This module implements pseudo-random number generators for various distributions.
Initialize the random number generator.
If a is omitted or
None, the current system time is used. If randomness sources are provided by the operating system, they are used instead of the system time (see the
os.urandom()function for details on availability).
If a is an int, it is used directly.
Returns a Python integer with k random bits. This method is supplied with the MersenneTwister generator and some other generators may also provide it as an optional part of the API. When available,
randrange()to handle arbitrarily large ranges.
randrange(start, stop[, step])
Return a randomly selected element from
range(start, stop, step). This is equivalent to
choice(range(start, stop, step)), but doesn’t actually build a range object.
The positional argument pattern matches that of
range(). Keyword arguments should not be used because the function may use them in unexpected ways.
>>> random.randrange(10) # Integer from 0 to 9 7 >>> random.randrange(0, 101, 2) # Even integer from 0 to 100 26
Return a random integer N such that a <= N <= b. Alias for
Return a random element from the non-empty sequence seq. If seq is empty, raises IndexError.
>>> random.choice('abcdefghij') # Single random element 'c'
Return the next random floating point number in the range
>>> random.random() # Random float x, 0.0 <= x < 1.0 0.374448
Return a random floating point number N such that a <= N <= b for a <= b and b <= N <= a for b < a.
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(1, 10) # Random float x, 1.0 <= x < 10.0 1.180014