data:image/png;base64,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:image/png;base64,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guessedstring1Letter replacementlives-1whenever the platform breaks, you have to click the green flag twiceThe art could be a little better-Jovy L

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 strreturn str.slice(1);

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 strreturn str.slice(0,-1);

All but last 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

arrreturn new List(arr.asArray().slice(0,-1));

All but last of empty sentence.

1 11 1

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.

1 1

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).

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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 _

string1lives-1

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