To develop a genuine random number generator in Python by utilizing ambient noise such as recorded MP3 or wave files, you can follow these steps:
Here's a sample code:
import wave
import numpy as np
import random
def get_random_number(audio_file):
# Step 1: Import necessary libraries
# Step 2: Read the audio file
with wave.open(audio_file, 'rb') as wav_file:
# Step 3: Extract the audio frames
frames = wav_file.readframes(-1)
# Step 4: Convert frames to integers
int_frames = np.frombuffer(frames, dtype='int16')
# Step 5: Generate a random sequence of integers
rand_seq = np.random.randint(0, 32767, len(int_frames))
# Step 6: Choose a random starting index
start_index = random.randint(0, len(int_frames) - len(rand_seq))
new_seq = []
# Step 7: Combine randomly generated integers and audio frames
for i in range(len(rand_seq)):
new_val = (rand_seq[i] + int_frames[start_index + i]) % 32767
new_seq.append(new_val)
# Step 8: Shuffle the list
random.shuffle(new_seq)
# Step 9: Set the shuffled list as the seed
random.seed(new_seq)
# Step 10: Generate a random number
return random.random()
Note: this method may not produce truly random numbers, as the ambient noise might contain patterns or biases. Additionally, the randomness of this method may depend on the quality of the audio file and the method used to record it. It's always best to evaluate the randomness of any random number generator before relying on it for security or other critical applications.
Asked: 2023-06-14 11:03:34 +0000
Seen: 11 times
Last updated: Jun 14 '23