Python generates random function randomness

Source: Internet
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Random is a built-in (built-in) function that generates random numbers

Import module:



You can then invoke the function under the random module using dir (random) to see what functions are under the random module, with the following results:

1>>>dir (random)2['BPF','LOG4','Nv_magicconst','RECIP_BPF','Random','Sg_magicconst','Systemrandom','Twopi','_builtinmethodtype','_methodtype','_sequence3 ', '_set', '__all__', '__builtins__', '__cached__', '__doc__', '__file__', '__loader__', '__name__', '__package__', '__spec__', '_acos', '_bisect4 ', '_ceil', '_cos', '_e', '_exp', '_inst', '_itertools', '_log', '_pi', '_random', '_sha512', '_sin', '_sqrt', '_test', '_test_generator', '_urandom'  5,'_warn','betavariate','Choice','Choices','expovariate','gammavariate','Gauss','getrandbits','GetState','lognormvariate','normalvariate',   6 'paretovariate','Randint','Random','Randrange','Sample','seed','SetState','Shuffle','Triangular','Uniform','vonmisesvariate','Weibullvaria7Te'] 

The most commonly used functions are as follows:


1 random.randint (1,10)

The meaning of the statement is to produce a random number (integer int) of 1 to 10 (containing 1 and 10). (The parameter is an integer cannot be a floating-point number otherwise it will be an error)

1 # the statement is incorrect. Lower limit must be less than or equal to upper limit 



Generate a random floating-point number from 0 to 1, including 0 but not 1, that is, [0.0, 1.0].


1 random.uniform (A, B)

Generates a random floating-point number between A and B. Unlike Randint, however, A and B can be either integers or sizes.


1  Random.uniform (3.65,10.56)# can do this
1 random.uniform (10.56, 3.65)# You can do   the same



1 random.choice (seq)

Randomly selects an element from a sequence. Seq needs to be a sequence, such as a list, a tuple, a string.

1Random.choice ([1, 2, 3, 5, 8, 13])#List2   3Random.choice ('Hello')#string4   5Random.choice (['Hello',' World'])#string consisting of a list6   7Random.choice ((1, 2, 3))#Meta-group

is a viable use.


1 random.randrange (start, stop, step)

Generate a random integer from start to stop (not including stop), at intervals of step. Start, stop, step are all integers, and start<stop. Such as:

1  Random.randrange (0, 2)#  randomly generates an even number between 0-20



From the P sequence, a random fetch of k elements is generated, generating a new sequence. Sample does not change the original sequence.

This module is 666, and supports very specialized stochastic algorithms such as triangulation, β distribution, exponential distribution, gamma distribution, Gaussian distribution, and so on.


1 random.shuffle (x)  

Disrupts the order of elements in sequence x. Shuffle directly changes the original sequence. Such as:

1 Import Random   2 a=[1,2,3,4,5,6]  3random.shuffle (a)  4print(a

The results are as follows:

1 [5, 1, 3, 6, 4, 2]

Novice there may be some errors when using this function, as follows:

1 Import Random   2 a=[1,2,3,4,5,6]  3print(Random.shuffle (a))  

Using this method results in a none because Random.shuffle () is used to disrupt the list element, there is no return value, so print (Random.shuffle (a)) cannot be used to output the printing scrambling

After the sequence

Python generates random function randomness

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