.RT  '<<:=>O:P%&67!(()9:23CDEEK Krrz \{(\d+)\}rrrz#Number of positional placeholders (z-) does not match number of columns provided (z). Found placeholders: {rz^placeholder_to_column must be a list of Columns or a dict mapping placeholder names to Columns)snowflake.snowpark.functionsrrr=rrrrr r'rrrr%rrr)rrrrnamed_placeholders provided_keysunused_columnsrrewritten_templaterordered_columnspositional_placeholdersnum_placeholders num_columnsrplaceholders_to_addrrs ` @@r"create_prompt_column_from_templateres(4'.!OX!FG16689 &);; `ao`pq   " L L3 L  VVO5H(SDUU406UU(P?PiPP )4 0#%**\8"D ' ( /0 q "%((k@R+S1b2J+S"T "1%8$9:H  ,56F5GH//:m<))-6#>U:V3W)X(YY[] hL!6L)LL l  =V ,Ts  F F plan_node)r)r, line_numberc$ddlm}d}||dfg}|r|j\}}}t||r|j d}|j |j }|j dj}|||}|dk\rn||j} |j| k(r ||_|S|jD]7} | j| k(s|j| |||jz |fnntd|d |rtd|d ) aX Given a parent plan node and a line number, return the plan node that contains the line number. Each parent node has a list of disjoint query line intervals, which are sorted by start line number, and each interval is associated with a plan node uuid. Each node either knows it is responsible for the lines in the interval if its uuid is the same as the interval's uuid, or that one of its descendants is responsible otherwise. If we find that the descendant is responsible, then we subtract the offset created by the parent before recursively searching the child. For example, if the parent is responsible for lines 0-10 and its descendants are responsible for lines 11-20 and we are searching for line 15, we will search the child for line 4. We raise ValueError if the line number does not fall within any interval. rr+cdt|dz }}||krJ||zdz}||j||j}}||cxkr|kr|S||kr|dz }n|dz}||krJy)NrrNrr)rrr) intervalsrleftrightmidrrs rfind_interval_containing_linezAget_plan_from_line_numbers..find_interval_containing_linesY!+eem%. s (Z'rNr rs@@r measure_timer s" )N*J ''~Hs $)NFT)i TNsha256F)r)NNrF) )NT)rN)r)F)T(r contextlibrFrDrrrrrrIloggingrr,rrrr3rHrqrrnrenumrrrrrrr jsonr r r typingrrrrrrrrrrrrrrrrr9rsnowflake.connector.constantsrsnowflake.connector.cursorrr snowflake.connector.descriptionr!r"rr#r$snowflake.connector.versionr%r9*snowflake.snowpark._internal.error_messager&snowflake.snowpark.rowr(snowflake.snowpark.versionr&rr)r*rr,rr-r.r getLoggerrsrSNOWURL_PREFIXRELATIVE_PATH_PREFIXSNOWFLAKE_PATH_PREFIXESrhrSNOWFLAKE_UNQUOTED_ID_PATTERNSNOWFLAKE_QUOTED_ID_PATTERNSNOWFLAKE_ID_PATTERN,SNOWFLAKE_CASE_INSENSITIVE_QUOTED_ID_PATTERN2SNOWFLAKE_CASE_INSENSITIVE_UNQUOTED_SUFFIX_PATTERNrrrGrKrrdigitsascii_lowercaser IGNORECASErYrZPACKAGE_NAME_TO_MODULE_NAME_MAPrMODULE_NAME_TO_PACKAGE_NAME_MAPrINFER_SCHEMA_FORMAT_TYPESrrrXML_ROW_TAG_STRINGXML_ROW_DATA_COLUMN_NAMEr\r%r__file__XML_READER_FILE_PATHXML_READER_API_SIGNATUREXML_READER_SQL_COMMENTXPATH_HANDLER_MAPXPATH_HANDLERS_FILE_PATHrSKIP_LEVELS_TWOSKIP_LEVELS_THREErrSUPPORTED_TABLE_TYPESrrrrrDATETIME_PART_TO_ALIASESrrDATETIME_PARTSrrr r'rrrr!r)r.rr7r:r=r@rErIrLrSrVr[rkrnruryr|rrrrrcontextmanagerrArrrrrrrrrrr r rrrr-r;r=r?rSrZrrtr]rorrrtrvrwryr~rrrrrrrrrrrrrrrrrrrrrrrr DOTALLr r rr r rrrrr/r3r7r:r>r@rDrFrOr=rQrrrrrrrrrrr)rrls000rrBs       ,,&&:FFSDV&BR:*? '  0 1 #:=# !<4%&a(C'DAF0Q,5O2)bjj  }-A,B(K_J``ab3="**03/9C 695 "%%9$:!<+}}v555 '1bjjr}}'# )3 & )% # v#_# V# # . # = #2#G# f#.#x#)#&# U## w!#"z##$(,62,5#<5::<# QAqD#9E #"%ww||BGGOOH$=O889Q8RRUV#$&  " 77<<(ACVW,:   !&*CDD T $! D! :! 5! : !  3 !  5 ! =! 7!@!@! !*6+!,H-!.6/!0I1!2<.3!4o&5!6?-/CD-/CD+-@A%u-)51A!F-2245-335 Qq:;AqD/4467KCE#s(OPsP C C  ISI I %C% % UU U JsJ J S  c 73747W#W$Wcc)& S T 0s0s0/s/s/(S(U38_( 'S'S'ccPCPCP$s$  #'%) < <3-<<# < Y <<~34!C!E$*G>>"mm`" I# 1-1$141* Kx 0 I)6NO     4NO ,022),EH 022),EH sx022),EH d$SVGI d5eCHo!567 8 @C   2 hsm%::   0 2 #s(^ 2.1#h 2 4S>4S> )* 2 ? #s(^? 4S>4S> )*?B #s(^B 4S>4S> )*B CH~ &VCVCV"88c8v  J 2&BJJ'EFASATAcAssHSHSH34$2::  % % %01&01 01F01  J K * ,   01ST01fLSLTL >c>d>"UeD%K0UTU  # /45 S#X   F, %.>.D(E % ' '!. /j$jZf/*ffR, 757t s 49  zDHHcHH  H` X X   S- -.5P0QQX  X ! X v>U23>U>U>UB hr5y)sE *)*x#ds;f=% g g=gg