sKg')dZddlZddlZddlZddlZddlZddlZddlZejZ Gdde Z Gdde Z Gdde Z Gd d e Zd d Zy) zb Fast cryptographic hash of Python objects, with a special case for fast hashing of numpy arrays. NceZdZdZdZy)_ConsistentSetza Class used to ensure the hash of Sets is preserved whatever the order of its items. c t||_y#ttjf$rtd|D|_YywxYw)Nc32K|]}t|ywNhash).0es R/home/alanp/www/video.onchill/myenv/lib/python3.12/site-packages/joblib/hashing.py z*_ConsistentSet.__init__..%s$ClT!Wls)sorted _sequence TypeErrordecimalInvalidOperation)self set_sequences r __init__z_ConsistentSet.__init__sF E $L1DN7334 E$$Cl$CDDN Es0AAN__name__ __module__ __qualname____doc__rr rrs  ErrceZdZdZdZy)_MyHashz7 Class used to hash objects that won't normally pickle c||_yr)args)rr s r rz_MyHash.__init__+s  rNrrrr rr(s ArrceZdZdZd dZd dZdZdZdejfdZ e jjZ e e ee<e e ee<e e ee <e e eej$<dZd Zee ee<y) HasherzW A subclass of pickler, to do cryptographic hashing, rather than pickling. ctj|_d}tj ||j|t j ||_y)N)protocol)ioBytesIOstreamPicklerrhashlibnew_hash)r hash_namer%s r rzHasher.__init__4s?jjl t{{X>[[+ rc: |j||jj }|j j||r|j jSy#tj$r"}|xjd|d|fz c_d}~wwxYw)NzPicklingError while hashing z: ) dumppickle PicklingErrorr r(getvaluer,update hexdigest)robj return_digestr dumpss r r z Hasher.hash=s  IIcN $$& % ::'') )  ##  FFsAFH HF  sA%%B8BBct|tjtijfrt |dr|j j}n |j}|j}t|tturt||j}n2| t||}n#|jj}t|||}tj||y)N__func__) isinstancetypes MethodTypetypepophasattrr9r__self__r0r __class__r)save)rr5 func_nameinstclss r rBz Hasher.saveHs cE,,d266l; <sJ'LL11 LL <.s%6IBG$!Q8 K  # #D$v6IBG6I0I+J K Ks(+8A&%A&cBtj|t|yr)r)rBr)r set_itemss r save_setzHasher.save_sets T>)45r)md5)T)rrrrrr rBrIstructrLrOr)dispatchcopyr=lenobjectr0r/r\rasetrrr r"r"/s, * &#%)v{{/*$$&H%HT#Y(HT&\)HT']"-HT&++  K6%HT#%[rr"ceZdZdZddZdZy) NumpyHasherz7 Special case the hasher for when numpy is loaded. c||_tj||ddl}||_t |dr|j |_yt|_y)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__sB' 2 2{ # llDO(DOrct||jjrF|jjs/|j dk(r|j }nL|jjr|}n3|jjr |j}n|j }|jj|j|j|jj|j r7t||jj"r|jj}n |j$}|d|j|j |j&ff}nyt||jjrY|jjdj)d|jjt+j,|yt.j1||y)z Subclass the save method, to hash ndarray subclass, rather than pickling them. Off course, this is a total abuse of the Pickler class. rHASHED _HASHED_DTYPEzutf-8N)r:rpndarraydtype hasobjectshapeflattenflags c_contiguous f_contiguousTr,r3rqviewuint8rnmemmaprAstridesencoder0r7r"rB)rr5obj_c_contiguousklasss r rBzNumpyHasher.saves\ c477?? +CII4G4GyyB$';;= ''#& ''#&55 $';;= JJ   0 5 5dggmm DE G JsDGGNN$C  8SYY 3;;GHC TWW]] + JJ  o44W= > JJ  fll3/ 0  D#rNrbF)rrrrrrBrrr rjrjs)(?rrjcd}||vrtdj||dtjvrt ||}n t |}|j |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 )rbsha1zAValid options for 'hash_name' are {}. Got hash_name={!r} instead.ro)r-rnrl) ValueErrorformatrQrRrjr"r )r5r-rnvalid_hash_nameshashers r r r se'((7 &!19=? ?#++ykJ), ;;s rr)rr0r*rQr;rcr&r_Picklerr)rgrrr"rjr rrr rsi  //EVE$fh%Wh%VW&Wtr