I am looking for the best way (fast and elegant) to get a random boolean in python (flip a coin).
For the moment I am using random.randint(0, 1)
or random.getrandbits(1)
.
Are there better choices that I am not aware of?
In order to generate Random boolean in Java, we use the nextBoolean() method of the java. util. Random class. This returns the next random boolean value from the random generator sequence.
The random() method returns a random floating number between 0 and 1.
Use the random. sample() function when you want to choose multiple random items from a list without repetition or duplicates. There is a difference between choice() and choices() . The choices() was added in Python 3.6 to choose n elements from the list randomly, but this function can repeat items.
Adam's answer is quite fast, but I found that random.getrandbits(1)
to be quite a lot faster. If you really want a boolean instead of a long then
bool(random.getrandbits(1))
is still about twice as fast as random.choice([True, False])
Both solutions need to import random
If utmost speed isn't to priority then random.choice
definitely reads better.
Note that random.choice()
is slower than just choice()
(after from random import choice
) due to the attribute lookup.
$ python3 --version Python 3.9.7 $ python3 -m timeit -s "from random import choice" "choice([True, False])" 1000000 loops, best of 5: 376 nsec per loop $ python3 -m timeit -s "from random import choice" "choice((True, False))" 1000000 loops, best of 5: 352 nsec per loop $ python3 -m timeit -s "from random import getrandbits" "getrandbits(1)" 10000000 loops, best of 5: 33.7 nsec per loop $ python3 -m timeit -s "from random import getrandbits" "bool(getrandbits(1))" 5000000 loops, best of 5: 89.5 nsec per loop $ python3 -m timeit -s "from random import getrandbits" "not getrandbits(1)" 5000000 loops, best of 5: 46.3 nsec per loop $ python3 -m timeit -s "from random import random" "random() < 0.5" 5000000 loops, best of 5: 46.4 nsec per loop
import random random.choice([True, False])
would also work.
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