data:image/png;base64,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

Blanks

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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