On 2023-03-20 15:21, Edmondo Giovannozzi wrote:
> def sum1():
> s = 0
> for i in range(1000000):
> s += i
> return s
>
> def sum2():
> return sum(range(1000000))
Here you already have the numbers you want to add.
Actually using numpy you'll be much faster in this case:
§ import numpy as np
§ def sum3():
§ return np.arange(1_000_000, dtype=np.int64).sum()
On my computer sum1 takes 44 ms, while the numpy version just 2.6 ms
One problem is that sum2 gives the wrong result. This is why I used np.arange
with dtype=np.int64.
sum2 evidently doesn't uses the python "big integers" e restrict the result to
32 bits.
On my computer they all give the same result, as I'd expect.
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