What is Random Number Generator in Python?

Python programming language was released in the year 1991. Since the release of the programming language, it has gained great popularity. Python language is considered now one of the most popular and most productive programming languages. It is a programming language used for different purposes like server-side web development, software development, mathematical and statistical analytics, system scripting, etc. Python helps in creating web applications. It is also used along with software to create workflows. Another task python can perform is that it can connect to database systems and it can read and modify files. Developers use python for handling big data and to perform complex mathematical problems. In rapid prototyping also python is used and also helpful in production-ready software development.

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Python is a multi-platform programming language. The syntax of python is very simple and is very close to the English language. When compared to other programming languages, python syntax can be written with few lines. This is a great advantage to python developers. The code of python can be executed as soon as the code is written. Python can be processed in three ways, viz procedurally, object-oriented, or functionally.

Random Number Generation in Programming languages

There are many programming languages available in the market now. Each one has its peculiarity and its uses. Without programming languages, technology is useless. Programming languages plays important role in every technology field. Even if it is machine learning, data science, Artificial Intelligence, Banking, Finance, the Medical sector, etc. Programming languages offer many functions which help the developers to complete their work without any hassle. Random number generation is a feature like that.

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Random number generation is an important aspect that is offered by programming languages to its developers. Random number generation can be defined as the ability to generate random numbers which can be used for specific programs like games, statistical modeling programs, and also cryptographic applications that need to encrypt and decrypt. The use of random numbers can be explained with the help of games as an example. Without random numbers in the game, you will see the same places everywhere, see the same objective every time, the results will be the same always, etc. So random numbers help in the change of objectives, sequences, and places in games. Like this, it helps in getting different outputs related to the different situations.

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Random Number Generator in Python

In Python programming language also, random the number generator plays a key role. But the process or algorithm is not the same as that of other programming languages. Python generates random using the module random. Python generates random numbers using the Mersenne Twister algorithm. However, because this approach is deterministic, it is unsuitable for cryptography purposes. Python uses different built-in functions under the random module. These different built-in functions are useful in different scenarios for generating a random number. Let us look into each one.

• randint()

When an integer is between the specified limits, the randint function is used to generate a random number. In this function there will be two arguments, they are x and y. The integer produced will be x < = i <= y.

• randrange()

In this function, there will be three arguments generated: 2 main arguments start and stop along with one optional argument step. The value of the step will always be 1.

• random()

In this function, it will return a random floating number between 0 and 1, excluding both 0 and 1.

• uniform()

This function allows you to generate a floating-point number inside a certain range. It takes two arguments, start and stop, and returns a float between the two (including the limits).

• choice()

This function can be used to select a random element from a given sequence. It only accepts one argument: the sequence. And it returns a sequence element at random.

• sample()

You can use a sample if you want more than one random element from a sequence. It accepts two arguments, population, and k, with the population being a sequence and k being an integer. Then it returns a list of k random sequence population elements.

• shuffle()

This function takes only one argument – a list. It then rearranges the elements of the list in place and returns None.

• seed()

In this function also, it takes only one value – the seed value. This value is used to start a random number generator. Now, whenever you execute the seed function with this seed value, the same series of random integers will be generated.

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Conclusion

We have seen the importance of the random number generator function in Python and the built-in function helps in random number generator. We looked at the functions available for producing integers. In addition, we learned how to produce random floating-point values. Finally, we showed how to use built-in functions to pick random elements from a sequence. Using random numbers, you can create a variety of little projects. You may create games, employ random numbers while dealing with statistics in Data Science, and do a lot more.