change-the-pitch.py

#Since a wav file basically is raw audio data, you won't be able to change the pitch without "raw audio processing".

#Here is what you could do. You will need the wave (standard library) and numpy modules.

import wave
import numpy as np

# Open the files.

wr = wave.open('YT_Track 5.wav', 'r')
# Set the parameters for the output file.
par = list(wr.getparams())
par[3] = 0  # The number of samples will be set by writeframes.
par = tuple(par)
ww = wave.open('pitch1.wav', 'w')
ww.setparams(par)

#The sound should be processed in small fractions of a second. This cuts down on reverb. Try setting fr to 1; you'll hear annoying echos.

fr = 20
sz = wr.getframerate()//fr  # Read and process 1/fr second at a time.
# A larger number for fr means less reverb.
c = int(wr.getnframes()/sz)  # count of the whole file
shift = 8//fr  # shifting 100 Hz
for num in range(c):

#Read the data, split it in left and right channel (assuming a stereo WAV file).

    da = np.fromstring(wr.readframes(sz), dtype=np.int16)
    left, right = da[0::2], da[1::2]  # left and right channel

#Extract the frequencies using the Fast Fourier Transform built into numpy.

    lf, rf = np.fft.rfft(left), np.fft.rfft(right)

#Roll the array to increase the pitch.

    lf, rf = np.roll(lf, shift), np.roll(rf, shift)

#The highest frequencies roll over to the lowest ones. That's not what we want, so zero them.

    lf[0:shift], rf[0:shift] = 0, 0

#Now use the inverse Fourier transform to convert the signal back into amplitude.

    nl, nr = np.fft.irfft(lf), np.fft.irfft(rf)

#Combine the two channels.

    ns = np.column_stack((nl, nr)).ravel().astype(np.int16)

#Write the output data.

ww.writeframes(ns.tostring())

#Close the files when all frames are processed.

wr.close()
ww.close()