data:image/png;base64,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

Digitsi1

+-x/+-x/outClone

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 ca:_ sense la primera lletra

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 ca:_ sense la primera paraula

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 ca:_ sense la darrera lletra

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 ca:_ sense la darrera paraula

All but last of empty sentence.

pt:a primeira palavra de _ ca:primera paraula de _

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

pt:o último caractere de _ ca:primera lletra de _ 0

pt:a última palavra de _ ca:darrera paraula 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 ca:paraula buida? _ 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 ca:frase buida? _

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.

ca:frase _

pt:lança o erro _

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

ca:notació textual de _ (

)

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 _ ca:primera lletra de _

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