MiNSrSSKrSSKrSSKrSSKJr SSKJr SSK r SSK J r SSK Jr SSKJr S \4S jr\R&S :a SS KJr S rO\rSSKJr SSjrSr"SS\ R<5r"SS5r "SS5r!"SS\5r"g!\a SSKJr Nuf=f!\a+ SSKJr N^!\a \ R6"S5 \rN{f=ff=f)a caching.py ----------- Functions and classes that help with tracking changes in `numpy.ndarray` and clearing cached values based on those changes. You should really `pip install xxhash`: ``` In [23]: %timeit int(blake2b(d).hexdigest(), 16) 102 us +/- 684 ns per loop In [24]: %timeit int(sha256(d).hexdigest(), 16) 142 us +/- 3.73 us In [25]: %timeit xxh3_64_intdigest(d) 3.37 us +/- 116 ns per loop ``` N)wraps)sha256)log) is_sequence)MappingreturncH[[U5R5S5$)N)int_sha256 hexdigestitems i/var/www/eduai.edurigo.com/storigo/production/storigo_env/lib/python3.13/site-packages/trimesh/caching.pyrr(s wt}&&(" --) )blake2bcF[[USS9R5S5$)NF)usedforsecurityr )r _blake2brrs r hash_fallbackr0s8D%8BBDbIIr)xxh3_64_intdigest)xxh64_intdigestzPfalling back to hashlib hashing: `pip install xxhash`for 50x faster cache checkscUc/n[R"XS9R[5nURS(deU$)aq Properly subclass a numpy ndarray to track changes. Avoids some pitfalls of subclassing by forcing contiguous arrays and does a view into a TrackedArray. Parameters ------------ array : array- like object To be turned into a TrackedArray dtype : np.dtype Which dtype to use for the array Returns ------------ tracked : TrackedArray Contains input array data. dtype C_CONTIGUOUS)npascontiguousarrayview TrackedArrayflags)arrayrtrackeds r tracked_arrayr'Is@( }""56;;LIG == (( ( NrcB^[T5U4Sj5n[U5$)a A decorator for class methods, replaces @property but will store and retrieve function return values in object cache. Parameters ------------ function : method This is used as a decorator: ``` @cache_decorator def foo(self, things): return 'happy days' ``` c>USnTRnURR5 X2RR;aURRU$T"U0UD6nURR(a;[ US5(a*[ UR5S:aSURl XBRRU'U$)zG Only execute the function if its value isn't stored in cache already. rr$F) __name___cacheverifycacheforce_immutablehasattrlenshaper$ writeable)argskwargsselfnamevaluefunctions r get_cached#cache_decorator..get_cachedys Aw    ;;$$ $;;$$T* *$)&) KK ' 'w''EKK 1$$)EKK !"' $ r)rproperty)r8r9s` rcache_decoratorr<gs)$ 8_B J rc~^\rSrSrSrSrS Sjr\S5r\RS5rSr U4Sjr U4S jr U4S jr U4S jrU4S jrU4S jrU4SjrU4SjrU4SjrU4SjrU4SjrU4SjrU4SjrU4SjrU4SjrU4SjrU4SjrU4SjrU4SjrU4SjrU4SjrU4Sjr U4Sjr!Sr"U=r#$)!r#a  Subclass of numpy.ndarray that provides hash methods to track changes. General method is to aggressively set 'modified' flags on operations which might (but don't necessarily) alter the array, ideally we sometimes compute hashes when we don't need to, but we don't return wrong hashes ever. We store boolean modified flag for each hash type to make checks fast even for queries of different hashes. Methods ---------- __hash__ : int Runs the fastest available hash in this order: `xxh3_64, xxh_64, blake2b, sha256` cVSUl[U[U55(aSUlgg)z Sets a modified flag on every TrackedArray This flag will be set on every change as well as during copies and certain types of slicing. TN) _dirty_hash isinstancetype)r5objs r__array_finalize__TrackedArray.__array_finalize__s)  c4: & &"CO 'rcxUR(a%[RR"XU/UQ70UD6$US$)zV Return a numpy scalar if array is 0d. See https://github.com/numpy/numpy/issues/5819 )ndimr ndarray__array_wrap__)r5out_arrcontextr3r4s rrJTrackedArray.__array_wrap__s6 <<::,,TGUdUfU Ur{rc URS$)N WRITEABLE)r$r5s rmutableTrackedArray.mutableszz+&&rc$XRlgN)r$r2)r5r7s rrQrRs $ rcUR(d[US5(a UR$[UR SS95nXlSUlU$)zy Return a fast hash of the contents of the array. Returns ------------- hash : long int A hash of the array contents. _hashedC)orderF)r@r/rV hash_fasttobytes)r5hasheds r__hash__TrackedArray.