> solve(x**2 == 1/2)
pip install funcoperators
>>> solve(x ** 2 |Equals| 1/2)
<<< Equals = infix(Eq)
<<< from sympy import Eq
Le mer. 19 mai 2021 à 08:40, Martin Teichmann <martin.teichm...@gmail.com>
a écrit :
> Hi list,
>
> as you might have noticed, I am trying to improve the syntax and semantics
> for symbolic math in Python. Until now, I have to say, my ideas were not
> that well received, but I learned from the discussion and maybe this time I
> come up with something people like.
>
> To frame the problem, let us try to solve the equation x ** 2 == 1/2
> using sympy:
>
> >>> from sympy import Eq, solve, symbols, S
> >>> x = symbols("x")
> >>> solve(Eq(x**2, S(1)/2))
> [-sqrt(2)/2, sqrt(2)/2]
>
> that worked well, but actually we would like to write the last line simply
> as
>
> >>> solve(x**2 == 1/2)
>
> as you might notice, this is fully legal Python syntax. Unfortunately the
> semantics is such that sympy has no way to determine what is actually going
> on, this is why they invented all those helper functions shown above.
>
> My idea is now to start at the line above, "x = symbols('x')". I propose a
> new syntax, "symbolic x", which tells the parser that x is a symbolic
> variable, and expressions should not be executed, but handed over as such
> to the calling functions. To stay with the example, the code would look
> like this (this is fake, I did not prototype this yet):
>
> >>> from sympy import solve
> >>> symbolic x
> >>> solve(x**2 == 1/2)
> [-sqrt(2)/2, sqrt(2)/2]
>
> Now to the details. The scope that "symbolic" acts on should be the same
> as the scope of "global". Note that "symbolic x" is currently illegal
> syntax, so we would not even need to make "symbolic" a keyword.
>
> Expressions that contain a symbolic variable are not executed, but instead
> the expression should be given to the function as a tuple, so in the
> example above, solve would be given
> ('==', ('**', ('x', 2)), ('/', 1, 2)). If that looks like LISP to you,
> then you are not completely wrong. The boundaries of expressions are
> function calls, assignments, getitems and getattrs, as they can be
> overloaded much easier by other means. To give an example with gory details
> (again, this is fake):
>
> >>> symbolic x
> >>> d = {"a" : 5}
> >>> c = 7 # not symbolic!
> >>> print(c * x + d["a"])
> ('+', ('*', 7, 'x'), 5)
>
> Maybe we would want to have a new class "expressiontuple" which simply
> acts as a pretty-printer, then the last lines would become
>
> >>> print(x + d["a"])
> 7 * x + 5
>
> What sympy does with this tuple would be fully at its discretion.
>
> I think that other libraries could also benefit from this proposal. As an
> example, in a numerics library (numpy? scipy?) one could improve numerical
> integration as in
>
> >>> symbolic x
> >>> integrate(sin(x), x, 0, pi)
>
> then the integrator could even compile the expression to machine code for
> faster integration.
>
> numpy could also compile expressions to machine code, making it even
> faster than it is now, as in
>
> >>> symbolic x
> >>> f = compile(5 * x + 7 * y, (x, y))
> >>> f(matrix_a, matrix_b)
>
> Let's see how well this proposal fares.
>
> Cheers
>
> Martin
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