How to use choice() function in Python Random

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by gayathrimohan dot icon Updated: Sep 25, 2023

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In Python, the random.choice() function is part of the random module. You use it to randomly select from a sequence or iterable, such as a list, tuple, or string.  

Here's how it works:  

  • Import the random module: You need to import the random module at the beginning of your Python script. Using import randomly will help with it.  
  • Using random.choice(): You can use the random.choice() function to select a random item from a sequence.   
  • Applications: Often used in where you need to introduce randomness into your code. Such as creating random game elements and shuffling items from a list of choices.  

In Python, we use the random.choice() function to select a random element from a sequence or iterable.  You can use these common data types as input. 

  • Integers: You can use a range of integers as input.   
  • Strings: If you have a list of strings, you can choose a random string.  
  • Lists: You can also choose a random element from a list of lists.  
  • Tuples: you can select a random element from a tuple-like list.  
  • Custom Objects: You can use random.choice() with custom objects. If your sequence contains instances of those objects.  

You have several options to customize its behavior while using the random.choice():  

  • Choosing a Random Number Generator (RNG): Python's random module uses a default RNG. This RNG is enough for most purposes. But you can choose a specific RNG by setting the seed with random.seed().  
  • Selecting from a List of Choices: The primary purpose of random.choice() is to select a random element. You can provide the sequence as an argument, and the function picks one element.  
  • Specifying the Number of Choices: By default, random.choice() selects a single element. This returns a list of random selections.  
  • Setting Weights for Choices: You can assign weights to the elements in your sequence. The weights' parameter in random.choices() does this. This allows you to bias the selection towards certain elements. For example, you can increase the likelihood of selecting certain choices over others.  
  • Sampling Without Replacement: you can use random.sample() instead of random.choice(). Each choice ensures that it is unique and not repeated in the results. It selects a specified number of unique elements from the sequence.  
  • Reproducibility with Seed: In the future, set a seed using random.seed(). We do this to reproduce the same random selections. This is useful for debugging or ensuring that your code behaves across runs.  

In Conclusion, it is using a random.choice() function is crucial when working with data. Particularly, it is crucial for generating random samples. It ensures unbiased and representative selections. It is vital in statistical analysis, machine learning, and simulations. We can avoid introducing unintended patterns in our data-driven tasks by incorporating randomness. This leads to more accurate and reliable results.  

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


In this solution we are using Python Random library of Python.


Follow the steps carefully to get the output easily.

  1. Download and Install the PyCharm Community Edition on your computer.
  2. Open the terminal and install the required libraries with the following commands.
  3. Install Random - pip install random.
  4. Create a new Python file on your IDE.
  5. Copy the snippet using the 'copy' button and paste it into your python file.
  6. Run the current file to generate the output.

I hope you found this useful.

I found this code snippet by searching for 'How to use choice() funtion in Python Random' 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. PyCharm Community Edition 2023.1
  2. The solution is created in Python 3.11.1 Version
  3. thanks Current Version

Using this solution, we can able to use choice() function in Python Random with simple steps. This process also facilities an easy way to use, hassle-free method to create a hands-on working version of code which would help us to use choice() function in Python Random.

Dependent Library

thanksby phildini

Python doticonstar image 153 doticonVersion:Currentdoticon
License: Permissive (Apache-2.0)

Finding ways to fund the packages you use.


            thanksby phildini

            Python doticon star image 153 doticonVersion:Currentdoticon License: Permissive (Apache-2.0)

            Finding ways to fund the packages you use.

                      You can search for any dependent library on kandi like 'thanks'.


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                      1. How does the number generator in Python Random Module work?                         

                      The random module in Python uses the PRNG algorithm to generate random numbers. PRNGs use an initial value. They call it a seed. We use that seed to generate a sequence of numbers. That number appears random but is deterministic.  

                      Here's a simplified overview of how it works:  

                      • Initialization: You can set the seed using random.seed().  
                      • Number Generation: Functions like random.randint(), random.random() are from the random module. The PRNG algorithm uses the seed to produce a sequence of random numbers.  
                      • Seed Update: After generating each number, we update the seed to a new value. This new seed is then used to generate the next number in the sequence.  
                      • Repeatable Sequences: This property is useful for debugging and reproducibility.  

                      2. What is a selected element in a list using Python choice ()?   

                      In Python, you can use the choice () function from the random module to select a chosen element from a list.   

                      Here's an example:  

                      import random  

                      my_list = [1, 2, 3, 4, 5]   

                      random_element = random.choice(my_list)  


                      In this example, random.choice(my_list) will return a selected element.   

                      3. Is there a boolean value assigned to each selected element?   

                      No, a boolean value is not assigned to each selected element by default. Whether someone assigns a boolean value to the selected element. It depends on the specific context and programming logic in use. You would need to define the boolean value. We do this based on your application's requirements.   

                      4. How can I generate a random list of elements with Python choice ()?   

                      You can generate a random list of elements using Python's random.choice() function. A random module generates it.   

                      Here's an example of how to do it:  

                      import random  

                      # List of elements to choose from   

                      elements = [1, 2, 3, 4, 5]  

                      # Number of elements you want in your random list   

                      num_elements = 3 # Change this to the desired number of elements  

                      # Generate a random list of elements   

                      random_list = random.choices(elements, k=num_elements)  


                      In this example, random.choices() selects num_elements random elements from the elements list. It returns them in a new list called random_list. You can adjust the value of num_elements to control how many random elements you want in your list.  

                      5. What are the pros and cons of using choice() for random selection versus other methods?   

                      The random module in Python uses the choice() function for random selection. But it has its own advantages and disadvantages compared to other methods.  

                      Advantages of using choice ():  

                      • Simplicity  
                      • Uniform Distribution  
                      • Speed  

                      Disadvantages of using choice ():  

                      • Limited to Sequences  
                      • Lack of Weighted Selection  
                      • Requires Loading the Entire Sequence  

                      See similar Kits and Libraries