__hash__sNGD)$<$<<< 4<SUl[URU]"U0UD6$)zk In-place addition. The i* operations are in- place and modify the array, so we better catch all of them. T)r@super __class____iadd__r5r3r4r`s rraTrackedArray.__iadd__s( T^^T3TDVDDrcF>SUl[URU]"U0UD6$NT)r@r_r`__isub__rbs rrfTrackedArray.__isub__&T^^T3TDVDDrcF>SUl[URU]"U0UD6$re)r@r_r`fillrbs rrjTrackedArray.fill&T^^T/@@@rcF>SUl[URU]"U0UD6$re)r@r_r` partitionrbs rrnTrackedArray.partitions&T^^T4dEfEErcF>SUl[URU]"U0UD6$re)r@r_r`putrbs rrqTrackedArray.puts&T^^T.???rcF>SUl[URU]"U0UD6$re)r@r_r`byteswaprbs rrtTrackedArray.byteswaprhrcF>SUl[URU]"U0UD6$re)r@r_r`itemsetrbs rrwTrackedArray.itemset&T^^T2DCFCCrcF>SUl[URU]"U0UD6$re)r@r_r`sortrbs rr{TrackedArray.sort rlrcF>SUl[URU]"U0UD6$re)r@r_r`setflagsrbs rr~TrackedArray.setflags rhrcF>SUl[URU]"U0UD6$re)r@r_r`__imul__rbs rrTrackedArray.__imul__rhrcF>SUl[URU]"U0UD6$re)r@r_r`__idiv__rbs rrTrackedArray.__idiv__rhrcF>SUl[URU]"U0UD6$re)r@r_r` __itruediv__rbs rrTrackedArray.__itruediv__&T^^T7HHHrcF>SUl[URU]"U0UD6$re)r@r_r` __imatmul__rbs rrTrackedArray.__imatmul__&T^^T6GGGrcF>SUl[URU]"U0UD6$re)r@r_r`__ipow__rbs rrTrackedArray.__ipow__!rhrcF>SUl[URU]"U0UD6$re)r@r_r`__imod__rbs rrTrackedArray.__imod__%rhrcF>SUl[URU]"U0UD6$re)r@r_r` __ifloordiv__rbs rrTrackedArray.__ifloordiv__)s&T^^T8$I&IIrcF>SUl[URU]"U0UD6$re)r@r_r` __ilshift__rbs rrTrackedArray.__ilshift__-rrcF>SUl[URU]"U0UD6$re)r@r_r` __irshift__rbs rrTrackedArray.__irshift__1rrcF>SUl[URU]"U0UD6$re)r@r_r`__iand__rbs rrTrackedArray.__iand__5rhrcF>SUl[URU]"U0UD6$re)r@r_r`__ixor__rbs rrTrackedArray.__ixor__9rhrcF>SUl[URU]"U0UD6$re)r@r_r`__ior__rbs rrTrackedArray.__ior__=ryrcF>SUl[URU]"U0UD6$re)r@r_r` __setitem__rbs rrTrackedArray.__setitem__ArrcF>SUl[URU]"U0UD6$re)r@r_r` __setslice__rbs rrTrackedArray.__setslice__Err)r@rVrT)$r* __module__ __qualname____firstlineno____doc__rDrJr;rQsetterr\rarfrjrnrqrtrwr{r~rrrrrrrrrrrrrr__static_attributes__ __classcell__)r`s@rr#r#s& #'' ^^%%. EEAF@EDAEEEIHEEJHHEEDHIIrr#ch\rSrSrSrSSjrSrSrSSjrSr S r S r S r S r S rSrSrSrg)CacheiJzX Class to cache values which will be stored until the result of an ID function changes. cZXl[U5UlSUlSUl0Ulg)z Create a cache object. Parameters ------------ id_function : function Returns hashable value force_immutable : bool If set will make all numpy arrays read-only Nr) _id_functionboolr. id_current_lockr-)r5 id_functionr.s r__init__Cache.__init__Ps,(#O4  rc\XR;aURRUS5 gg)z Remove a key from the cache. N)r-popr5keys rdelete Cache.deletees% **  JJNN3 % rc \URS:wagUR5nXR:wa|[UR5S:aU[ R "S[UR5[[URR5555 0UlXlgg)z Verify that the cached values are still for the same value of id_function and delete all stored items if the value of id_function has changed. rNz%d items cleared from cache: %s) rrrr0r-rdebugstrlistkeys)r5id_news rr, Cache.verifyls ::? ""$ __ $4::" 5 OTZZ__./0DJ$O %rNcUc0UlgURR5VVs0sHup#X!;dM X#_M snnUlgs snnf)zl Remove elements in the cache. Parameters ----------- exclude : list List of keys in cache to not clear. N)r-items)r5excludekvs rclear Cache.clearsB ?DJ+/::+;+;+=N+=41$!$+=NDJNs AAc<URRU5 UR(a`URR5HBn[ US5(dM[ UR 5S:dM1SURlMD UR5 g)zO Update the cache with a set of key, value pairs without checking id_function. r$rFN) r-updater.valuesr/r0r1r$r2id_set)r5rrs rr Cache.updatesi %   ZZ&&(1g&&3qwwUR5 XR;$rTrrs r __contains__Cache.__contains__s jj  rcLUR5 [UR5$rT)r,r0r-rPs r__len__ Cache.__len__s 4::rc.U=RS- slgNr)rrPs r __enter__Cache.__enter__s a rcXU=RS-slUR5Ulgr)rrr)r5r3s r__exit__Cache.