Return random integer in range [a, b], including both end points.
        

No Document.

random() -> x in the interval [0, 1).

Choose a random item from range(start, stop[, step]).

This fixes the problem with randint() which includes the
endpoint; in Python this is usually not what you want.
Do not supply the 'int', 'default', and 'maxwidth' arguments.

Choose a random element from a non-empty sequence.

Get a random number in the range [a, b) or [a, b] depending on rounding.

x, random=random.random -> shuffle list x in place; return None.

Optional arg random is a 0-argument function returning a random
float in [0.0, 1.0); by default, the standard random.random.

Initialize internal state from hashable object.

None or no argument seeds from current time or from an operating
system specific randomness source if available.

If a is not None or an int or long, hash(a) is used instead.

Chooses k unique random elements from a population sequence.

Returns a new list containing elements from the population while
leaving the original population unchanged.  The resulting list is
in selection order so that all sub-slices will also be valid random
samples.  This allows raffle winners (the sample) to be partitioned
into grand prize and second place winners (the subslices).

Members of the population need not be hashable or unique.  If the
population contains repeats, then each occurrence is a possible(more...)

Exponential distribution.

lambd is 1.0 divided by the desired mean.  It should be
nonzero.  (The parameter would be called "lambda", but that is
a reserved word in Python.)  Returned values range from 0 to
positive infinity if lambd is positive, and from negative
infinity to 0 if lambd is negative.

Gaussian distribution.

mu is the mean, and sigma is the standard deviation.  This is
slightly faster than the normalvariate() function.

Not thread-safe without a lock around calls.

Normal distribution.

mu is the mean, and sigma is the standard deviation.

getrandbits(k) -> x.  Generates a long int with k random bits.

Alternate random number generator using sources provided
by the operating system (such as /dev/urandom on Unix or
CryptGenRandom on Windows).

 Not available on all systems (see os.urandom() for details).

No Document.

No Document.

Log normal distribution.

If you take the natural logarithm of this distribution, you'll get a
normal distribution with mean mu and standard deviation sigma.
mu can have any value, and sigma must be greater than zero.

Triangular distribution.

Continuous distribution bounded by given lower and upper limits,
and having a given mode value in-between.

http://en.wikipedia.org/wiki/Triangular_distribution

Pareto distribution.  alpha is the shape parameter.

Return internal state; can be passed to setstate() later.