SCL2 m2u1 [ + ] afegeix un personatge que pots moure per l'esceniri per definir la seva trajectòria. [ > ] reprodueix les trajectòries dels personatges. [ < ] reprodueix les trajectòries dels personatges cap 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 m2u1 [ + ] afegeix un personatge que pots moure per l'esceniri per definir la seva trajectòria. [ > ] reprodueix les trajectòries dels personatges. [ < ] reprodueix les trajectòries dels personatges cap enrera.

Take any number of input lists, and create a new list containing the items of the input lists. So APPEND [A B] [C D] where the [...] are lists reports the list [A B C D] not [[A B] [C D]].

1111

Reports a new list containing the items of the input list, but in the opposite order.

1inputresult

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.

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.

copy of datasplitmerge11#1#2

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.

This block applies the given function to each item of the given list, like the primitive MAP block, but with two differences: 1. The # variable provided will contain the item number of the item currently being used in the given function: 1 for item 1, and so on. You read the variable in your function; don't set it. 2. You can provide more than one input list. If so, the lengths of all the lists should be the same, and the function you supply must expect as many inputs as you have lists (i.e., that many empty input slots in the function).

#11datacountmapmany#

1data listscount

This block makes a new list containing selected items from the given list, like the primitive KEEP block. What's different is that it provides the # variable for use in your predicate function. It will contain the item number (in the original list) of the item being examined by the predicate.

#1datacount1

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.

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KBgAAH6CYJECBAgIAA+wECBAgQIBAICHCAbpIAAQIECByxcQFpoRMBzwAAAABJRU5ErkJggg==