data:image/png;base64,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:image/png;base64,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bye girl bye.....

2010001000

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 resulti2

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 0

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 resulti1

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 01 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 _ index01 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 index10

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 _ 1121

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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1,2,3,4,5,6,7,8,9,0b,V,e,*,V,W,Z,!,#,410!,@,#,$,%,&,*yesyesA,B,C,D,E,F,G,H,I,J,K,L,M,N,O,P,Q,R,S,T,U,V,W,X,Y,Zq,w,e,r,t,y,u,i,o,p,a,s,d,f,g,h,j,k,l,z,x,c,v,b,n,myesyes