Python__random Library Basic Introduction

The random library is a Python standard library that uses stochastic numbers

From the perspective of probability, random numbers are randomly generated data (such as coin toss), but it is impossible for a computer to produce random values, and the true random number is a definite value produced under certain conditions, but these conditions are not understood or beyond our comprehension. A computer does not produce a true random number, so a pseudo-random number is called a random number.

Pseudo-random number: (pseudo) random sequence elements generated by using the Mason rotation algorithm in a computer

The library for generating pseudo-random numbers in Python is random

Because it is a standard library, only import random is required when using

The random library contains two types of functions, a total of 8 common

--Basic random function: seed (), random ()

--Extended Random function: Randint (), Getrandbits (), Uniform (), Randrange (), Choice (), Shuffle ()

Basic Random number

In Python, random numbers are generated using random number seeds (as long as the seed is the same, the resulting random sequence, regardless of the relationship between the number and number is deterministic, so the random number seed determines the generation of the random sequence)

Random sequence of the random number seed Mason rotation algorithm

10 0.5714025946899135

Each number in a random sequence is a random number.

Basic random functions

Function	Describe
Seed (A=none)	Initializes the given random number seed, tacitly considers the current system time >>>random.seed (#产生种子10对应的序列)
Random ()	Generates a random decimal between [0.0,1.0] >>>random.random () 0.5714025946899135 #随机数产生与种子有关, if the seed is 1 Oh, the first number must be this one

The benefit of using a random number seed is a program that can re-existing random numbers

Extended Random number function

In the random library, the most basic is the seed and the random function, but the function is relatively single, resulting in 6 extended random number function

Extended Random number function

Function	Describe
Randint (A, B)	Generates an integer between [a, b] >>>random.randint (10,100)
Randrange (M,n[,k])	Generates a random integer with a K-step between [M,n] >>>random.randrange (10,100,10)
Getrandbits (k)	Generate a random integer with K-specific features >>>random.getrandbits (16) 37885
Uniform (A, B)	Generates a random decimal between [a, b] >>>random.uniform (10,100) 16.848041210321334
Choice (seq) Sequence correlation	Randomly select an element from the sequence >>>random.choice ([1, 2, 3, 4, 5, 6, 7, 8, 9]) 8
Shuffle (SEQ) Sequence correlation	Randomly arranges elements in a sequence seq to return scrambled sequences >>>s=[1, 2, 3, 4, 5, 6, 7, 8, 9]; Random.shuffle (s); Print (s) [9, 4, 6, 3, 5, 2, 8, 7, 1]

Key points for using random number functions:

--Ability to generate "OK" pseudo-random number seed with random number seed, random function to generate stochastic number

--ability to generate random integers

--ability to randomly manipulate sequence types

Python__random Library Basic Introduction