How does `random.seed()` control the randomness in Python?

Understanding the Role of random.seed() in Python

Python's random.seed() method plays a crucial role in generating pseudo-random numbers, but its functionality can often be confusing. To shed light on this topic, let's delve into the underlying concepts.

Pseudorandom number generators (PRNGs) are used to create sequences of numbers that appear random. They work by performing operations on a seed value, typically the previous number generated. However, initializing a PRNG requires an initial seed value, known as the seed, to start this process.

The random.seed() method sets this initial seed value, allowing subsequent calls to random functions (e.g., random.randint()) to use it as the starting point for their sequence. By providing a consistent seed, as shown in the example, the same sequence of random numbers will be generated each time. This deterministic behavior is useful for debugging and testing.

However, it's important to note that the sequence generated by a PRNG will remain the same for a given seed. Changing the seed is necessary to obtain a different series of numbers.

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