In general, sleep sort works by starting a separate task for each item to be sorted, where each task sleeps for an interval corresponding to the item's sort key, then emits the item. Items are then collected sequentially in time.
Only positive integersdata:image/png;base64,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In general, sleep sort works by starting a separate task for each item to be sorted, where each task sleeps for an interval corresponding to the item's sort key, then emits the item. Items are then collected sequentially in time.
Only positive integers#1By LouchemanThis is a message !false@SaveX@SaveY@SaveDir@SaveCostume@SaveGhostEffect@SaveColor@SaveSaturation@SaveBrightness@SaveFisheye@SaveWhirl@SaveNegative@SaveMosaic@SavePixelateThis block reports "true" if there is a variable with this given name (input slot) in that context.
It can be a global, sprite or script variable.
Otherwise it reports "false".pt:a variável _ existe
ca:existeix la variable _ ?
es:existe la variable _ ?
de:existiert var _ ?
err_resetMySpriteVarMySpriteVarThis block creates new variables on the selected scope: global (for all sprites), sprite (for this sprite only) or script (only for that blocks stack) with the names given (in 'names' list).
If there is already a variable with that name in that scope, it does nothing: no errors and no overwrites.pt:cria as variáveis _ _
ca:crea les _ variables _
es:crear las _ variables _
de:erstellen _ var _
globalglobal
sprite
scriptThis block sets the given value (last input) to the variable named with the name givent (var input).
It looks for that variable following the scope order 'script' -> 'sprite' -> 'global' (the first match it finds).
If that variable does not exist (in any scope) an error happens, stopping their script. You can check it before using the "does var (name) exists?" block. ca:assigna a _ el valor _
es:asignar a _ el valor _
pt:altera _ para _
de:setze var _ auf _
§_getVarNamesDictde:fange _ _
ca:agafa _ _
es:atrapar _ _
fr:attrape _ _
pt:captura _ _
pl:przechwyć _ _
contde:wirf _
ca:llança _
es:lanzar _
fr:lance _
pt:lança _
pl:wyrzuć _
catchtagde:fange _ _
ca:agafa _ _
es:atrapar _ _
fr:attrape _ _
pt:captura _ _
pl:przechwyć _ _
contde:wirf _ _
ca:llança _ _
es:lanzar _ _
fr:lance _ _
pt:lança _ _
pl:wyrzuć _ _
catchtagThis is a breakpoint block, to be used in debugging.
The Boolean input specifies the condition under which
the program should pause. (Use True for an unconditional breakpoint.) The intent is that the script should have
SHOW VARIABLE blocks for the process's local variables.
After the pause, this block automatically hides all temporary variables.de:falls _ dann _ und pause $pause-1-255-220-0
ca:si _ fes _ i atura-ho tot $pause-1-255-220-0
es:si _ haz _ y páralo todo $pause-1-255-220-0
fr:si _ faire _ et mettre tout en pause $pause-1-255-220-0
pt:se _ , então _ e faz pausa em tudo $pause-1-255-220-0
pl:jeżeli _ wykonaj _ i pauzuj wszystko $pause-1-255-220-0
This block does nothing.
Use it when you are calling a reporter
for its side effect and don't care about
its return value.de:ignoriere _
ca:ignora _
es:ignorar _
fr:ignore _
pt:ignora _
pl:ignoruj _
Call f(f(f(...(f(x))))) n times where the three input slots are n, f, and x from left to right. The # variable can be used inside f to represent how many times f has been called.pt:o resultado de _ invocações em cascata de _ com argumento inicial _ _
ca:en cascada _ vegades _ _ _
pl:kaskada _ razy _ _ _
Call f(f(f(...(f(x))))) until condition is true, where the three input slots are condition, f, and x from left to right. The # variable can be used inside f or condition to indicate how many times f has been called.pt:o resultado da invocação em cascata até que _ de _ com argumento inicial _ _
ca:en cascada fins _ _ _ _
pl:kaskada aż _ _ _ _
Returns the function x↦f(g(x)) where f and g are the two inputs.pt:a composição de _ com _
ca:composa _ _
pl:skomponuj _ _
Like the built-in REPEAT UNTIL block, except that the ending condition is not tested until the script has been run the first time. So the script is run at least once.pt:repete _ até que _ $loop-0.7
ca:repeteix _ fins _
pl:powtarzaj _ aż _
Run the script repeatedly, as long as the given condition is true. Runs the script at least once before testing the condition.pt:repete _ enquanto _ $loop-0.7
ca:repeteix _ mentre _
pl:powtarzaj _ gdy _
Runs the script repeatedly, as long as the condition is true. Tests the condition before the first time the script is run. Like the built in REPEAT UNTIL except that in this block the condition must be true, not false.pt:enquanto _ , repete _ $loop-0.7
pl:powtarzaj gdy _ _
Runs the script the specified number of times, like the built-in REPEAT block, but this one provides the # variable that can be used inside the script. Try
REPEAT (200)
MOVE (#) STEPS
RIGHT 92
with the pen down.pt:repete _ vezes _ _ $loop-0.7
ca:repeteix _ _ _
pl:powtórz _ _ _
The primitive FOR block uses an implicit step of ±1 depending on which of the starting and ending values is larger. This version allows you to provide an explicit step value. If the sign of the step input is incompatible with the ordering of the starting and ending values, the script will not be run at all.pt:para _ de _ com passo _ a _ _ $loop-0.7
ca:per _ = _ incrementant _ fins _ _
pl:dla _ = _ co _ do _ _
1110Provides LOOP as a function of one input that runs
the body of the LET with A set to the function input,
so the body can run itself recursively.
See COPY block in Variables for an example of use.pt:tendo _ o valor inicial _ , executa _ definido como _
ca:fes que _ sigui _ al _ _
pl:ustaw _ na _ w _ _
new valuede:führe _ mit Continuation aus
de:rufe _ mit Continuation auf
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build the unsorted listIt will take 10 seconds to sort the list !#1i add "#1/10" for speed purpose...gotruebh said it doesn't work all time with #1/100 seconds, so i change it for #1/10
thk bh!the original algorithm wait #1 second instead of #1/10 seconds1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,10013,39,43,28,73,10,54,16,66,31,80,15,92,97,91,30,25,76,78,44,34,21,72,74,62,50,1,55,59,51,6,75,93,2,99,96,7,45,69,90,12,94,14,8,9,4,65,100,86,77,33,19,49,64,18,52,53,82,27,35,36,41,20,46,68,40,71,3,81,24,79,32,11,70,38,37,98,88,87,85,42,22,63,48,29,89,58,47,57,17,26,67,84,95,56,60,61,23,5,83