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Title: A Guide to Seeding Randomness in Python with Examples
Introduction:
Random number generation is a common task in programming, and Python provides a built-in module called random for this purpose. However, if you want to generate reproducible random sequences, it's essential to seed the random number generator. This tutorial will guide you through the process of seeding randomness in Python, ensuring consistent results across different runs.
In Python, the random module provides functions for generating random numbers. Start by importing this module in your script or Jupyter notebook:
To ensure reproducibility, you need to seed the random number generator. The seed is a starting point for the sequence of pseudo-random numbers generated. You can use the seed() function from the random module to set the seed:
Choose a seed value that makes sense for your application or experiment. Using the same seed will result in the same sequence of random numbers.
Once you have seeded the random number generator, you can use the various functions provided by the random module to generate random numbers. Here are a few examples:
To guarantee reproducibility, make sure to set the seed before generating any random numbers. Running the script or notebook with the same seed should produce identical results.
Seeding randomness in Python is a crucial step when you need consistent and reproducible random sequences. By following the steps outlined in this tutorial, you can control the initial state of the random number generator and obtain the same random results across different runs of your code.
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