On 07/18/2010 05:52 PM, Reid Kleckner wrote:

Usual disclaimer: python-dev is for the development *of* python, not *with*. See python-list, etc.

Moving to python-list. Please keep discussion there.

That said, def declares new functions or methods, so you can't put arbitrary expressions in there like type(f).__mul__ .

You can usually assign to things like that though, but in this case you run into trouble, as shown below:

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def func(): pass ... type(func) <class 'function'> def compose(f, g): ... return lambda x: f(g(x)) ... type(func).__mul__ = compose Traceback (most recent call last): File "<stdin>", line 1, in <module> TypeError: can't set attributes of built-in/extension type 'function'

As the interpreter says, it doesn't like people mucking with operator slots on built in types.

Finally, if you like coding in that very functional style, I'd recommend Haskell or other ML derived languages. Python doesn't support that programming style very well by choice.

Reid

On Sun, Jul 18, 2010 at 8:34 AM, Christopher Olah <christopherolah.co@gmail.com> wrote:

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Dear python-dev,

In mathematical notation, f*g = z->f(g(z)) and f^n = f*f*f... (n times). I often run into situations in python where such operators could result in cleaner code. Eventually, I decided to implement it myself and see how it worked in practice.

However, my intuitive implementation [1] doesn't seem to work. In particular, despite what it says in function's documentation, function does not seem to be in __builtin__. Furthermore, when I try to implement this through type(f) (where f is a function) I get invalid syntax errors.

I hope I haven't made some trivial error; I'm rather inexperienced as a pythonist.

Christopher Olah

[1] Sketch:

def __builtin__.function.__mul__(self, f): return lambda x: self(f(x))

def __builtin__.function.__pow__(self, n): return lambda x: reduce(lambda a,b: [f for i in range(n)]+[x])

As Reid explained, you can't just muck around with built-in types like that. However, you can "use a different type". If you're not familiar with Python decorators, look them up, and then have a look at this simple implementation of what you were looking for:

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class mfunc: ... def __init__(self, func): ... self.func = func ... self.__doc__ = func.__doc__ ... self.__name__ = func.__name__ ... def __call__(self, *args, **kwargs): ... return self.func(*args, **kwargs) ... def __mul__(self, f2): ... @mfunc ... def composite(*a, **kwa): ... return self.func(f2(*a, **kwa)) ... return composite ... def __pow__(self, n): ... if n < 1: ... raise ValueError(n) ... elif n == 1: ... return self.func ... else: ... return self * (self ** (n-1)) ... @mfunc ... def square(x): return x*x ... @mfunc ... def twice(x): return 2*x ... (square*twice)(1.5) 9.0 addthree = mfunc(lambda x: x+3) addfifteen = (addthree ** 5) addfifteen(0) 15