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tech_docs/music/extract_mp3_tracks.md
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tech_docs/music/extract_mp3_tracks.md
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### Analyze Programmatically Using Librosa for Detailed Feature Extraction and PyDub for Automated Audio Manipulations
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#### Librosa: Detailed Feature Extraction
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Librosa is a powerful library for audio and music analysis. It provides a range of tools to extract and visualize audio features, making it highly useful for music production. Here are some key features and ideas on how to use them:
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1. **Loading Audio Files**
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- Load audio files with a specified sample rate.
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```python
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import librosa
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y, sr = librosa.load('output/vocals.wav', sr=44100)
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```
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2. **Visualizing Waveforms**
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- Visualize the audio waveform to understand the overall structure.
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```python
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import librosa.display
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import matplotlib.pyplot as plt
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plt.figure(figsize=(14, 5))
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librosa.display.waveshow(y, sr=sr)
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plt.title('Waveform')
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plt.show()
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```
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3. **Spectrogram Analysis**
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- Compute and display the spectrogram to analyze the frequency content over time.
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```python
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D = np.abs(librosa.stft(y))
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DB = librosa.amplitude_to_db(D, ref=np.max)
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plt.figure(figsize=(14, 5))
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librosa.display.specshow(DB, sr=sr, x_axis='time', y_axis='log')
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plt.colorbar(format='%+2.0f dB')
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plt.title('Spectrogram')
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plt.show()
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```
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4. **Mel-frequency Cepstral Coefficients (MFCCs)**
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- Extract MFCCs for timbral analysis, which are widely used in music and speech recognition.
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```python
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mfccs = librosa.feature.mfcc(y=y, sr=sr, n_mfcc=13)
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plt.figure(figsize=(14, 5))
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librosa.display.specshow(mfccs, sr=sr, x_axis='time')
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plt.colorbar()
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plt.title('MFCC')
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plt.show()
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```
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5. **Chroma Feature Extraction**
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- Analyze harmonic content using chroma features, useful for chord recognition.
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```python
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chroma = librosa.feature.chroma_stft(y=y, sr=sr)
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plt.figure(figsize=(14, 5))
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librosa.display.specshow(chroma, sr=sr, x_axis='time', y_axis='chroma')
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plt.colorbar()
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plt.title('Chroma Feature')
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plt.show()
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```
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6. **Tempo and Beat Tracking**
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- Estimate the tempo and detect beats in the audio, which can be useful for syncing and remixing.
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```python
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tempo, beat_frames = librosa.beat.beat_track(y=y, sr=sr)
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print(f'Tempo: {tempo} BPM')
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# Convert beat frames to time
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beat_times = librosa.frames_to_time(beat_frames, sr=sr)
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```
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7. **Onset Detection**
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- Detect note onsets, which is useful for transcribing music or syncing effects.
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```python
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onset_frames = librosa.onset.onset_detect(y=y, sr=sr)
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onset_times = librosa.frames_to_time(onset_frames, sr=sr)
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```
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#### PyDub: Automated Audio Manipulations
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PyDub is a high-level library for audio manipulation. It simplifies many common tasks, making it ideal for automated workflows in music production.
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1. **Loading Audio Files**
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- Load audio files for manipulation.
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```python
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from pydub import AudioSegment
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sound = AudioSegment.from_wav('output/vocals.wav')
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```
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2. **Volume Adjustments**
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- Increase or decrease the volume of audio segments.
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```python
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louder_sound = sound + 6 # Increase volume by 6 dB
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quieter_sound = sound - 6 # Decrease volume by 6 dB
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```
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3. **Splitting and Merging Audio**
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- Split and merge audio segments to rearrange parts of a track.
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```python
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# Split audio at 30 seconds
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first_part = sound[:30000]
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second_part = sound[30000:]
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# Merge two audio segments
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combined = first_part + second_part
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```
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4. **Applying Effects**
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- Apply various effects like reverb, fade in/out, and normalization.
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```python
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# Apply fade in and fade out
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faded_in = sound.fade_in(2000) # 2-second fade in
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faded_out = sound.fade_out(2000) # 2-second fade out
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# Normalize the audio
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normalized_sound = sound.normalize()
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```
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5. **Exporting Audio Files**
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- Export manipulated audio to different formats.
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```python
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normalized_sound.export('output/normalized_vocals.wav', format='wav')
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```
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6. **Batch Processing**
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- Automate the processing of multiple files using loops and scripts.
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```python
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import os
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input_directory = 'input_folder'
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output_directory = 'output_folder'
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for filename in os.listdir(input_directory):
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if filename.endswith('.wav'):
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audio = AudioSegment.from_wav(os.path.join(input_directory, filename))
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# Apply some effects
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louder_audio = audio + 6
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# Export the result
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output_path = os.path.join(output_directory, filename)
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louder_audio.export(output_path, format='wav')
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```
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### Useful Ideas for Music Production
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1. **Creating Stems for Remixing**:
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- Use Spleeter to create separate stems (vocals, drums, bass, etc.) from a mixed track, allowing for easy remixing and re-arranging of music elements.
