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PYTHON PROGRAM • MODULES, DATES & REGULAR EXPRESSIONS

Generate a Reproducible Random Number in Python

Learn generate a reproducible random number in python with a short, executable Python example.

Beginnerrandomseed()

PROBLEM UNDERSTANDING

Input and expected output

Sample input
No input required
Sample output
6

COMPLETE PYTHON PROGRAM

Complete Python implementation

python-seeded-random.py
Open in compiler
import random
random.seed(7)
print(random.randint(1, 10))

GUIDED CODE TOUR • NOT LIVE EXECUTION

Study the program line by line

Use the real compiler button above to run and debug with different inputs.

CURRENT STEP

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SELECTED LINE

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EXPECTED OUTPUT FOR THE SAMPLE

6
0%Step 0 of 0

PROGRAM EXPLANATION

Algorithm and explanation

  1. Import the required standard-library tools and prepare the sample data for generate a reproducible random number.
  2. Apply random and seed() to compute the required result.
  3. Display the result for generate a reproducible random number and compare it with the documented sample output.

This example of generate a reproducible random number computes the result directly from the prepared sample data. It demonstrates random and seed() and prints a deterministic result that can be checked against the sample output.

EFFICIENCY

Time and space complexity

Time complexity

O(1)

Auxiliary space

O(1)

DEBUGGING CHECKLIST

Common mistakes

Check this

For generate a reproducible random number, keep the data shape and value types consistent with random.

Check this

Apply random in the same order shown by the algorithm; changing the order can change the result.

Check this

Verify the final random and seed() result against the sample before trying new data.

Try it yourself

Practice: Run the program with the sample input, predict its output, and then test one boundary case of your own.