data:image/png;base64,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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

This 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

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 _

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 x↦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

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 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

The inputs are a starting value and one or more monadic functions. The first function is called with the starting value as its input. The second function is called with the value reported by the first function as its input, and so on. PIPE reports the value reported by the last function. PIPE provides an alternative notation for function composition instead of the usual nesting. nested acronym: report (combine (keep items (capital-letter? ( )) from (map (letter (1) of ( )) over (sentence→list (phrase)))) using (join ( ) ( ))) piped acronym: report (pipe (phrase) → (sentence→list ( )) (map (letter (1) of ( )) over ( )) (keep items (capital-letter? ( )) from ( )) (combine ( ) using (join ( ) ( ))) Some people find PIPE easier to read because the functions are called in the same order in which you read them, whereas in nested composition the innermost function is called first.

pt:a aplicação a _ de _

Takes a text string as input, and reports a new text string containing all but the first character of the input.

pt:_ sem o primeiro caractere

All but first of empty word.

Takes a text string as input, divides it into words treating one or more spaces as a word separator (only spaces count; punctuation is part of the word) and reports a text string containing all but the first word, with one space between words and no spaces at the beginning or end. (Note: consider using SENTENCE➞LIST and processing the resulting list instead of doing recursion on sentences in text string form. List operations are faster.)

pt:_ sem a primeira palavra

All but first of empty sentence.

Takes a text string as input, and reports a new text string containing all but the last letter of the input.

pt:_ sem o último caractere

All but first of empty word.

Takes a text string as input, divides it into words treating one or more spaces as a word separator (only spaces count; punctuation is part of the word) and reports a text string containing all but the last word, with one space between words and no spaces at the beginning or end. (Note: consider using SENTENCE->LIST and processing the resulting list instead of doing recursion on sentences in text string form. List operations are faster.)

pt:_ sem a última palavra

All but last of empty sentence.

pt:a primeira palavra de _

Takes a text string as input, and reports the last character in the string.

pt:o último caractere de _ 0

pt:a última palavra de _

Last of empty sentence.

Takes a text string as input, and reports TRUE if the string has no characters in it of any kind, otherwise false.

pt:a palavra _ está vazia 0

Takes a text string as input, and reports TRUE if the input contains no characters other than spaces (therefore, no words when the string is considered as a sentence), otherwise FALSE.

pt:a frase _ está vazia

Like JOIN, takes any number of words (text strings) and reports a sentence with its inputs concatenated, but inserts a blank space between the inputs. Consider using SENTENCE (Lists palette) instead.

de:füge Wörter zusammen _ ca:uneix les paraules _ es:unir las palabras _ fr:fusionne les mots _ pt:uma frase com as palavras _ firstbffirst1

1bf

Takes a sentence in list form and reports the sentence as a text string.

de:Liste $arrowRight Satz _ ca:llista $arrowRight frase _ es:lista $arrowRight frase _ fr:liste $arrowRight phrase _ pt:uma frase com as palavras em _

Takes a sentence in text string form and reports the sentence as a list of its words.

de:Satz $arrowRight Liste _ ca:frase $arrowRight llista _ es:frase $arrowRight lista _ fr:phrase $arrowRight liste _ pt:uma lista com as palavras da frase _

report a list in which each item is one letter from the input word

de:Wort $arrowRight Liste _ ca:paraula $arrowRight llista _ es:palabra $arrowRight lista _ fr:mot $arrowRight liste _ pt:uma lista com os caracteres da palavra _

join all the items of the input list into a single word, and report it

de:Liste $arrowRight Wort _ ca:llista $arrowRight paraula _ es:lista $arrowRight palabra _ fr:liste $arrowRight mot _ pt:uma palavra com os caracteres em _

SENTENCE is the main constructor for sentences, represented as lists of words. It takes zero or more inputs, each of which can be either a list or a text string. If a list, the input is assumed to be a list of words. If a text string, it is converted to a list of words using SENTENCE→LIST. Then all the lists of words are appended to form a new list of words. If the inputs are lists of lists rather than lists of words, SENTENCE, like APPEND, does only one level of flattening, reporting a list of all the items of all the input lists.

pt:lança o erro _

Takes a (possibly deep) list as input, and reports a human-readable text form of the list (namely, Lisp notation).

(

)

Helper function for word/sentence library. Reports its first input, unless that input is empty, in which case it gives its second input as an error message.

Takes a text string as input, and reports the first character in the string.

pt:a primeira palavra de _

pt:o texto multilinha _

Reports the part of the first string up to the first instance of the second string inside it. If the second string isn't found, reports the entire first string.

pt:o texto de _ antes de _

Reports the portion of the first input string starting after the first occurrence of the second string. If the second string isn't found in the first string, reports an empty string.

pt:o texto de _ depois de _

Reports the character position (starting from 1) of the beginning of the first input string inside the second input string. If it's not found, reports 0.

pt:a posição de _ em _

If input is TRUE, comparisons made by functions in the string library will be case-independent (so "FOO" = "foo"). This is the default. If input is FALSE, comparisons will be exact.

pt:altera comparações ignorando distinção minúsculas/maiúsculas para _

Reports the portion of the first input (string) starting at the position given by the second input (counting from 1, like LETTER n OF) and ending at the position given by the third input (also counting from 1). If the third input is empty, reports the portion from the first position to the end of the string. If a position number is negative, counts from the end backward, so -1 is the last character, -2 is the next to last, etc.

pt:o texto de _ entre as posições _ e _ , inclusive

Reports True if the first input string contains the second input string, otherwise false. Comparison is case-independent by default; use USE CASE-INDEPENDENT COMPARISONS to change that.

pt:o texto de _ antes de _

Reports the input text with lower case letters instead of capital letters in the input. Uses the user's locale's rules for case conversion.

pt:em minúsculas _

err_reset

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KBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECByxcQFpoRMBzwAAAABJRU5ErkJggg==