I find your example code far less readable than just writing out the loops in the appropriate functions, especially for matrix_multiply. On Mon Feb 10 2014 at 10:51:35 AM, Alex Rodrigues <lemiant@hotmail.com> wrote:

Over the last few days I've been considering a lot of what we talked about regarding Python scoping and inline functions. Today I found a further use case for inline functions (one which is a fair bit harder to replicate using standard techniques). I was working on writing a basic linear algebra calculator for school and one of the annoying things about doing it is that every time you want to do an element-wise operation on the matrix (which is a list of lists) you have to nest what is essentially one line of code inside a pair of for loops. Below I've done three basic linear algebra functions which are written as if there was a builtin "inline()" which transformed a standard function into an inline function and also assuming that python had more powerful lambdas. I feel that these represent a good use case, because the inline function serves to make the code both shorter and clearer.

import copy

@inline def element_wise(func): func = inline(func) for i, row in enumerate(matrix): result.append([0]*len(row)) for j, el in enumerate(row): func()

def is_symmetric(matrix): element_wise(lambda: if matrix[i][j] != matrix[j][i]: return False) return True

def matrix_add(matrix, matrix2): result = copy.deepcopy(matrix) element_wise(lambda: result[i][j] = matrix[i][j] + matrix2[i][j]) return result

def matrix_multiply(matrix, matrix2): result = copy.deepcopy(matrix) element_wise(lambda: result[i][j] = sum([a*b for a,b in zip(matrix[i], [r[j] for r in matrix2])])) return result _______________________________________________ Python-ideas mailing list Python-ideas@python.org https://mail.python.org/mailman/listinfo/python-ideas Code of Conduct: http://python.org/psf/codeofconduct/

On Feb 10, 2014, at 10:49, Alex Rodrigues <lemiant@hotmail.com> wrote: The only reason you think you need more powerful lambdas and inline functions is that you're ignoring features Python already has. For example;

def is_symmetric(matrix): element_wise(lambda: if matrix[i][j] != matrix[j][i]: return False) return True

This requires full statements as lambdas, and inline functions, and some kind of "multi-level return", where the implicit lambda return is level -1 so an explicit one returns from the outer (dynamic) scope, right? But element_wise is just a genexpr in disguise. And with the builtin all function you don't need early return. And that early return was the only reason your if needed to be a statement. So: return all(matrix[i][j] == matrix[j][i] for i, j in element_wise(matrix)) And this element_wise isn't anything magic, it's just product(range(len(matrix)), repeat=2).