o XRh')@sdZddlZddlZddlZddlZddlZddlZddlZejZ Gddde Z Gddde Z Gddde Z Gd d d e Zdd dZdS)zb Fast cryptographic hash of Python objects, with a special case for fast hashing of numpy arrays. Nc@eZdZdZddZdS)_ConsistentSetza Class used to ensure the hash of Sets is preserved whatever the order of its items. c Cs@zt||_WdSttjfytdd|D|_YdSw)Ncss|]}t|VqdSNhash).0er P/home/air/sanwanet/backup_V2/venv/lib/python3.10/site-packages/joblib/hashing.py %sz*_ConsistentSet.__init__..)sorted _sequence TypeErrordecimalInvalidOperation)self set_sequencer r r __init__s z_ConsistentSet.__init__N__name__ __module__ __qualname____doc__rr r r r rs rc@r)_MyHashz7 Class used to hash objects that won't normally pickle cGs ||_dSr)args)rrr r r r+s z_MyHash.__init__Nrr r r r r(s rc@seZdZdZdddZdddZdd Zd d Zd ej fd dZ e j Z e e ee<e e ee<e e ee <e e eej<ddZddZee ee<d S)HasherzW A subclass of pickler, to do cryptographic hashing, rather than pickling. md5cCs0t|_d}tj||j|dt||_dS)N)protocol)ioBytesIOstreamPicklerrhashlibnew_hash)r hash_namerr r r r4s zHasher.__init__Tc Cslz||Wntjy!}z |jd||ff7_d}~ww|j}|j||r4|jSdS)Nz"PicklingError while hashing %r: %r) dumppickle PicklingErrorrr!getvaluer%update hexdigest)robj return_digestrdumpsr r r r=s   z Hasher.hashcCst|tjtijfr>t|dr|jj}n|j}|j}t|tt ur*t ||j}n|dur4t ||}n |jj }t |||}t ||dS)N__func__) isinstancetypes MethodTypetypepophasattrr0r__self__r(r __class__r"save)rr- func_nameinstclsr r r r9Hs    z Hasher.savecCs"t|ttfr dSt||dSr)r1bytesstrr"memoize)rr-r r r r?[szHasher.memoizeNcCst||d}|d=z tj||fi|WdStjyTtj||fi|t|dd}|dkrN|}|dur;|j}tj|}t ||sQt |||YdSYdSYdSw)N)namepackrAr__main__) dictr" save_globalr(r)getattrrsysmodulesr6setattr)rr-r@rAkwargsmodulemy_namemodr r r rDfs"    zHasher.save_globalc CsNz t|tt|WdSty&t|ttdd|DYdSw)Ncss |] \}}t||fVqdSrr)rkvr r r r sz)Hasher._batch_setitems..)r"_batch_setitemsiterr r)ritemsr r r rOs zHasher._batch_setitemscCst|t|dSr)r"r9r)r set_itemsr r r save_setszHasher.save_set)r)T)rrrrrrr9r?structrArDr"dispatchcopyr4lenobjectr(r'rOrSsetr r r r r/s       rc@s"eZdZdZd ddZddZdS) NumpyHasherz7 Special case the hasher for when numpy is loaded. rFcCsB||_tj||dddl}||_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_mmaprrnumpynpr6r\ _getbuffer memoryview)rr&r]r_r r r rs    zNumpyHasher.__init__cCst||jjrT|jjsT|jdkr|}n|jjr|}n |jj r$|j }n|}|j | ||jj|jrEt||jjrE|jj}n|j}|d|j|j|jff}nt||jjro|j dd|j t|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. r HASHED _HASHED_DTYPEzutf-8N)r1r_ndarraydtype hasobjectshapeflattenflags c_contiguous f_contiguousTr%r+r`viewuint8r]memmapr8stridesencoder(r/rr9)rr-obj_c_contiguousklassr r r r9s(   zNumpyHasher.saveNrF)rrrrrr9r r r r rZs  rZrFcCsHd}||vrtd||dtjvrt||d}nt|d}||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 )rsha1zAValid options for 'hash_name' are {}. Got hash_name={!r} instead.r^)r&r]r[) ValueErrorformatrFrGrZrr)r-r&r]valid_hash_nameshasherr r r rs    rrt)rr(r#rFr2rTrr_Picklerr"rXrrrrZrr r r r s kZ