There are two types of random number generators: pseudo-random number generator and true random number generator.

Pseudorandom numbers depend on computer algorithms. The computer uses algorithms to generate random numbers. These random numbers are not truly random because they are predictable like the generated numbers using NumPy random seed.

Whereas, truly random numbers are generated by measuring truly physical random parameters so we can ensure that the generated numbers are truly random.

The pseudo-random numbers are not safe to use in cryptography because they can be guessed by attackers.

In Python, the built-in random module generates pseudo-random numbers. In this tutorial, we will discuss both types. So let’s get started.

Table of Contents

• Random number between 0 and 100
• Random number with a step size
• Random floating/double number in a range
• Random number from Iterable
• Using random.choice()
• Using randint()
• Using randrange()
• Excluding certain numbers from a range (Conditional choice)
• Random number of length N
• Random numbers in a two-dimensional array
• Random number probability
• Mean and standard deviation
• Negative random number
• Generate with duplicates
• Using randrange()
• Using choice()
• Generate without duplicates (Unique random numbers)
• Random number on circle
• Shuffle Numbers
• Generate true random number

#python #random #generate random numbers #random numbers #generate random numbers in python