3 QfX#@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||_dS)N)sortedZ _sequence)selfZ set_sequencerU/home/psgendb/BIRCHDEV/pkg/SPAdes-3.15.4/linux-x86_64/share/spades/joblib3/hashing.py__init__ sz_ConsistentSet.__init__N)__name__ __module__ __qualname____doc__r rrrr rsrc@seZdZdZddZdS)_MyHashz7 Class used to hash objects that won't normally pickle cGs ||_dS)N)args)rrrrr r 'sz_MyHash.__init__N)r r r rr rrrr r$src@seZdZdZdddZdddZdd Zd d Zd ej fd dZ e j j Z e e ee<e e ee<e e ee <e e eej<ddZddZee ee<d S)HasherzW A subclass of pickler, to do cryptographic hashing, rather than pickling. md5cCs<tj|_trtjntj}tj||j|dt j ||_ dS)N)protocol) ioBytesIOstreamPY3pickleDEFAULT_PROTOCOLHIGHEST_PROTOCOLPicklerr hashlibnew_hash)r hash_namerrrr r 0s   zHasher.__init__TcCsny|j|Wn6tjk rD}ztjd||fWYdd}~XnX|jj}|jj||rj|jj SdS)Nz"PicklingError while hashing %r: %r) dumpr PicklingErrorwarningswarnrgetvaluerupdate hexdigest)robjZ return_digestedumpsrrr hash:s$  z Hasher.hashcCst|tjtijfr|t|dr*|jj}n|j}|j}t|tt krTt ||j}n(|dkrht ||}n|jj }t |||}t j ||dS)N__func__) isinstancetypes MethodTypetypepophasattrr+r __self__rr __class__rsave)rr' func_nameinstclsrrr r4Ds    z Hasher.savecCst|trdStj||dS)N)r,rrmemoize)rr'rrr r8Ws zHasher.memoizeNc Cst||d}tjdkr|d=ytj||f|Wnltjk rtj||f|t|dd}|dkr|}|dkrx|j}tj |}t ||st |||YnXdS)N)namepackr:r __main__)r;r<) dictsys version_infor save_globalrr!getattrr modulesr1setattr)rr'r9r:kwargsmoduleZmy_namemodrrr rAbs     zHasher.save_globalcCstj|tt|dS)N)r_batch_setitemsiterr)ritemsrrr rHszHasher._batch_setitemscCstj|t|dS)N)rr4r)rZ set_itemsrrr save_setszHasher.save_set)r)T)r r r rr r*r4r8structr:rArdispatchcopyr/lenobjectrr rHrKsetrrrr 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. )rrN getbuffer) coerce_mmaprr numpynpr1rS _getbuffer memoryview)rrrTrVrrr r s   zNumpyHasher.__init__c Cst||jjr|jj ry$|j|jj}|jj|j |Wn<t t fk rx|j j|jj}|jj|j |YnX|j rt||jjr|jj}n|j}|d|j|j|jff}n"t||jjr|j}|d|jff}tj||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,rVZndarrayZdtypeZ hasobjectviewZuint8rr%rW ValueError BufferErrorZflattenrTZmemmapr3shapestridesZdescrrr4)rr'Zobj_bytes_viewklassrrr r4s  zNumpyHasher.saveN)rF)r r r rr r4rrrr rRs rRrFcCs,dtjkrt||d}n t|d}|j|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 rU)rrT)r)r?rCrRrr*)r'rrTZhasherrrr r*s  r*)rF)rr"rrr?r-rL_compatrrversionr_PicklerrrPrrrrRr*rrrr s" bQ