Random numbers and sequences in Python
Everybody knows about random.randint(a, b)
in Python, which returns a ≤ n ≤ b:
random.randint(10, 99)
# 59
But the random
module has so much more to offer.
Like selecting a number from a range with a step:
random.randrange(10, 99, 3)
# 91
Or a random sequence element:
numbers = [7, 9, 13, 42, 64, 99]
random.choice(numbers)
# 42
Or multiple elements:
numbers = range(99, 10, -1)
random.choices(numbers, k=3)
# [32, 62, 76]
How about choosing some elements more often than others? Sure:
numbers = [7, 9, 13, 42, 64, 99]
weights = [10, 1, 1, 1, 1, 1]
random.choices(numbers, weights, k=3)
# [42, 13, 7]
random.choices(numbers, weights, k=3)
# [7, 7, 7]
random.choices(numbers, weights, k=3)
# [13, 7, 7]
Wanna see a sample without repetitions? No problem:
numbers = [7, 9, 13, 42, 64, 99]
random.sample(numbers, k=3)
# [42, 99, 7]
Or even shuffle the whole sequence:
numbers = [1, 2, 3, 4, 5]
random.shuffle(numbers)
# [3, 2, 1, 5, 4]
There are also countless real-valued distributions like uniform()
, gauss()
, expovariate()
, paretovariate()
and many more. Not gonna get into the specifics now — see for yourself if your are a statistics fan.
Last but not least. When testing, seed the generator with a constant so that it gives reproducible results:
random.seed(42)
On the contrary, use seed()
without arguments in production. Python will then use the sources of randomness provided by the operating system.
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