Possible Triples: (1,2,3) (4,5,6)(7,8,9) (1,4,7) (2,5,8) (3,6,9) (1,5,9) (3,5,7)data:image/png;base64,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data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAeAAAAFoCAYAAACPNyggAAACtUlEQVR4nO3BMQEAAADCoPVPbQwfoAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA+Bo3+AAF/RMkcAAAAAElFTkSuQmCCstart_gamethis sprite is an abstraction.

LABEL will stamp text on the stage at the given font size. The direction of the text is the direction the sprite is facing, and color will match the pen color.

Hello!12

1datamapmany

data lists

110i

121

cont

catchtag

cont

catchtag

Sprite

-50-50This algorithm has an O (NxN) efficiency.What happens when you have a loop inside a loop.-50-50

game_overfalse

triple_square10

000

falsex,o,x,o,x,empty,x,empty,otrue1,9,3,7,5,2,4,6,8false