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Josh VanderLinden committed bb3aa92

Renaming the readme

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README

-sudokulib is a collection of tools that are useful for generating solutions to 
-Sudoku puzzles.  It uses a recursive backtracking algorithm (originally 
-written by Jeremy Brown, Cel Destept), and is capable of generating a 3x3 
-Sudoku in ~0.015 seconds.  It can also generate 4x4 Sudokus in ~0.100 seconds 
-(sometimes longer).
-
-Some 5x5 grids have been generated in a matter of seconds using this library, 
-but I've also seen the program run for hours without successfully generating 
-a 5x5.  Anything beyond 5x5 always seems to take a long time.
-
-You can solve Sudoku puzzles using this library by calling the ``init_grid`` 
-method of an instance of ``Sudoku``.  This method takes two types of values. 
-Where ``n`` is the grid size:
-
-* a 1-dimensional list with n^4 values
-* a multi-dimensional list with n^2 lists with n^2 values each.  Each list 
-  represents a row in the grid
-
-The values in the list(s) provided to ``init_grid`` must be numeric and 
-greater than 0 but less than n^2 in order to appear in the starting grid. Any 
-other values will be ignored, and the puzzle will be solved with no 
-consideration for such values.
-
-The library also provides utilities for generating starting grids, so you can 
-play Sudoku instead of just generating solutions.  There are several difficulty 
-levels to choose from.
-
-Also included in the distribution is a sample class for generating "jigsaw" 
-variations of Sudoku.  This class will occasionally generate solvable grids 
-within a second or two, but it takes much longer more often than not.
-
-Another variation of Sudoku, called Hyper Sudoku, can be found in hyper.py. 
-This one involves four additional regions inside the grid.  See the entry 
-for Sudoku on Wikipedia for an image of Hyper Sudoku.
-
+sudokulib is a collection of tools that are useful for generating solutions to 
+Sudoku puzzles.  It uses a recursive backtracking algorithm (originally 
+written by Jeremy Brown, Cel Destept), and is capable of generating a 3x3 
+Sudoku in ~0.015 seconds.  It can also generate 4x4 Sudokus in ~0.100 seconds 
+(sometimes longer).
+
+Some 5x5 grids have been generated in a matter of seconds using this library, 
+but I've also seen the program run for hours without successfully generating 
+a 5x5.  Anything beyond 5x5 always seems to take a long time.
+
+You can solve Sudoku puzzles using this library by calling the ``init_grid`` 
+method of an instance of ``Sudoku``.  This method takes two types of values. 
+Where ``n`` is the grid size:
+
+* a 1-dimensional list with n^4 values
+* a multi-dimensional list with n^2 lists with n^2 values each.  Each list 
+  represents a row in the grid
+
+The values in the list(s) provided to ``init_grid`` must be numeric and 
+greater than 0 but less than n^2 in order to appear in the starting grid. Any 
+other values will be ignored, and the puzzle will be solved with no 
+consideration for such values.
+
+The library also provides utilities for generating starting grids, so you can 
+play Sudoku instead of just generating solutions.  There are several difficulty 
+levels to choose from.
+
+Also included in the distribution is a sample class for generating "jigsaw" 
+variations of Sudoku.  This class will occasionally generate solvable grids 
+within a second or two, but it takes much longer more often than not.
+
+Another variation of Sudoku, called Hyper Sudoku, can be found in hyper.py. 
+This one involves four additional regions inside the grid.  See the entry 
+for Sudoku on Wikipedia for an image of Hyper Sudoku.
+