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

de:fange _ _ ca:agafa _ _ es:atrapar _ _ fr:attrape _ _ pt:captura _ _ cont

de:wirf _ ca:llança _ es:lanzar _ fr:lance _ pt:lança _ catchtag

de:fange _ _ ca:agafa _ _ es:atrapar _ _ fr:attrape _ _ pt:captura _ _ cont

de:wirf _ _ ca:llança _ _ es:lanzar _ _ fr:lance _ _ pt:lança _ _ catchtag

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

de:ignoriere _ ca:ignora _ es:ignorar _ fr:ignore _ pt:ignora _

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 _ _

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 _ _

Returns the function f(g(x)) where f and g are the two inputs.

pt:a composição de _ com _

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

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

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

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

pt:para _ de _ com passo _ a _ _ $loop-0.7 1110

Provides 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 _ new value