4 ms·

The author points to this line as the main culprit for self-hell: self.minimum, self.maximum = min(self.minimum, self.maximum), max(self.minimum, self.maximu

The author points to this line as the main culprit for self-hell: self.minimum, self.maximum = min(self.minimum, self.maximum), max(self.minimum, self.maximum)` This line is needed to 'defensively protect the input'), i.e. try to compensate when minimum and maximum arrive out of order. Firstly, I can't understand exactly why this defensive protection is not done before assigning the attributes, i.e. simply: # not too hellish, more readable on two lines self.minimum = min(minimum, maximum) self.maximum = max(minimum, maximum) Secondly, I'm not very up on my Python Zen, but I think this naming of arguments followed by defensive protection isn't particularly Pythonic anyway. How about something like this? class Window(object): def __init__(self, x1, x2): # pass your dimensions in any order self.minimum = min(x1, x2) self.maximum = max(x1, x2) def __call__(self, x): return self.minimum <= x <= self.maximum

bkeroack 12y ago
The Pythonic solution is named parameters: def __init__(self, min=x, max=y):
- iterati 12y ago
  Any parameter/argument is named in Python. What you're providing are default values for arguments.
  - bkeroack 12y ago
    Of course you are correct. This is why I shouldn't post shortly after waking up.
iterati 12y ago
This would also work: def make_window(min, max): min, max = sorted([min, max]) return lambda val: min <= val <= max
- parennoob 12y ago
  Simple min and max on my computer reliably seems to take less time than the sorted solution, and also makes more sense to read. This is what I would intuitively expect anyway with the overhead of making the array. >>> timeit.timeit('x=4; y=3; x, y = sorted([x, y])') 0.49517297744750977 >>> timeit.timeit('x=4; y=3; x = min(x,y); y = max(x, y)') 0.2774021625518799
andreasvc 12y ago
The solution of adding the protection first is mentioned but there will be other situations later in which the use of a lot of self cannot be avoided, so it doesn't solve the general problem, if you call it that. What is being called "defensive" I would rather call "permissive". If at all possible, I would prefer raising a ValueError if x1 >= x2.

bkeroack 12y ago

The Pythonic solution is named parameters: def __init__(self, min=x, max=y):

iterati 12y ago
Any parameter/argument is named in Python. What you're providing are default values for arguments.
- bkeroack 12y ago
  Of course you are correct. This is why I shouldn't post shortly after waking up.

iterati 12y ago

This would also work: def make_window(min, max): min, max = sorted([min, max]) return lambda val: min <= val <= max

parennoob 12y ago
Simple min and max on my computer reliably seems to take less time than the sorted solution, and also makes more sense to read. This is what I would intuitively expect anyway with the overhead of making the array. >>> timeit.timeit('x=4; y=3; x, y = sorted([x, y])') 0.49517297744750977 >>> timeit.timeit('x=4; y=3; x = min(x,y); y = max(x, y)') 0.2774021625518799

andreasvc 12y ago

The solution of adding the protection first is mentioned but there will be other situations later in which the use of a lot of self cannot be avoided, so it doesn't solve the general problem, if you call it that. What is being called "defensive" I would rather call "permissive". If at all possible, I would prefer raising a ValueError if x1 >= x2.