This week we are going to discuss hashing. Simply put, a hashing function takes arbitrary sized data and maps it to fixed size in a deterministic manner. Therefore, when given the same input, the same result is generated. Ideally, a hash function would be 1-1, as in for every input a unique output is given. This is also known as an injective function. In reality, though, that’s not possible since the amount of data being input can be many times larger than the output. So instead hashing algorithms aim to be uniform, which is to say they use the entire output space equally. This means that the chances of two inputs generating the same hash are lower given the size of the output hash.