PyAudioToolBox

PyAudioToolBox is a Python library for audio format conversion and manipulation.

Installation

You can install PyAudioToolBox using pip:

pip install pyaudiotoolbox

Usage

Audio Format Conversion

To convert an audio file to a different format, use the convert_audio function:

from pyaudiotoolbox.audio_converter import convert_audio

input_file = 'input.wav'
output_file = 'output.mp3'
output_format = 'mp3'

convert_audio(input_file, output_file, output_format)

Batch Conversion

To perform batch audio format conversion, use the batch_convert_audio function:

from pyaudiotoolbox.audio_converter import batch_convert_audio

input_directory = 'input_folder'
output_directory = 'output_folder'
output_format = 'ogg'

batch_convert_audio(input_directory, output_directory, output_format)

Audio Extraction

To extract audio from a video file, use the extract_audio function:

from pyaudiotoolbox.audio_extractor import extract_audio

input_video = 'input.mp4'
output_audio = 'output.wav'

# Extract audio from the video
extract_audio(input_video, output_audio)

Audio Trimming

Trim an audio file to a specified duration and save the trimmed portion to an output file.

• input_audio (str): Path to the input audio file.
• output_audio (str): Path to save the trimmed audio file.
• start_time_ms (int): Start time in milliseconds for the trim.
• end_time_ms (int): End time in milliseconds for the trim.

from pyaudiotoolbox.audio_editor import trim_audio

# Trim audio from 10 seconds to 30 seconds
- `input_audio` = "input.mp3"
- `output_audio` = "trimmed_output.mp3"
- `start_time_ms` = 10000  # 10 seconds
- `end_time_ms` = 30000    # 30 seconds

trim_audio(input_audio, output_audio, start_time_ms, end_time_ms)

Audio Splitting

Split an audio file into multiple segments at specified split points and save each segment to separate files.

• input_audio (str): Path to the input audio file.
• output_prefix (str): Prefix for the output file names.
• split_points_ms (list): List of split points in milliseconds.

from pyaudiotoolbox.audio_editor import split_audio

# Split audio into segments at 10 seconds and 20 seconds
input_audio = "input.mp3"
output_prefix = "segment"
split_points_ms = [10000, 20000]

split_audio(input_audio, output_prefix, split_points_ms)

Concatenate audio

Concatenate multiple audio files into a single audio file.

• input_files (list): List of paths to input audio files in the desired order.
• output_audio (str): Path to save the concatenated audio file.

from pyaudiotoolbox.audio_editor import concatenate_audio

# Concatenate two audio files into one
input_files = ["file1.mp3", "file2.mp3"]
output_audio = "concatenated_output.mp3"

concatenate_audio(input_files, output_audio)

Apply fade in to audio

Apply a fade-in effect to an audio file and save it to the output file.

• input_audio (str): Path to the input audio file.
• output_audio (str): Path to save the faded audio file.
• fade_duration_ms (int): Duration of the fade-in effect in milliseconds.

from pyaudiotoolbox.audio_editor import apply_fade_in

# Apply a 3-second fade-in effect to an audio file
input_audio = "input.mp3"
output_audio = "faded_intput.mp3"
fade_duration_ms = 3000  # 3 seconds

apply_fade_in(input_audio, output_audio, fade_duration_ms)

Apply fade out to audio

Apply a fade-out effect to an audio file and save it to the output file.

• input_audio (str): Path to the input audio file.
• output_audio (str): Path to save the faded audio file.
• fade_duration_ms (int): Duration of the fade-out effect in milliseconds.

from pyaudiotoolbox.audio_editor import apply_fade_out

# Apply a 2-second fade-out effect to an audio file
input_audio = "input.mp3"
output_audio = "faded_output.mp3"
fade_duration_ms = 2000  # 2 seconds

apply_fade_out(input_audio, output_audio, fade_duration_ms)

Normalize audio volume

You can use this function to normalize the volume of an audio file by specifying the input audio file path and the target volume level in dBFS.

input_audio_file = 'input.mp3'
target_volume_level = -15  # Set your target volume level in dBFS

normalized_audio = normalize_audio(input_audio_file, target_volume_level)

# Export the normalized audio to a new file
normalized_audio.export('output_normalized_audio.mp3', format='mp3')