Generate Random Numbers (int and float) in Python

In Python, you can generate pseudo-random numbers (int and float) with random(), randrange(), randint(), uniform(), etc., from the random module.

• random — Generate pseudo-random numbers — Python 3.11.3 documentation

The random module is included in the standard library, so no additional installation is required.

See the following articles on how to sample or shuffle elements in a list randomly.

• Random sample from a list in Python (random.choice, sample, choices)
• Shuffle a list, string, tuple in Python (random.shuffle, sample)

See the following article on random number generation with NumPy.

• NumPy: Generate random numbers with np.random

Generate random floating point numbers (float)

random.random(): 0.0 <= float < 1.0

random.random() generates a random floating point number (float) within the range of 0.0 <= n < 1.0.

• random.random() — Generate pseudo-random numbers — Python 3.11.3 documentation

import random

print(random.random())
# 0.4496839011176701

random.uniform(): float in a given range

random.uniform(a, b) generates a random floating point number (float) in the range a <= n <= b or b <= n <= a.

• random.uniform() — Generate pseudo-random numbers — Python 3.11.3 documentation

import random

print(random.uniform(100, 200))
# 175.26585048238275

The two arguments can be in any order, regardless of which is larger or smaller. If they are equal, only that value is returned.

print(random.uniform(100, -100))
# -27.82338731501028

print(random.uniform(100, 100))
# 100.0

The arguments can also be specified as float values.

print(random.uniform(1.234, 5.637))
# 2.606743596829249

As documented, whether the value of b is included in the range depends on the rounding equation a + (b-a) * random.random().

The end-point value b may or may not be included in the range depending on floating-point rounding in the equation a + (b-a) * random(). random.uniform() — Generate pseudo-random numbers — Python 3.9.7 documentation

Generate random numbers for various distributions (Gaussian, gamma, etc.)

In addition to the uniform distribution provided by random.random() and random.uniform(), the random module also offers functions for generating random numbers from various distributions.

• Beta distribution: random.betavariate()
• Exponential distribution: random.expovariate()
• Gamma distribution: random.gammavariate()
• Gaussian distribution: random.gauss()
• Log normal distribution: random.lognormvariate()
• Normal distribution: random.normalvariate()
• von Mises distribution: random.vonmisesvariate()
• Pareto distribution: random.paretovariate()
• Weibull distribution: random.weibullvariate()

See the official documentation for more information on each distribution.

• random — Generate pseudo-random numbers - Real-valued distributions — Python 3.11.3 documentation

Generate random integers (int)

random.randrange(): int in a given range and step

random.randrange(start, stop, step) returns a random integer (int) within the range(start, stop, step).

• random.randrange() — Generate pseudo-random numbers — Python 3.11.3 documentation

Similar to range(), start and step can be omitted. If omitted, the default values are start=0 and step=1.

• How to use range() in Python

import random

print(list(range(10)))
# [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]

print(random.randrange(10))
# 5

You can generate random integers that are either even or odd, or multiples of any integer. For example, if start is even and step is set to 2, only even integers within the range will be randomly generated.

print(list(range(10, 20, 2)))
# [10, 12, 14, 16, 18]

print(random.randrange(10, 20, 2))
# 18

random.randint(): int in a given range

random.randint(a, b) returns a random integer (int) in the range a <= n <= b. It is equivalent to random.randrange(a, b + 1). Note that the value of b is included in the range, so it may be generated.

• random.randint() — Generate pseudo-random numbers — Python 3.11.3 documentation

print(random.randint(50, 100))
# print(random.randrange(50, 101))
# 74

Generate a list of random numbers (int and float)

List of random floating point numbers

To generate a list of random floating point numbers, you can use functions like random.random(), random.uniform(), etc., in combination with list comprehensions.

import random

print([random.random() for i in range(5)])
# [0.5518201298350598, 0.3476911314933616, 0.8463426180468342, 0.8949046353303931, 0.40822657702632625]

See the following article for more information on list comprehensions.

• List comprehensions in Python

List of random integers

When generating a list of random integers using random.randrange() or random.randint() with list comprehensions, it may contain duplicate values.

print([random.randint(0, 10) for i in range(5)])
# [8, 5, 7, 10, 7]

If you want to make a list of random integers without duplicates, you can use random.sample() to select elements from a range().

print(random.sample(range(10), k=5))
# [6, 4, 3, 7, 5]

print(random.sample(range(100, 200, 10), k=5))
# [130, 190, 140, 150, 170]

See the following article for more information about random.sample().

• Random sample from a list in Python (random.choice, sample, choices)

random.seed(): Initialize the random number generator

You can fix the random seed and initialize the random number generator with random.seed().

• random.seed() — Generate pseudo-random numbers — Python 3.11.3 documentation

After initializing with the same seed, the same sequence of random numbers will be generated.

random.seed(0)
print(random.random())
# 0.8444218515250481

print(random.random())
# 0.7579544029403025

random.seed(0)
print(random.random())
# 0.8444218515250481

print(random.random())
# 0.7579544029403025