Python module module of Random

random - generating a pseudo-random number, the module for the distribution of a variety of pseudo-random number generator. Let's look at a few common modules introduce random function:

First, the method for integer:

random.randrange (GFC)

random.randrange (start, stop [, step
]) is equivalent to the choice (range (start, stop, step)), but does not actually create an object range.

>>> Import Random
 >>> Print (random.randrange (. 4))          # returns a random integer of 0 to 3 
1 
>>> Print (random.randrange (1,. 9))        # returns a random integer of 1 to 8 
8 
> >> Print (random.randrange (1,. 11, 2))     # returns a random odd number of 1 to 10 
3

random.randint (a, b)
returns a random integer N, a <= N <= b, is equivalent to randrange (a, b + 1) .

>>> Print (the random.randint (1, 10))         # Returns [1, 10] is a random integer 
. 8 
>>> Print (the random.randint (-10, -1))       # Returns [-10, -1] random integer, can not be written the random.randint (-1, -10) 
-5

Second, a method for the sequence:
The random.choice (SEQ)
returns a random element from a non-empty sequence, if the sequence is empty, the trigger IndexError.

>>> Print (The random.choice ( ' BHasdgiHUI1234 ' ))    # returns a character 
the I
 >>> Print (The random.choice ([ ' Apple ' , ' Peach ' , ' PEAR ' ]))   # Returns a list of a random element 
PEAR
 >>> Print (the random.choice (( ' Bob ' , ' Jhon ' , ' of Micheal ' )))　　# tuple returns a random element 
Jhon

random.choices (population, weight = None,
*, cum_weight = None, k = 1) random k elements taken from population alternative sequence composition list, the list is returned. weight is relative weights sequence, cum_weight cumulative weight, while developing and cumulative weight weight weight cum_weight, will produce a type error.

>>> print(random.choices(['red', 'yellow','green', 'blue', 'black', 'pink', 'purple', 'white'], k=4))　　
['red', 'red', 'purple', 'black']
>>> print(random.choices(['apple', 'peach', 'pear'], [1, 2, 3], k=4))
['pear', 'pear', 'pear', 'peach']
>>> print(random.choices(['apple', 'peach', 'pear'], [6, 12, 2], k=4))
['peach', 'peach', 'pear', 'pear']

random.shuffle (x [, random])
rearranged sequence (shuffle)

= SEQ >>> [ ' red1 ' , ' yellow2 ' , ' Blue3 ' , ' green4 ' ]
 >>> random.shuffle (SEQ)　　　　# list reordering
 >>> Print (SEQ) 
[ ' red1 ' , ' Blue3 ' , ' green4 ' , ' yellow2 ' ]

random.sample (population, k)
returns a random number K from the elements will not be repeated in a sequence population consisting of the new queue. Irreplaceable for random sampling. It returns a new list does not destroy the original list. If the new queue length k greater than the length of the original population of the queue, an error is thrown ValueError.

>>> Print (random.sample ([ ' A ' , ' B ' , ' C ' , ' D ' , ' E ' , ' . 1 ' , ' 2 ' , ' . 3 ' ], 2 ))　　# random list extracting two elements of the new list of 
[ ' D ' , ' B ' ]
 >>> Print ( '' .join (random.sample ( "ahoiNUAI483*4"4 )))　　
UohI

Third, the true value distribution:

random.random ()
returns a random floating point numbers, the range [0, 1)

>>> print(random.random())
0.5867129667371662

random.uniform (a, b)
returns a random floating point between a and b, if a> b, the floating-point between b and a is returned. a and b are likely to appear in the results.

>>> print(random.uniform(1, 10))
5.961863773592117
>>> print(random.uniform(2,6))
3.2723769810535543