How to generate 100million mobile phone numbers? Python has 22 methods to generate random numbers, and the random function is too strong

Hello everyone , Here is Python Programmer Wanfeng .

Case analysis

Recently I saw a on the Internet python The interview topic of ： How to use Python Generate 1 Million cell phone numbers ？

When I first saw it, I thought , This is not easy ？ direct random.randint(1,999999999999) Just a matter of .

But I found the mistake immediately ： This is the generation 1-99999999 Random number between , May be 1, It could be 666.

But the phone number is 11 Bit , And before 3 Bit has only the specified number segment , such as 135、136. direct random.randint(1,999999999999) This is not qualified .

So how to generate ？ So here's the code ：

import random
def create_phone_num(num):
all_phone_nums = set() # Store the generated phone number
while True: # because set It will automatically go heavy , So the loop generates phone numbers , Until it's equal to num Number stop
start = random.choice(['135', '136', '137']) # Before storage 3 Number segment of bit , Choose one at random
end = ''.join(random.sample(string.digits, 8)) # After random generation 8 Digit number
all_phone_nums.add(f'{start}{end}') # Before splicing 3 Position and back 8 position
if len(all_phone_nums) >= num: # If the number of numbers equals num, Then stop
break
phone_num(10000 * 10000)


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After writing the code this time, I found , original Python Of random There are so many easy-to-use methods of generating random numbers .

I sorted them all out , Today we will learn together ~

If there are omissions or errors , Welcome to give more advice ~

Which file generates random numbers ？

In the first line of the code above ：import random, We imported random This standard library .

This library has only one file ：random.py, The structure of this document is mainly divided into 3 individual part （ As shown in the figure below ）, Their functions are ：

• 2 Major classes ：Random(_random.Random) and SystemRandom(Random)
  • Among them, we use the most Random()
• Yes 2 Four test methods ：_test_generator(n, func, args) and _test(N=2000)
  • We can't use this part
• The function we call ： The use method is as the code above random.choice、random.sample, Specific usage , We will explain in detail next .
  

random What random number methods are provided ？

Next, we will focus on as python Users of , What will we use random The random number method of , As mentioned above random.py Page 2 of the document 3 part .

As shown in the code below ,random The methods provided are as follows 22 individual , It is mainly divided into 2 class ：

• Ordinary users Common methods , Altogether 12 individual ;
• Scientific Computing Common methods , Altogether 10 individual .

For ordinary users 12 How to use a random number method ？

For the above 22 A random number method , Here I will focus on the one commonly used by ordinary users 12 A way .

As for the latter 10 A method for scientific calculation , Because it's really profound , I won't waste my time here , Interested students , You can go directly to the math book ：《 probability theory 》.

1. random.seed & random.getstate & random.setstate

Put this 3 Put them together and say , Because random In essence, it generates pseudo-random numbers , And this 3 A function , It well reflects the characteristics of pseudo-random numbers

Code example :seed

# Appoint seed after , The generated random numbers are the same 
random.seed(1)
print(' random number 1：', random.random())
random.seed(1)
print(' random number 2：', random.random())
# output：
# random number 1： 0.13436424411240122
# random number 2： 0.13436424411240122


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Code example : random.getstate & random.setstate

import random
random.seed(42)
print(random.sample(range(20), k=10))
st = random.getstate() # Take out and generate the last line of code ,random The state of 
print(random.sample(range(20), k=20)) # print 20
random.setstate(st) # Restore the last random state 
print(random.sample(range(20), k=10)) # print same first 10
# output：
# [12, 0, 4, 3, 11, 10, 19, 1, 5, 18]
# [4, 9, 0, 3, 10, 8, 16, 7, 18, 17, 14, 6, 2, 1, 5, 11, 15, 13, 19, 12]
# [4, 9, 0, 3, 10, 8, 16, 7, 18, 17]


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2. random.random

Randomly generate one [0,1) The floating point number between

Code example

float = random.random()
""" float = 0.123565654548978 """


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3. random.uniform

produce [a,b] A random floating-point number in the range

Code example

float = random.uniform(11,15)
""" float = 13.882923467738049 """


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4. random.randint

Random generation [a,b] An integer in the range .

Code example

int = random.randint(1, 9)
""" int = 2 """


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5. random.choice

Randomly select a data from a non empty sequence and bring it back , The sequence can be list、tuple、str、set.

Code example

str = random.choice(" Programmer Wanfeng original series ")
""" str = primary """


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6. random.choices

Python3.6 Version added . Select randomly from the cluster k Time data , Return a list , You can set weights . Altogether 4 Parameters

• population： colony , Required .
• weights： Relative weights .
• cum_weights： Add weight , Not commonly used . Unable to join weights share .
• k： Selection times .

Code example

str = [" cheng ", " order ", " member ", " On the evening of ", " Maple "]
res = random.choices(str, weights=[0, 0, 1, 0, 0], k=5)
""" Because to 【 member 】 This word , adopt weights The parameter adds a special weight ：1, Other weights are 0, So no matter how many times you choose randomly , The result is 【 member 】 res = [' member ', ' member ', ' member ', ' member ', ' member '] """


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7. random.randrange(a,b,step)

Reference resources range Usage of ：

• Don't specify step, Random generation [a,b) An integer in the range .
• Appoint step,step As a step size, it will further limit [a,b) The scope of the , such as randrange(0,11,2) It means to generate [0,11) Random even numbers in the range .
• Don't specify a, Default from 0 Start .

Code example

int = random.randrange(3, 9)
""" int = 5 """


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8. random.sample

Select from the set k Elements , Return a list , Clusters can be list、tuple、str、set.

• No repetition ： It can be understood as a deck of playing cards , It's really random , But it won't repeat .
• Random number , Cannot exceed the length of the set . When dealing cards , A deck of cards has 54 Zhang , It is impossible to draw randomly 100 Time .

Code example

str = [" cheng ", " order ", " member ", " On the evening of ", " Maple "]
res = random.sample(str, 5)
""" res = [' member ', ' order ', ' cheng ', ' Maple ', ' On the evening of '] """


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9. random.shuffle

Disrupt the original ordered set , Be careful ： This method does not return a value , It directly changes the order of the original set . So if you want to change tuple This immutable set , Will report a mistake .

Code example

str = [" cheng ", " order ", " member ", " On the evening of ", " Maple ", " Yes ", " along ", " order "]
random.shuffle(str)
""" str = [' Maple ', ' along ', ' member ', ' order ', ' Yes ', ' On the evening of ', ' order ', ' cheng '] """


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10. random.getrandbits

Generate an integer with a specified bit size .

Code example

int = random.getrandbits(8)
""" int = 136 """


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At the end

Although I am Python The programmer , But in the recent development, I found that I didn't master many basic knowledge .

So I decided to start with this one , I decided to take that time to join Python when , The romantic feelings of feeding horses and chopping firewood and facing the sea , Go to the serious in-depth sorting and sharing Python Common knowledge points .

I hope it works for you .