Oct 22, 2010 · 2 If we look at their source implementations, random.randrange() (and random.randint() because it is the former's syntactic sugar) use a while-loop to generate a pseudo-random number via _randbelow method while random.choices() calls random() once and uses it to index the population. So if a lot of pseudo-random numbers need to be generated ...

@RajeshSwarnkar random.random() * 2*math.pi, as the doc says the random function "Return[s] the next random floating point number in the range 0.0 <= X < 1.0" – Magnus Teekivi Commented Feb 15, 2023 at 9:23

Jul 4, 2021 · So to get a random 3-digit number: from random import randint, randrange randint(100, 999) # randint is inclusive at both ends randrange(100, 1000) # randrange is exclusive at the stop * Assuming you really meant three digits, rather than "up to three digits".

Mar 24, 2017 · To avoid wasting time looping for useful random number, I suggest you create a list from 0 to 9 using for loop [0,1,....9,]. then you shuffle this list once randomly. [ 4,8,0,....1] to get a random number, just "poll" the first number from this list each time you want a random number (which will not exist in the list the next time read).

Nov 20, 2008 · NumPy solution: numpy.random.choice. For this question, it works the same as the accepted answer (import random; random.choice()), but I added it because the programmer may have imported NumPy already (like me)

Feb 2, 2017 · I am a bit confused about how the random.random() function works in python. The docs say that it 'Return the next random floating point number in the range [0.0, 1.0)'. I understand that pseudo-random number generators work by performing some operation on a value. Generally this value is the previous number generated by the generator.

Mar 18, 2012 · actually my answer has similar complexity as other top voted answers and is faster because it uses numpy. other, top-voted methods use random.shuffle, which uses Mersenne Twister, qhich is much slower than algos offered by numpy (and probably jax). numpy and jax allow for other random number generation algorithms. jax also allows jit-compiling ...

Oct 30, 2017 · This is random, so running it again would result in a different sequence like [1 1 0], [0 1 0], or maybe even [1 1 1]. Although you cannot get the same number of 1s and 0s in three runs, on average you would get the same number. Technical explanation. Numpy implements random number generation in C.

Oct 19, 2017 · The fastest way to generate random numbers if you're going to be doing lots of them is by using numpy: In [1]: import numpy as np In [2]: import random In [3]: %timeit [random.choice([-1,1]) for i in range(100000)] 10 loops, best of 3: 88.9 ms per loop In [4]: %timeit [(-1)**random.randrange(2) for i in range(100000)] 10 loops, best of 3: 110 ms per loop In [5]: …

Feb 12, 2012 · NOTE: You should bear the following warning in mind when using random.shuffle() (taken from the docs: Note that for even rather small len(x), the total number of permutations of x is larger than the period of most random number generators; this implies that most permutations of a long sequence can never be generated.