Question

When the random module is imported, what does it use as a seed value for random number generation?

Short answer

The default seed value for random number generation in Python's random module is derived from the current system time using the 'time.time()' function. This ensures that the generated sequence of random numbers is different each time the module is used, unless the seed is manually set to a specific value.

Step-by-step solution

Understanding Random Number Generation

In Python, the random number generation process is based on certain algorithms that produce sequences of numbers that appear to be random. In reality, these numbers are not truly random but follow a deterministic pattern, and are considered to be pseudorandom.

Concept of a Seed

A seed is an initial value used by the algorithm for generating random numbers. The seed value serves as the starting point, and the algorithm will generate the same sequence of random numbers whenever the same seed value is used. Different seed values will result in different sequences of random numbers. Seeding is essential in random number generation because it ensures that, for example in simulations, the same starting conditions can be used to achieve repeatability of results, as well as initiating random number generation with a different sequence each time the random module is used.

Default Seed Value in Python's Random Module

When the random module is imported in Python, it uses a default seed value derived from the current system time. This is done using the 'time.time()' function, which returns the current time in the form of a floating-point number (the number of seconds since the epoch, typically January 1, 1970). When the random module is initialized without explicitly specifying a seed value, it will automatically use the current system time as the seed, ensuring that the generated sequence of random numbers is different each time the module is used, unless the seed is manually set to a specific value.