from audio_normalizer import AudioNormalizer

# Peak normalization to -1 dBFS
normalizer = AudioNormalizer()
normalizer.load('input.mp3')
normalizer.normalize_peak(target_dbfs=-1.0)
normalizer.save('normalized.mp3')

# RMS normalization for consistent average loudness
normalizer.normalize_rms(target_dbfs=-20.0)
normalizer.save('normalized_rms.mp3')

# Batch normalize all files to same level
normalizer.batch_normalize(
    input_files=['audio1.mp3', 'audio2.mp3'],
    output_dir='normalized/',
    method='rms',
    target_dbfs=-20.0
)

# Peak normalization
python audio_normalizer.py input.mp3 --output normalized.mp3 --method peak --target -1.0

# RMS normalization
python audio_normalizer.py input.mp3 --output normalized.mp3 --method rms --target -20.0

# Batch normalize directory
python audio_normalizer.py *.mp3 --output-dir normalized/ --method rms --target -20.0

# Show current levels without normalizing
python audio_normalizer.py input.mp3 --analyze-only

class AudioNormalizer:
    def load(self, filepath: str) -> 'AudioNormalizer'
    def normalize_peak(self, target_dbfs: float = -1.0, headroom: float = 0.1) -> 'AudioNormalizer'
    def normalize_rms(self, target_dbfs: float = -20.0) -> 'AudioNormalizer'
    def analyze_levels(self) -> Dict[str, float]
    def save(self, output: str, format: str = None, bitrate: str = '192k') -> str
    def batch_normalize(self, input_files: List[str], output_dir: str,
                       method: str = 'rms', target_dbfs: float = -20.0) -> List[str]

normalizer.normalize_rms(target_dbfs=-19.0)  # Speech clarity

normalizer.normalize_peak(target_dbfs=-1.0)  # Preserve dynamics

normalizer.normalize_rms(target_dbfs=-23.0)  # EBU R128 compliance