There are many computational needs for randomness--from creating a game to building a simulation involving naturally occurring randomness similar to the physical world. For most purposes using the python math module to create random numbers within a specific range can be done with no further questions, but sometimes we require a more nuanced implementation. We will look at both pseudo-random number generators, which use statistically repeatable processes to generate seemingly random series and true random number generators, which inject physical processes like atmospheric noise to generate sequences of numbers. We will discuss the benefits and drawbacks of both approaches and common methods of implementing these two types of generators in python. Finally, we will look at several real applications for randomness and discuss the best method for generating “randomness” in each scenario.