This is the project which started it all. After an example by E. Paul Goldenberg. Featuring recursion without the need for a base case and first class custom blocks it was Brian's demo at the 2008 Scratch conference, why Scratch needed custom procedures.To this day, Vee is the first project we test whenever we change anything or add new features to 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This is the project which started it all. After an example by E. Paul Goldenberg. Featuring recursion without the need for a base case and first class custom blocks it was Brian's demo at the 2008 Scratch conference, why Scratch needed custom procedures.To this day, Vee is the first project we test whenever we change anything or add new features to Snap.
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 es:todos menos la primera letra de _ pl:_ bez pierwszej litery 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 es:todas menos la primera palabra de _ pl:_ bez pierwszego słowa 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 es:todos menos la última letra de _ pl:_ bez ostatniej litery 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 es:todos menos la última palabra de _ pl:_ bez ostatniego słowa All but last of empty sentence.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 first word, with no spaces before or after it.
pt:a primeira palavra de _ ca:primera paraula de _ es:primera palabra de _ pl:pierwsze słowo _ Takes a text string as input, and reports the last character in the string.
pt:o último caractere de _ ca:primera lletra de _ es:última letra de _ pl:ostatnia litera _ 0Takes 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 _ ca:darrera paraula de _ es:última palabra de _ pl:ostatnie słowo _ 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? _ es:¿palabra vacía? _ pl:puste słowo? _ 0Takes 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? _ es:¿oración vacía? _ pl:puste zdanie? _ 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 _ pl:połącz słowa _ firstbffirst111bf 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 _ pl:lista $arrowRight zdanie _ 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 _ pl:zdanie $arrowRight lista _ 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 _ pl:słowo $arrowRight lista _ 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 _ pl:lista $arrowRight słowo _ 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 _ es:oración _ pl:zdanie _
pt:lança o erro _ pl:błąd _ Takes a (possibly deep) list as input, and reports a human-readable text form of the list (namely, Lisp notation).
ca:notació textual de _ es:imprimible _ pl:tekstowa _ ( )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.
es:requerir no vacío _ _ Takes a text string as input, and reports the first character in the string.
pt:a primeira palavra de _ ca:primera lletra de _ es:primera letra de _ pl:pierwsza litera _ 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