We also do so with the column and two diagonals. First, we place a queen somewhere on the first row and we mark the row it occupies as menaced. The basic algorithm to solve the Eight queens puzzle is a relatively simple recursive algorithm.

Now, to make things more interesting, we might be interested in enumerating all solutions (and, for the time being, neglecting to check if a solution is a rotated or mirrored version of another solution). Using a real chessboard and pawns in lieu of queens, you can easily find a solution in a few seconds. So this means that no queen is on the same row, column, or diagonal as another queen. By “checking”, we mean that if the other queen was of the opposing camp, you could capture it if it were your turn to play. The eight queens puzzle consist in finding a way to place 8 queens on a 8×8 chessboard so that none of the queen checks another queen.

I implemented the same program in C++, Python, and Bash, and got help from friends for the C# and Java versions 2. This puzzle is most easily solved using, as Dijkstra did, a depth-first backtracking program, using bitmaps to test rapidly whether or not a square is free of attack 1. So I have decided to investigate by comparing the implementation of a simple, compute-bound problem, the eight queens puzzle generalized to any board dimensions. But it was unclear to me just how slow Python was compared to other languages. But Python is slow compared to other programming languages. It is simple, to the point, and has several functional-like constructs that I am already familiar with.

Python is a programming language that I learnt somewhat recently (something like 2, 3 years ago) and that I like very much.

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