U Nv f')@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@seZdZdZddZdS)_ConsistentSetza Class used to ensure the hash of Sets is preserved whatever the order of its items. c CsBzt||_Wn.ttjfk r<tdd|D|_YnXdS)Ncss|]}t|VqdSNhash).0er2/tmp/pip-unpacked-wheel-dylwa62s/joblib/hashing.py %sz*_ConsistentSet.__init__..)sortedZ _sequence TypeErrordecimalInvalidOperation)selfZ set_sequencerrr __init__sz_ConsistentSet.__init__N__name__ __module__ __qualname____doc__rrrrr rsrc@seZdZdZddZdS)_MyHashz7 Class used to hash objects that won't normally pickle cGs ||_dSr)args)rrrrr r+sz_MyHash.__init__Nrrrrr r(src@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_namerrrr r4s zHasher.__init__Tc Csvz||Wn>tjk rL}z|jd||ff7_W5d}~XYnX|j}|j||rr|jSdS)Nz"PicklingError while hashing %r: %r) dumppickle PicklingErrorrrgetvaluer"update hexdigest)robjZ return_digestrdumpsrrr r=s  z Hasher.hashcCst|tjtijfr|t|dr*|jj}n|j}|j}t|tt krTt ||j}n(|dkrht ||}n|jj }t |||}t ||dS)N__func__) isinstancetypes MethodTypetypepophasattrr,r__self__r%r __class__rsave)rr* func_nameinstclsrrr r5Hs    z Hasher.savecCs"t|ttfrdSt||dSr)r-bytesstrrmemoize)rr*rrr r;[szHasher.memoizeNcCst||d}|d=ztj||f|Wnltjk rtj||f|t|dd}|dkr|}|dkrn|j}tj|}t ||st |||YnXdS)N)namepackr=r__main__) dictr save_globalr%r&getattrrsysmodulesr2setattr)rr*r<r=kwargsmoduleZmy_namemodrrr r@fs    zHasher.save_globalc CsPzt|tt|Wn2tk rJt|ttdd|DYnXdS)Ncss|]\}}t||fVqdSrr)rkvrrr r sz)Hasher._batch_setitems..)r_batch_setitemsiterr r )ritemsrrr rJs zHasher._batch_setitemscCst|t|dSr)rr5r)rZ set_itemsrrr save_setszHasher.save_set)r)T)rrrrrrr5r;structr=r@rdispatchcopyr0lenobjectr%r$rJrMsetrrrr r/s      rc@s"eZdZdZd ddZddZdS) NumpyHasherz7 Special case the hasher for when numpy is loaded. rFcCs@||_tj||dddl}||_t|dr6|j|_nt|_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_mmaprrnumpynpr2rV _getbuffer memoryview)rr#rWrYrrr rs   zNumpyHasher.__init__cCst||jjr|jjs|jdkr*|}n&|jjr8|}n|jj rH|j }n|}|j | ||jj|jrt||jjr|jj}n|j}|d|j|j|jff}n6t||jjr|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. rZHASHEDZ _HASHED_DTYPEzutf-8N)r-rYZndarrayZdtypeZ hasobjectshapeflattenflags c_contiguous f_contiguousTr"r(rZviewZuint8rWZmemmapr4stridesencoder%r+rr5)rr*Zobj_c_contiguousklassrrr r5s(   zNumpyHasher.saveN)rF)rrrrrr5rrrr rTs rTrFcCsHd}||krtd||dtjkr4t||d}n t|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.rX)r#rWrU) ValueErrorformatrBrCrTrr)r*r#rWZvalid_hash_namesZhasherrrr rs   r)rF)rr%r rBr.rNrr _PicklerrrRrrrrTrrrrr s kZ