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

Reports 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 last one is kept in the result.

ca:elimina els duplicats de _

Reports 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 _

The 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 _ _

This 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 _ _

Takes 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.

ca:notació textual de _ (

)

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 _

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.

The 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.)

ca:multi-mapeja _ sobre _

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 _

Invaders

false

Invader Movement-10.5

Player

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-23080120-235-134.99999999999710