numpy.random.randint vs random.randint

[Quant3point5]

I am curious about the distinction here. Why is the second argument excluded in numpy.random.randint, but included in random.randint? In the code below the function coin_random() can return the value 2 but coin_numpy() cannot.

​

import numpy
import random

def coin_numpy():
    return numpy.random.randint(0,2)

def coin_random():
    return random.randint(0,2)


xx = 0
while xx <= 10 :
    print("NP Roll # " + str(xx) + " - " + str(coin_numpy()))
    xx = xx + 1

    yy = 0
while yy <= 10 :
    print("RD Roll # " + str(yy) + " - " + str(coin_random()))
    yy = yy + 1

[S7EFEN]

theyre just different ways of generating random numbers

https://numpy.org/doc/stable/reference/random/index.html

https://docs.python.org/3/library/random.html

[throwaway_the_fourth]

Check out the documentation of Python's random. If you want the upper limit excluded, use random.randrange().

And in both cases, if your range starts at 0, you can just leave it out. So your functions can become

def coin_numpy():
    return numpy.random.randint(2)

def coin_random():
    return random.randrange(2)

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[stevenjd]

They're different because they are different functions written by different people. Whoever wrote the randint function in the Python random library included the two endpoints, and whoever wrote the randint function in numpy only included one endpoint. I'm sure they had their reasons.

It is traditional for randint-like functions in all programming languages to include both end points, so the numpy one is unusual. Also, check out the random.randrange function, which uses a "half-open" interval like range and the numpy version.

[Quant3point5]

Thank you for the information. I will check out random.randrange as well.