ԋgBdZddlmZddlZddlZddlZddlZddlZddlm Z m Z ddl m Z m Z ddlmZddlmZddlmZddlZddlZdd lmZmZdd lmZmZdd lmZdd lm Z ejBZ"d"d Z#d#dZ$d$dZ%d%dZ&dddd d&dZ'd'dZ(d(dZ)d)dZ*d*dZ+ d+dZ,dddeddf d,dZ-d-dZ.dZ/dZ0 d.d Z1d!Z2y)/a, This module contains utility functions to construct and manipulate counting data structures for frames. When performing statistical profiling we obtain many call stacks. We aggregate these call stacks into data structures that maintain counts of how many times each function in that call stack has been called. Because these stacks will overlap this aggregation counting structure forms a tree, such as is commonly visualized by profiling tools. We represent this tree as a nested dictionary with the following form: { 'identifier': 'root', 'description': 'A long description of the line of code being run.', 'count': 10 # the number of times we have seen this line 'children': { # callers of this line. Recursive dicts 'ident-b': {'description': ... 'identifier': 'ident-a', 'count': ... 'children': {...}}, 'ident-b': {'description': ... 'identifier': 'ident-b', 'count': ... 'children': {...}}} } ) annotationsN) defaultdictdeque)Callable Collection)sleep) FrameType)Any) NoDefault no_default) format_timeparse_timedelta)time)color_ofcT|y|j} dj|j|jt |j fS#t $rR|jr)|jd|jdt|cYS|jdt|cYSwxYw)zpA string identifier from a frame Strings are cheaper to use as indexes into dicts than tuples or dicts None;.:) f_codejoinco_name co_filenamestrco_firstlinenoAttributeError __module__ __qualname__ _f_lineno)framecos 3lib/python3.12/site-packages/distributed/profile.py identifierr#6s  } \\ ?88JJNN))*  ?}}--"//):!Ie>  ?s:A filenamename line_numberr5) rrrrr0r1r2r3r IndexErrorr)r r!r&r<r;r5s r" info_framer?os BH zz>>  5??KRRT    J '  sAA11BB)stopomitdepthc|!tdtjdz}tfd|Dryj}|dkDrA|?|%|j j j|st||||dz }|y|}t} |d|} |d xxdz cc<|| S| d xxdz cc<y#t$rdti|d } | |d|<YBwxYw) aAdd counts from a frame stack onto existing state This recursively adds counts to the existing state dictionary and creates new entries for new functions. Parameters ---------- frame: The frame to process onto the state child: For internal use only state: The profile state to accumulate this frame onto, see ``create`` stop: Filename suffix that should stop processing if we encounter it omit: Filenames that we should omit from processing depth: For internal use only, how deep we are in the call stack Used to prevent stack overflow Examples -------- >>> import sys, threading >>> ident = threading.get_ident() # replace with your thread of interest >>> frame = sys._current_frames()[ident] >>> state = create() >>> process(frame, None, state) >>> state {'count': 1, 'identifier': 'root', 'description': 'root', 'children': {'...'}} See also -------- create merge Ndc3hK|])}jjj|+ywN)rrendswith).0or s r" zprocess..s' >A5<< # # , ,Q /s/2r)rArCchildrencount descriptionrNr#rP) minsysgetrecursionlimitanyf_backrrrIprocessr#KeyErrorr?) r childstaterArBrCprev new_stateidentds ` r"rWrWs` } C..0A56 > >> <.s-G srrQ)rQrNrPr#) createlen ValueErrorrlistappenditemsmergeRecursionErrorsum) argsrasrNrYkv children_dictrPs r"rhrhs x&*+ds\ dA+ 1v{5aS9::4 H_E UO " "3z?5#9 :%2:..2BC2B$!QE1I2B C -- -EAw}-!1gl+   ,D  s) C6C C C C CCcdidddddddS)Nrrootr9r:)rPrNr#rQr@r@r7r"rbrbs!$&1bQ  r7cpg}|}|r)|jt||j}|r)|dddS)zWCreate a call text stack from a frame Returns ------- list of strings Nr%)rfr6rV)r L cur_frames r" call_stackrusA A"'I  I&'$$   TrT7Nr7c g g gggg ggg gg   f d|dddDcgc] }d|zdd }} Dcgc]}|dz c}   |d Scc}wcc}w)zConvert a profile state into data useful by Bokeh See Also -------- plot_figure distributed.bokeh.components.ProfilePlot c |dsyj|j| j|||z }j|j|jt|dz|d} j|dj|dj|dj|d |d}|dk(r jdn jt| ||z |dz }|}|d j D]#\} } | d|z}| |||z|d z||z }%y#t$r jd YcwxYw) NrPrQr;r5r=r< lightgraygrayrNrM)rfr rr>rg)rZr-rAheightwidthdescfndeltax_rYcolors filenamesheights line_numberslinesnamesprofile_intervalstartsstatesstopstimestraversewidthss r"rzplot_data..traverse#soW~  e Tvu  e e [w2B!BCD]#j)* T&\"D/0 T&\" ,j!B]" k* hrl+w/ j)//1HAu'NU*E UAq5y&1* 5 JA2 " MM& ! "sEE32E3rrMrEz.1f%) leftrightbottomr|topcolorrr;r5r=r<r percentager@)rZrw percentagesrrrrrrrrrrrrrs ` @@@@@@@@@@@@r" plot_datarsF EG F F F EI EL E"""H UAq!.45fcAgc]!