Ug')dZddlZddlZddlZddlZddlZddlZddlZejZ Gdde Z Gdde Z Gdde Z Gd d e Zdd ZdS)zb Fast cryptographic hash of Python objects, with a special case for fast hashing of numpy arrays. NceZdZdZdZdS)_ConsistentSetza Class used to ensure the hash of Sets is preserved whatever the order of its items. c t||_dS#ttjf$r"td|D|_YdSwxYw)Nc34K|]}t|VdSNhash).0es M/var/www/surfInsights/venv3-11/lib/python3.11/site-packages/joblib/hashing.py z*_ConsistentSet.__init__..%s($C$CT!WW$C$C$C$C$C$C)sorted _sequence TypeErrordecimalInvalidOperation)self set_sequences r __init__z_ConsistentSet.__init__sj E $L11DNNN734 E E E$$C$Cl$C$C$CDDDNNNN Es4AAN__name__ __module__ __qualname____doc__rrr rrs2 E E E E ErrceZdZdZdZdS)_MyHashz7 Class used to hash objects that won't normally pickle c||_dSr)args)rr s r rz_MyHash.__init__+s  rNrrrr rr(s)AArrc(eZdZdZd dZd dZdZdZdej fd Z e j Z e e ee<e e ee<e e ee <e e eej<d Zd Zee ee<dS)HasherzW A subclass of pickler, to do cryptographic hashing, rather than pickling. md5ctj|_d}t||j|t j||_dS)N)protocol)ioBytesIOstreamPicklerrhashlibnew_hash)r hash_namer&s r rzHasher.__init__4sHjll t{X>>>[++ rTc. ||n/#tj$r}|xjd|d|fz c_d}~wwxYw|j}|j||r|jSdS)NzPicklingError while hashing z: ) dumppickle PicklingErrorr r)getvaluer-update hexdigest)robj return_digestr dumpss r r z Hasher.hash=s  IIcNNNN#    FFFsssAAFH HFF   $$&& %    *:'')) ) * *sA?Act|tjtijfrt |dr |jj}n|j}|j}t|tturt||j}n0|t||}n|jj }t|||}t ||dS)N__func__) isinstancetypes MethodTypetypepophasattrr:r__self__r1r __class__r*save)rr6 func_nameinstclss r rCz Hasher.saveHs cE,d26ll; < < 4sJ'' )L1 L K|]\}}t||fVdSrr)r kvs r r z)Hasher._batch_setitems..sL6I6I:>!Q8 > > > > K K K  # #D$v6I6IBG6I6I6I0I0I+J+J K K K K K K Ks59A BBcVt|t|dSr)r*rCr)r set_itemss r save_setzHasher.save_sets$ T>)4455555r)r#)T)rrrrrr rCrJstructrMrPr*dispatchcopyr>lenobjectr1r0r]rbsetrrr r"r"/s,,,, * * * *   &###%)v{////*$$&&H%HTT#YY(HTT&\\)HTT']]"-HTT&+   K K K666%HTT##%%[[rr"c eZdZdZddZdZdS) NumpyHasherz7 Special case the hasher for when numpy is loaded. r#Fc||_t||ddl}||_t |dr|j|_dSt|_dS)a Parameters ---------- hash_name: string The hash algorithm to be used coerce_mmap: boolean Make no difference between np.memmap and np.ndarray objects. r.rN getbuffer) coerce_mmapr"rnumpynpr@rm _getbuffer memoryview)rr.rnrps r rzNumpyHasher.__init__s_' 222 2{ # # ) lDOOO(DOOOrcNt||jjr|jjs|jdkr|}n7|jjr|}n(|jj r|j }n|}|j | ||jj|jr't||jjr |jj}n|j}|d|j|j|jff}nut||jjr[|j dd|j t+j|dSt.||dS)z Subclass the save method, to hash ndarray subclass, rather than pickling them. Off course, this is a total abuse of the Pickler class. rHASHED _HASHED_DTYPEzutf-8N)r;rpndarraydtype hasobjectshapeflattenflags c_contiguous f_contiguousTr-r4rqviewuint8rnmemmaprBstridesencoder1r8r"rC)rr6obj_c_contiguousklasss r rCzNumpyHasher.saves c47? + +9 CI4G9 yB$';;==  ' 1#&  ' 1#&5  $';;== J   0 5 5dgm D DEE G G G  &JsDGN$C$C &  8SY 3;GHCC TW] + +  J  o44W== > > > J  fl3// 0 0 0 F D#rNr#F)rrrrrrCrrr rjrjsA))))(?????rrjr#Fcd}||vr#td||dtjvrt ||}nt |}||S)aj Quick calculation of a hash to identify uniquely Python objects containing numpy arrays. Parameters ---------- hash_name: 'md5' or 'sha1' Hashing algorithm used. sha1 is supposedly safer, but md5 is faster. coerce_mmap: boolean Make no difference between np.memmap and np.ndarray )r#sha1zAValid options for 'hash_name' are {}. Got hash_name={!r} instead.ro)r.rnrl) ValueErrorformatrRrSrjr"r )r6r.rnvalid_hash_nameshashers r r r s'(((7 &!19==?? ?#+ykJJJ),,, ;;s  rr)rr1r+rRr<rcr'r_Picklerr*rgrrr"rjr rrr rs9   /EEEEEVEEE$fh%h%h%h%h%Wh%h%h%VWWWWW&WWWtr