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  2. Random.random() generates its output in the traditional way: pick a random integer in [0, 2**53) and divide by 2**53 (53 is the number of bits in a double). So random() returns 2**53 equiprobable doubles, and you can divide this evenly into N outputs only if N is a power of 2.

  3. 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 ...

  4. Many times looking in the library can be more helpful. Getting the documentation for the random module would have worked. It does take some time to know where to look, but for anything involving "random" check the random module first. –

  5. For completness sake: If you use numpy, you can also call the uniform method on an instance of random number generator (now the preferred way in numpy when dealing with random numbers). import numpy as np seed = 42 low = 0.12 high = 3.45 rng = np.random.default_rng(seed) rng.uniform(low, high)

  6. I have a file with some probabilities for different values e.g.: 1 0.1 2 0.05 3 0.05 4 0.2 5 0.4 6 0.2 I would like to generate random numbers using this distribution. Does an existing module that

  7. @wjandrea yeah I'm aware that Python 3 range produces a generator. Back when I posted that comment if you tried sample = random.sample(range(1000000000000000000), 10) you could watch the memory of the process grow as it tried to materialize the range before extracting a sample.

  8. And I would like to pick a random number within that range. Again, that range is defined as 100:100:20000. Furthermore, by saying 'within that range', I don't mean randomly picking a number from 100->20000, such as 105. I mean randomly choosing a number from the list of numbers available, and that list is defined as 100:100:20000.

  9. random.random() Return the next random floating point number in the range [0.0, 1.0). But if your inclusion of the numpy tag is intentional, you can generate many random floats in that range with one call using a np.random function.

  10. In Python how can I choose two or more random numbers from a given list,such that the numbers are chosen in the same sequence they are arranged in the list they are chosen from?It seems random.choice selects only one number from the list per iteration and as stated earlier random.sample does not give satisfactory answers.for example:

  11. Generate random number in range excluding some numbers

    stackoverflow.com/questions/42999093

    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).