>ie UdZddlmZddlZddlZddlZddlZddlm Z ddl m Z m Z ddl mZmZddlmZmZddlmZdd lmZmZdd lmZdd lmZd ZeZdad ed<e eZ ded<eZ!dZ" dddZ#dS)z2 A threaded shared-memory scheduler See local.py ) annotationsN) defaultdict)MappingSequence)ExecutorThreadPoolExecutor)Lockcurrent_thread)config)MultiprocessingPoolExecutor get_async) CPU_COUNT)Keyc(tjS)N)r ident-lib/python3.11/site-packages/dask/threaded.py_thread_get_idrs    !!rzExecutor | None default_poolz2defaultdict[threading.Thread, dict[int, Executor]]poolsc8|tjdfS)N)sysexc_info)edumpss rpack_exceptionr!s clnnQ rdskrkeysSequence[Key] | Keyc |ptjdd}|ptjdd}t}t5||J|turAt 2t tatj t j t }n|tvr#|t|vrt||}ngt |}tj |j |t||<n.t|tjjrt!|}dddn #1swxYwYt#|j|j||f|t(t*d|}t5t-t/j}|tur^t3tD]I} | |vrCt| D]} | Jdddn #1swxYwY|S)aThreaded cached implementation of dask.get Parameters ---------- dsk: dict A dask dictionary specifying a workflow keys: key or list of keys Keys corresponding to desired data num_workers: integer of thread count The number of threads to use in the ThreadPool that will actually execute tasks cache: dict-like (optional) Temporary storage of results Examples -------- >>> inc = lambda x: x + 1 >>> add = lambda x, y: x + y >>> dsk = {'x': 1, 'y': 2, 'z': (inc, 'x'), 'w': (add, 'z', 'y')} >>> get(dsk, 'w') 4 >>> get(dsk, ['w', 'y']) (4, 2) poolN num_workers)cacheget_idr)r getr pools_lock main_threadrrratexitregistershutdownr isinstancemultiprocessingr#Poolr r submit _max_workersrrset threading enumeratelistpopvalues) rr r%r$r#kwargsthreadresultsactive_threadstps rr'r'%spB  +6:fd++D@M4!@!@K   F 55 <"v'<'<'#5i#@#@LOL$9:::#5[E&M%A%AV}[1)+66 ...-1f k** o27 8 8 5.t44D555555555555555      %     G %%Y02233  $ $%[[ % %N**"YYq\\0022%% %%%%%%%%%%%%%%% Ns&C"D22D69D6,BHHH)NNN)rrr r!)$__doc__ __future__rr*multiprocessing.poolr.rr3 collectionsrcollections.abcrrconcurrent.futuresrrr r daskr dask.localr r dask.systemr dask.typingrrr)r__annotations__dictrr(rr'rrrrJs #"""""  ######--------;;;;;;;;********========!!!!!!"""n $ $$$$