a +[#@sdZddlZddlZddlZddlZddlZddlZddlmZddl Z ej ddkZ e rbej Z nej Z GdddeZGdd d eZGd d d e ZGd d d eZdddZdS)zb Fast cryptographic hash of Python objects, with a special case for fast hashing of numpy arrays. N)_bytes_or_unicode3c@seZdZdZddZdS)_ConsistentSetza Class used to ensure the hash of Sets is preserved whatever the order of its items. cCst||_dSN)sortedZ _sequence)selfZ set_sequencer R/home/psgendb/BIRCHDEV/pkg/quast-5.2.0/quast_libs/site_packages/joblib3/hashing.py__init__ sz_ConsistentSet.__init__N__name__ __module__ __qualname____doc__r r r r r rsrc@seZdZdZddZdS)_MyHashz7 Class used to hash objects that won't normally pickle cGs ||_dSr)args)rrr r r r 'sz_MyHash.__init__Nr r r r r r$src@seZdZdZdddZdddZdd Zd d Zd ej fd dZ e j Z e e ee<e e ee<e e ee <e e eej<ddZddZee ee<d S)HasherzW A subclass of pickler, to do cryptographic hashing, rather than pickling. md5cCs<t|_trtjntj}tj||j|dt ||_ dS)N)protocol) ioBytesIOstreamPY3pickleDEFAULT_PROTOCOLHIGHEST_PROTOCOLPicklerr hashlibnew_hash)r hash_namerr r r r 0s   zHasher.__init__Tc Cspz||Wn8tjyF}ztd||fWYd}~n d}~00|j}|j||rl|j SdS)Nz"PicklingError while hashing %r: %r) dumpr PicklingErrorwarningswarnrgetvaluer update hexdigest)robjZ return_digestedumpsr r r hash:s(  z Hasher.hashcCst|tjtijfr|t|dr*|jj}n|j}|j}t|tt krTt ||j}n(|durht ||}n|jj }t |||}t ||dS)N__func__) isinstancetypes MethodTypetypepophasattrr-r __self__rr __class__rsave)rr) func_nameinstclsr r r r6Ds    z Hasher.savecCst|trdSt||dSr)r.rrmemoize)rr)r r r r:Ws zHasher.memoizeNcCst||d}tjdkr|d=ztj||fi|Wnntjytj||fi|t|dd}|dkr|}|dur~|j}tj |}t ||st |||Yn0dS)N)namepack)r<r__main__) dictsys version_infor save_globalrr#getattrr modulesr3setattr)rr)r;r<kwargsmoduleZmy_namemodr r r rCbs     zHasher.save_globalcCst|tt|dSr)r_batch_setitemsiterr)ritemsr r r rJszHasher._batch_setitemscCst|t|dSr)rr6r)rZ set_itemsr r r save_setszHasher.save_set)r)T)r rrrr r,r6r:structr<rCrdispatchcopyr1lenobjectrr"rJrMsetr r r r r+s      rc@s"eZdZdZd ddZddZdS) NumpyHasherz7 Special case the hasher for when numpy is loaded. rFcCs@||_tj||dddl}||_t|dr6|j|_nt|_dS)a Parameters ---------- hash_name: string The hash algorithm to be used coerce_mmap: boolean Make no difference between np.memmap and np.ndarray objects. r!rN getbuffer) coerce_mmaprr numpynpr3rV _getbuffer memoryview)rr!rWrYr r r r s   zNumpyHasher.__init__c Cst||jjr|jjsz$||jj}|j| |Wn:t t fyt| |jj}|j| |Yn0|j rt||jjr|jj}n|j}|d|j|j|jff}n"t||jjr|j}|d|jff}t||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. ZHASHEDN)r.rYndarraydtype hasobjectviewuint8r r'rZ ValueError BufferErrorflattenrWmemmapr5shapestridesdescrrr6)rr)Zobj_bytes_viewklassr r r r6s  zNumpyHasher.saveN)rF)r rrrr r6r r r r rTs rTrFcCs,dtjvrt||d}n t|d}||S)al 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 rX)r!rWrU)rArErTrr,)r)r!rWZhasherr r r r,s  r,)rF)rr$rrrAr/rN_compatrrversionr_PicklerrrRrrrrTr,r r r r s"  bQ