A new take on this question would involve the use of Faker which you can install easily with pip.
from faker import Factory
#----------------------------------------------------------------------
def create_values(fake):
""""""
print fake.boolean(chance_of_getting_true=50) # True
print fake.random_int(min=0, max=1) # 1
if __name__ == "__main__":
fake = Factory.create()
create_values(fake)
I was curious as to how the speed of the numpy answer performed against the other answers since this was left out of the comparisons. To generate one random bool this is much slower but if you wanted to generate many then this becomes much faster:
$ python -m timeit -s "from random import random" "random() < 0.5"
10000000 loops, best of 3: 0.0906 usec per loop
$ python -m timeit -s "import numpy as np" "np.random.randint(2, size=1)"
100000 loops, best of 3: 4.65 usec per loop
$ python -m timeit -s "from random import random" "test = [random() < 0.5 for i in range(1000000)]"
10 loops, best of 3: 118 msec per loop
$ python -m timeit -s "import numpy as np" "test = np.random.randint(2, size=1000000)"
100 loops, best of 3: 6.31 msec per loop
u could try this it produces randomly generated array of true and false :
a=[bool(i) for i in np.array(np.random.randint(0,2,10))]
out: [True, True, True, True, True, False, True, False, True, False]
random.choice([True, False])
would also work.
You could use the Faker library, it's mainly used for testing, but is capable of providing a variety of fake data.
Install: https://pypi.org/project/Faker/
>>> from faker import Faker
>>> fake = Faker()
>>> fake.pybool()
True
If you want to generate a number of random booleans you could use numpy's random module. From the documentation
np.random.randint(2, size=10)
will return 10 random uniform integers in the open interval [0,2). The size keyword specifies the number of values to generate.
I like
np.random.rand() > .5
Found a faster method:
$ python -m timeit -s "from random import getrandbits" "not getrandbits(1)"
10000000 loops, best of 3: 0.222 usec per loop
$ python -m timeit -s "from random import random" "True if random() > 0.5 else False"
10000000 loops, best of 3: 0.0786 usec per loop
$ python -m timeit -s "from random import random" "random() > 0.5"
10000000 loops, best of 3: 0.0579 usec per loop
Source: Stackoverflow.com