return next(genexcept stopiterationreturn none if __name__ ="__main__"test_csp(dfs_solve #trydfs_solve_all(csp dfs_solve_all(csp dfs_solve_all(crossword dfs_solve_all(crossword dwarningmay take *verylong timeexercise instead of testing all constraints at every nodechange it so each constraint is only tested when all of it variables are assigned given an elimination orderingit is possible to determine when each constraint needs to be tested implement this hintcreate parallel list of sets of constraintswhere at each position in the listthe constraints at position can be evaluated when the variable at position has been assigned exercise estimate how long dfs_solve_all(crossword dwill take on your computer to do thisreduce the number of variables that need to be assignedso that the simplifies problem can be solved in reasonable time (between second and secondsthis can be done by reducing the number of variables in var_orderas the program only splits on these how much more time will it take if the number of variables is increased by (try it!then extrapolate to all of the variables see section for how to time your code would making the code times faster or using computer times faster help converting csps to search problems to run the demoin folder "aipython"load "cspsearch py"and copy and paste the example queries at the bottom of that file the next solver constructs search space that can be solved using the search methods of the previous this takes in csp problem and an optional variable orderingwhich is list of the variables in the csp in this search spacea node is variable value dictionary which does not violate any constraints (so that dictionaries that violate any conmtratints are not addedan arc corresponds to an assignment of value to the next variable this assumes static orderingthe next variable chosen to split does not depend on the context if no variable ordering is giventhis makes no attempt to choose good ordering version june