]j)SrSSKrSSKrSSKrSSKrSSKrSSKrSSKr\Rr "SS\ 5r "SS\ 5r "SS\ 5r "S S \ 5rS S jrg) zb Fast cryptographic hash of Python objects, with a special case for fast hashing of numpy arrays. Nc\rSrSrSrSrSrg)_ConsistentSetzTClass used to ensure the hash of Sets is preserved whatever the order of its items. c[U5Ulg![[R4a [SU55Ulgf=f)Nc38# UHn[U5v M g7fNhash).0es K/home/mande/repo/quber/.venv/lib/python3.13/site-packages/joblib/hashing.py *_ConsistentSet.__init__..%s$ClT!WWls)sorted _sequence TypeErrordecimalInvalidOperation)self set_sequences r __init___ConsistentSet.__init__sF E $L1DN7334 E$$Cl$CDDN Es1AA)rN__name__ __module__ __qualname____firstlineno____doc__r__static_attributes__r rrs  Er!rc\rSrSrSrSrSrg)_MyHash(z5Class used to hash objects that won't normally picklecXlgrargs)rr's r r_MyHash.__init__+s r!r&Nrr r!r r#r#(s ?r!r#c&\rSrSrSrS SjrS SjrSrSrS\ R4Sjr \ RR5r \ \ \"\5'\ \ \"\5'\ \ \"\ 5'\ \ \"\R&5'S rS r\\ \"\"55'S rg)Hasher/zA subclass of pickler, to do cryptographic hashing, rather than pickling. This is used to produce a unique hash of the given Python object that is not necessarily cryptographically secure. c[R"5UlSn[R XRUS9 [ R "USS9Ulg)N)protocolF)usedforsecurity)ioBytesIOstreamPicklerrhashlibnew_hash)r hash_namer.s r rHasher.__init__5s?jjl {{X>[[EB r!cJURU5 URR 5nUR RU5 U(aUR R5$g![Ra$nU=RSU<SU<34- sleSnAff=f)NzPicklingError while hashing z: ) dumppickle PicklingErrorr'r2getvaluer6update hexdigest)robj return_digestr dumpss r r Hasher.hash>s  IIcN $$& % ::'') )  ##  FFsAFH HF  sA**B">BB"c[U[R[0R545(a[ US5(aUR RnO URnURn[U5[[5La[X#R5nO1Uc [X#5nO"URRn[X#U5n[RX5 g)N__func__) isinstancetypes MethodTypetypepophasattrrEr__self__r;r# __class__r3save)rr@ func_nameinstclss r rN Hasher.saveIs cE,,d266l; < <sJ''LL11 LL <B+*B+c [R"U[[U55/UQ76 g![a4 [R"U[[SU555/UQ76 gf=f)Nc3@# UHup[U5U4v M g7frr )r kvs r r)Hasher._batch_setitems..s!A54147A,5s)r3_batch_setitemsiterrr)ritemsr's r rlHasher._batch_setitemssc   # #D$ve}*= E E   # #d6!A5!AAB EI  s*-;A+*A+cB[RU[U55 gr)r3rNr)r set_itemss r save_setHasher.save_sets T>)45r!)r6r2)md5)T)rrrrrrr rNrVstructrZr]r3dispatchcopyrIlenobjectr;r:rlrrsetrr r!r r*r*/s C * &#%)v{{/*$$&H%HT#Y(HT&\)HT']"-HT&++  6%HT#%[r!r*c(\rSrSrSrSSjrSrSrg) NumpyHasherz1Special case the hasher for when numpy is loaded.cX l[RXS9 SSKnX0l[ US5(aUR Ulg[Ulg)z Parameters ---------- hash_name: string The hash algorithm to be used coerce_mmap: boolean Make no difference between np.memmap and np.ndarray objects. r7rN getbuffer) coerce_mmapr*rnumpynprKr _getbuffer memoryview)rr7rrs r rNumpyHasher.__init__s?'2 2{ # # llDO(DOr!c2[XRR5(Ga_URR(GdCUR S:XaUR 5nOVURR(aUnO8URR(a URnOUR 5nURRURURURR555 UR (a;[XRR"5(aURRnO UR$nUSURUR UR&44nO~[XRR5(aZURRSR)S55 URR[*R,"U55 g[.R1X5 g)zSubclass the save method, to hash ndarray subclass, rather than pickling them. Off course, this is a total abuse of the Pickler class. r HASHED _HASHED_DTYPEzutf-8N)rFrndarraydtype hasobjectshapeflattenflags c_contiguous f_contiguousTr6r>rviewuint8rmemmaprMstridesencoder;rBr*rN)rr@obj_c_contiguousklasss r rNNumpyHasher.saves\ c77?? + +CII4G4G4GyyB$';;= ''#& ''#&55 $';;= JJ  doo.>.C.CDGGMM.RS T JsGGNN$C$C  8SYY 3;;GHC WW]] + + JJ  o44W= > JJ  fll3/ 0  Dr!)rrrNrtF)rrrrrrrNrr r!r r|r|s;)*>r!r|cSnX;a[SRX155eS[R;a [ XS9nO [ US9nUR U5$)a%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 )rtsha1zAValid options for 'hash_name' are {}. Got hash_name={!r} instead.r)r7rr) ValueErrorformatr_r`r|r*r )r@r7rvalid_hash_nameshashers r r r s_'( O V V    #++yJ), ;;s r!r)rrr4r0r;rur_rG_Picklerr3ryrr#r*r|r r r!r rsg //EVE&fl%Wl%^V&Vrr!