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2. **Dynamic Sound Effects**:
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- Use PyDub to automate the application of dynamic effects like volume changes, fades, and crossfades to create more engaging transitions in your music.
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3. **Beat Matching and Syncing**:
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- Use Librosa’s tempo and beat detection features to match the beats of different tracks for seamless DJ mixing or mashups.
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4. **Harmonic Analysis for Mashups**:
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- Use chroma feature extraction to analyze the harmonic content of tracks, making it easier to find compatible songs for mashups based on their harmonic profiles.
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5. **Transcription and Note Detection**:
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- Use Librosa’s onset detection and MFCC features to transcribe music or detect notes, which can be useful for creating MIDI files or sheet music from audio recordings.
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6. **Automated Mastering**:
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- Create scripts using PyDub to apply a series of mastering effects like normalization, equalization, and compression to batches of tracks, ensuring a consistent sound across an album.
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7. **Sound Design and Sampling**:
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- Extract unique sounds or samples from existing tracks using Spleeter and manipulate them with PyDub to create new instruments or sound effects.
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8. **Visualization and Analysis for Education**:
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- Use Librosa to visualize and analyze audio features, which can be useful for music education and understanding the structure and components of different music genres.
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By combining these tools and techniques, you can create a comprehensive and powerful workflow for music production on Linux, leveraging the strengths of both manual and automated processes to enhance your creative capabilities.
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User
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what Linux or Python tool can I utilize to capture mp3s, is there a way to capture from Youtube and or Youtube Music?
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ChatGPT
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To capture MP3s from YouTube or YouTube Music on Linux, you can use tools like `youtube-dl` or its actively maintained fork `yt-dlp`, combined with FFmpeg for audio extraction. These tools allow you to download videos and extract audio from them.
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### Using yt-dlp to Capture MP3s from YouTube
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#### 1. Install yt-dlp
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First, you need to install `yt-dlp`. You can do this using pip or by downloading the binary directly.
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**Using pip**:
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```bash
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pip install yt-dlp
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```
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**Using the binary**:
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```bash
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sudo wget https://github.com/yt-dlp/yt-dlp/releases/latest/download/yt-dlp -O /usr/local/bin/yt-dlp
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sudo chmod a+rx /usr/local/bin/yt-dlp
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```
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#### 2. Install FFmpeg
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FFmpeg is required to convert the downloaded video to MP3.
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```bash
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sudo apt install ffmpeg
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```
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#### 3. Download and Convert to MP3
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You can use `yt-dlp` to download the audio directly and convert it to MP3 format. Here’s how you can do it:
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**Download and convert a single video**:
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```bash
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yt-dlp -x --audio-format mp3 <YouTube-URL>
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```
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**Download and convert a playlist**:
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```bash
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yt-dlp -x --audio-format mp3 -i <Playlist-URL>
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```
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**Download and specify output directory and filename**:
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```bash
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yt-dlp -x --audio-format mp3 -o '~/Music/%(title)s.%(ext)s' <YouTube-URL>
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```
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### Example Workflow
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1. **Install yt-dlp and FFmpeg**:
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```bash
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pip install yt-dlp
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sudo apt install ffmpeg
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```
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2. **Download and convert a YouTube video to MP3**:
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```bash
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yt-dlp -x --audio-format mp3 https://www.youtube.com/watch?v=dQw4w9WgXcQ
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```
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3. **Download and convert a YouTube playlist to MP3**:
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```bash
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yt-dlp -x --audio-format mp3 -i https://www.youtube.com/playlist?list=PL4o29bINVT4EG_y-k5jGoOu3-Am8Nvi10
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```
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### Advanced Options
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- **Set Audio Quality**: You can specify the audio quality by setting the `--audio-quality` option (e.g., `0` for best quality).
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```bash
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yt-dlp -x --audio-format mp3 --audio-quality 0 <YouTube-URL>
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```
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- **Custom Post-processing**: You can use FFmpeg for custom post-processing. For example, normalize audio volume or change bitrate.
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```bash
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yt-dlp -x --audio-format mp3 --postprocessor-args "-ar 44100 -b:a 192k" <YouTube-URL>
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```
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### Using Python Script with yt-dlp
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If you prefer to integrate this into a Python script, you can use the `yt_dlp` library directly.
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```python
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import yt_dlp
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def download_audio(url, output_path):
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ydl_opts = {
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'format': 'bestaudio/best',
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'postprocessors': [{
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'key': 'FFmpegExtractAudio',
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'preferredcodec': 'mp3',
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'preferredquality': '192',
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}],
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'outtmpl': output_path,
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}
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with yt_dlp.YoutubeDL(ydl_opts) as ydl:
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ydl.download([url])
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# Example usage
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url = 'https://www.youtube.com/watch?v=dQw4w9WgXcQ'
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output_path = '~/Music/%(title)s.%(ext)s'
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download_audio(url, output_path)
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```
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### Summary
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By using `yt-dlp` and FFmpeg, you can effectively download and convert YouTube videos to MP3 files on Linux. These tools offer a flexible and powerful way to capture audio from YouTube, making them ideal for music collection and other audio-related projects.
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