How to use the Random randint() method in Python

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by Abdul Rawoof A R dot icon Updated: Sep 19, 2023

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A random number generator (RNG) is a math formula that makes sequences of numbers seem random. Various applications require these numbers for randomness. It is difficult to create a random number generator. The numbers need to be unpredictable and evenly distributed.   

Here are some different types of random number generators:  

  • Linear Congruential Generator (LCG)   
  • Mersenne Twister   
  • Secure PRNGs (CSPRNG)   
  • True Random Number Generators (TRNG)   
  • Chaotic Systems   
  • Hardware Random Number Generators (HRNG)   
  • Non-uniform Random Variate Generators   
  • Middle Square Method   
  • XOR-Shift Generators   
  • Lagged Fibonacci Generator   


You can use the Python randint() function to generate random integers. Just provide the lower and upper bounds as arguments. Programming often needs randomness for different applications. For sequences, there is a uniform selection of a random element. We need two functions. You can use two functions. One shuffles a list randomly, and another picks items without repeats.   


Here is an example of how to use the Random randint() method in Python:   

Fig: Preview of the output that you will get on running this code from your IDE.



Follow the steps carefully to get the output easily.

  1. Install PyCharm Community Edition on your computer.
  2. Open the terminal and install the required libraries with the following commands.
  3. Create a new Python file(e.g.
  4. Copy the snippet using the 'copy' button and paste it into that file.
  5. Run the file using the run button.

I hope you found this helpful. I have added the link to dependent libraries, and version information in the following sections.

I found this code snippet by searching for 'error generating random number in python' in kandi. You can try any such use case!

Environment Tested

I tested this solution in the following versions. Be mindful of changes when working with other versions.

  1. The solution is created in PyCharm 2022.3.3.
  2. The solution is tested on Python 3.9.7.

Using this solution, we are able to use the random randint() method in Python with simple steps. This process also facilitates an easy-to-use, hassle-free method to create a hands-on working version of code which would help us to use the random randint() method in Python.


1. What is the generation process of random integers using Python's randint() function?   

In Python, you can get random numbers from the random module with the randint() function. The randint() function will generate a random integer between a specified range.   

2. how does a module handle a decimal number when you generate random integers in Python?   

The random module offers functions for generating random numbers, including random integers. To generate random integers, the random.randint(a, b) function uses floating-point numbers.   

3. What is the range of random integer values generated by the randint function?   

The randint function generates random integer values. The range of these values depends on the programming language. I'll provide examples from a few common programming languages and libraries:   

  • Python (using the random module).   
  • JavaScript (using the Math. random function).   
  • C++ (using the <random> library).   

4. How can we make a draw game that uses random numbers from Python's randint() function?   

We can make a draw game by using Python's randint() function to generate random numbers. It can be an educational project. In this game, players choose numbers, and the program picks a random number. The player aims to guess the correct number. Here's a step-by-step guide on how to create a simple draw game in Python using randint():  

  • Import the Random Module.   
  • Set Up the Game.   
  • Create a Loop for the Game.   
  • Run the Game.   

5. Is there a limit to the random integers or other data types that this Python function can generate?   

  • Pseudorandomness.   
  • Seed Sensitivity.   
  • Quality of Randomness.   
  • Distribution.   
  • Periodicity.   
  • Thread Safety.   
  • Compatibility.   
  • Performance.  


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