data:image/png;base64,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 a new list whose items are the same as in the input list, except that if two or more equal items appear in the input list, only the first one is kept in the result.ca:elimina els duplicats de _
1Reports a sorted version of the list in its first input slot, using the comparison function in the second input slot. For a list of numbers, using < as the comparison function will sort from low to high; using > will sort from high to low.ca:ordena _ segons criteri _
copy of datasplitmerge11#1#2The second input is an "association list," a list of two-item lists. Each of those smaller lists has a "key" as its first item and a "value" as its second. ASSOC reports the first key-value pair in the association list whose key matches the first input.ca:associació _ _
11This block carries out the given script for each item of the given list, like the primitive FOR EACH.
What's different is that it provides the # variable, which will contain the item number in the list of each item in turn, 1 while processing item 1, and so on.ca:_ per cada _ de _ _
1Takes a (possibly deep) list as input,
and reports a human-readable text form
of the list (namely, Lisp notation).
Will not work on circular lists.()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.ZIP takes any number of lists as inputs. The lists should all be the same length. ZIP reports a list of lists in which the first item is a list of all the first items, the second item is a list of all the second items, etc.
Viewing the inputs as the rows of a matrix, ZIP reports its transpose.1The identity function reports its input.Takes as input a function of N inputs and N lists.
The function is called with item 1 of all the lists as its inputs, with item 2 of all the lists as its inputs, and so on. (The lists should all be the same length.)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 _
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