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HaFb5S+/1b5/cvpT220nia5yJcdVudR9fQu8DV6eZ6JzNzsRlh751zdNVpuLHzQO1qcwzHxCgQXmvqr4/hYD0SN2P/rh/wstNH8H9lwUkFdxNzAQAAAABJRU5ErkJggg==data:image/png;base64,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0-1yes234.1no1#1011212-1Testmedian list#002falsefalse1Takes 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
resulti2Takes 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
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
resulti1Takes 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
11111Takes 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 only the first word, with no spaces before or after it.pt:a primeira palavra de _
Takes a text string as input, and reports the last character in the string.pt:o último caractere de _
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 only the last word of the input, with no spaces before or after it.pt:a última palavra de _
11Takes 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
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
de:füge Wörter zusammen _
ca:uneix les paraules _
es:unir las palabras _
fr:fusionne les mots _
pt:uma frase com as palavras _
121de:Liste $arrowRight Satz _
ca:llista $arrowRight frase _
es:lista $arrowRight frase _
fr:liste $arrowRight phrase _
pt:uma frase com as palavras em _
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 wordde: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 itde:Liste $arrowRight Wort _
ca:llista $arrowRight paraula _
es:lista $arrowRight palabra _
fr:liste $arrowRight mot _
pt:uma palavra com os caracteres em _
random wordde:Kostüm aus Text _ Größe _
pt:um traje com o texto _ de tamanho _
A72#20##0Length360Width480360230current center12515152522515252falsetruefalsebactrackfalse-80000-8000001234a112error15,0,3,1List of squareslist of dimensionslist of center pointsSqr#0pt:tenta executar _ e, em caso de erro _ , executa _
returnpt:lança o erro _
pt:cria a variável de guião _ com valor _
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