[Python-ideas] Inline Functions - idea

[Amber Yust]

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 at 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
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