$fK5&'w!Aw'#! 6 (s A7 A< ct}t}|st||zkDrft}t5|jt|ft} t j |}t|d||~dddt||syy#t $r YdddywxYw#1swY5xYw)N)rB) rbrlockrfrS_current_framesrXrWr) thread_idlogintervalcyclerBrArecentlastr s r"_watchrZsXF 6Df 6D5L XF DFF+,v//1)#B':B>' B;0B>:B;;B>>C20ms2scy)NFr@r@r7r"r{sur7c X|tur3tjjd}t |t s|Jt |}tjtd|xstjt|t||||d}d|_ |j|S)aFGather profile information on a particular thread This starts a new thread to watch a particular thread and returns a deque that holds periodic profile information. Parameters ---------- thread_id : int, optional Defaults to current thread interval : str Time per sample cycle : str Time per refreshing to a new profile state maxlen : int Passed onto deque, maximum number of periods omit : collection of str Don't include entries whose filename includes any of these substrings stop : callable Function to call to see if we should stop. It must accept no arguments and return a bool (True to stop, False to continue). Returns ------- deque of tuples: - timestamp - dict[str, Any] (output of ``create()``) z&distributed.admin.low-level-log-length)maxlenProfile)rrrrrBrA)targetr<kwargsT)r daskconfigget isinstanceintr threadingThreadr get_identrdaemonr-)rrrrrBrArthreads r"watchrusJ!IJ&#&&.88/4F/CC    ";i&9&9&;'1$U+   FFM LLN Jr7c|d}ntj||f}|d}n*tj||fdz}|t|k\rd}|dk(r| t |}n+| t|n|}t ||Dcgc]}|| }}t tjd|} |s tS|r t | |} | Scc}w)aCollect profile information from a sequence of profile states Parameters ---------- history : Sequence[Tuple[time, Dict]] A list or deque of profile states recent : dict The most recent accumulating state start : time stop : time NrrM) bisect bisect_left bisect_rightrcrerangerhtoolzpluckrb) historyrr-rAkeyistartistopiistopiprofs r" get_profilers }##GeX6 |##GdW59 CL E {u}w-!&WE',VV'<='s< Cc jddlm}ddlm}m}d|vrt j |d}||}|dddi|}|jdd d d d d d|}d|_d|_ |dd}|j|d|j_ d|j_ d|j_ ||fS)zPlot profile data using Bokeh This takes the output from the function ``plot_data`` and produces a Bokeh figure See Also -------- plot_data r) HoverTool)ColumnDataSourcefigurer)datatoolsztap,box_zoom,xwheel_zoom,resetrrrrrblack)r line_color line_widthsourceN follow_mousea3
Name:  @name
Filename:  @filename
Line number:  @line_number
Line:  @line
Time:  @time
Percentage:  @percentage
) point_policytooltipsFr@) bokeh.modelsrbokeh.plottingrrrdissocquadselection_glyphnonselection_glyph add_toolsxaxisvisibleyaxisgrid) rrrrrrfigrhovers r" plot_figurers'74||D(+ 4 (F  B7 B6 BC    AAA # E:MM%CIICIICHH ;r7c#>K|D]}|jry|ywrH) is_python)framesentrys r"_remove_py_stackr!s ??  sc|sy|j}|r t|||}|sJt|j|jz }dj t t|jd|f} |d|}|dxxd z cc<||S|dxxd z cc<y#t$r*dd|jdt|di|d}||d|<YQwxYw) aUAdd counts from low level profile information onto existing state This uses the ``stacktrace`` module to collect low level stack trace information and place it onto the given state. It is configured with the ``distributed.worker.profile.low-level`` config entry. See Also -------- process ll_get_stack NrrxrNrr:rOrPrM) pop llprocesshexaddroffsetrmaprr<rX)rrYrZr rr]r^s r"rr(s$  JJLE &%/ L5 uzzELL( )D HHSuzz=$?@ AE% * e $ 'NaN  ' a )  %)  E   $%j%  %s6B0CCcZddlm}||d}tt|ddd}|S)z2Collect low level stack information from thread idr)get_thread_stackF) show_pythonNr%) stacktracerrer)tidrrllframess r" ll_get_stackr\s/+ cu 5F$V,-dd3H Or7)r zFrameType | Nonereturnr)r r rr)r r rr)r r rdict[str, Any])r r rY object | NonerZrrAz str | NonerBCollection[str]rC int | Nonerdict[str, Any] | None)rkrrr)rr)r r rz list[str])g{Gz?)rrr#deque[tuple[float, dict[str, Any]]]rfloatrrrBrrACallable[[], bool]rr)rrrrrrrzint | None | NoDefaultrBrrArrr)NNNN)rYrrZrrr)3__doc__ __future__rrr(r0rSr collectionsrrcollections.abcrrrrtypesr typingr tlzr dask.configr dask.typingr r dask.utilsr rdistributed.metricsdistributed.utilsrLockrr#rr6r?rWrhrbrurrrrrrrrr@r7r"r s6#  *0-3$&y~~?00 0X X X X  X  X XXv2 IX ,       8!%/, 999 9 # 9  9  9)9x&RDN1 1 !1 1hr7