__exit__s a ++-r)rrr-r.r)FrT)r*rrrrrrr,rrrrrrrrrrrGrrrrJsD *&%8 O . (*!.rrc(\rSrSrSrSSjrSrSrg) DiskCacheiz Store results of expensive operations on disk with an option to expire the results. This is used to cache the multi-gigabyte test corpuses in `tests/corpus.py` cX l[RR[RR U55Ul[R "URSS9 g)z Create a cache on disk for storing expensive results. Parameters -------------- path : str A writeable location on the current file path. expire_days : int or float How old should results be considered expired. T)exist_okN) expire_daysospathabspath expandusermakedirs)r5rrs rrDiskCache.__init__s?'GGOOBGG$6$6t$<=  DII-rc[URS55R5n[RR URU5n[RR U5(an[R"5[R"U5R- S- nXPR:a&[US5nUR5sSSS5 $[R"SUS35 U"5n[US5nURU5 SSS5 U$!,(df  NW=f!,(df  U$=f)z Get a key from the cache or run a calculation. Parameters ----------- key : str Key to reference item with fetch : function If key isn't stored and recent run this function and store its result on disk. zutf-8g@rbNznot in cache fetching: ``wb)r encoderrrjoinisfiletimestatst_mtimeropenreadrrwrite)r5rfetchkey_hashrage_daysfraws rget DiskCache.gets3::g./99;ww||DIIx0 77>>$   bggdm&<&<<GH***$%668&% ,SE34g $  GGCL &%  s D.D?. D<? E)rrN))r*rrrrrrrrGrrrrs.&%rrc\rSrSrSrSrSrSrSr\ S5r \ RS5r S r S r S rS rS rSrSrSrSrg) DataStorei%z} A class to store multiple numpy arrays and track them all for changes. Operates like a dict that only stores numpy.ndarray c0UlgrTdatarPs rrDataStore.__init__-s  rc,[UR5$rT)iterrrPs r__iter__DataStore.__iter__0sDIIrc:URRUS5$rTrrrs rr DataStore.pop3syy}}S$''rc<URRUS5 grTrrs r __delitem__DataStore.__delitem__6s c4 rc[USS5$)zu Is data allowed to be altered or not. Returns ----------- is_mutable : bool Can data be altered in the DataStore _mutableT)getattrrPs rrQDataStore.mutable9stZ..rc[U5nURR5H n[U[5(dMXlM" X lg)zy Is data allowed to be altered or not. Parameters ------------ is_mutable : bool Should data be allowed to be altered N)rrrrAr#rQr)r5r7 is_mutablers rrQrEs=%[ !!#A!\**! $# rc [UR5S:XagURR5HLn[U5(a[U5S:Xa g g[ [ R "U55(dML g g)zu Is the current DataStore empty or not. Returns ---------- empty : bool False if there are items in the DataStore rTF)r0rrrrr isrealr5rs ris_emptyDataStore.is_emptyXsc tyy>Q !!#A1~~q6Q; biil##$rc0Ulg)z% Remove all data from the DataStore. NrrPs rrDataStore.clearms  rc URU$rTrrs rrDataStore.__getitem__ssyy~rc UR(d [S5e[U[5(aUnOI[U[R [ [[45(a [U5nO[U5 Un[US5(aURUlX0RU'g![a [SUS[U5S35ef=f)z Store an item in the DataStore. Parameters ------------- key A hashable key to store under data Usually a numpy array which will be subclassed but anything hashable should be able to be stored. z"DataStore is configured immutable!z unhashable `:rrN)rQ ValueErrorrAr#r rIrsettupler'hash BaseExceptionrBr/r)r5rrr&s rrDataStore.__setitem__vs||AB B dL ) )G rzz4e< = =#D)G ET G 4 $ $"llGO #! E <uAd4j\!CDD Es 1 B//&CcXR;$rTrrs rrDataStore.__contains__siirc,[UR5$rT)r0rrPs rrDataStore.__len__s499~rc~[U[5(d [S5eUR5H up#X0U'M g)Nz!Update only implemented for dicts)rAdictr,r)r5rrr7s rrDataStore.updates4&$''@A A ,,.JCI)rc 2[[R"URR 5Vs/sH5nUcM[ US5(a[ U5S:dM*[U5PM7 sn[RS9R55$s snf)zq Get a hash reflecting everything in the DataStore. Returns ---------- hash : str hash of data in hexadecimal rrr) rYr r%rrr/r0r/int64rZr#s rr\DataStore.__hash__s HH"YY--//.5a.C.Cs1vPQzDG/ hh  gi  sB B B )rrN)r*rrrrrrrrr;rQrr$rrrrrrr\rrGrrr r %sp(! / / ^^##$* #!J   rr rT)#rrsysr functoolsrhashlibrr numpyr constantsrutilrcollections.abcrr0r version_inforrrxxhashrrYrrr'r<rIr#rrr rGrrrEs, %(' .C.v+JM"5<4 niI2::iIXU.U.p@@FV V C('(. " "7 "  , " " "s;BB+ B('B(+C2B::CCCC