python 41 lines · 5 steps

Reading WAV metadata into a dataclass

Open a WAV file, pull its raw audio parameters, and derive duration and bitrate into a typed record.

Explained by highlit

Beginner dataclass audio file-io context-manager metadata

1import wave
2import os
3from dataclasses import dataclass
4 
5 
6@dataclass
7class WavInfo:
8    path: str
9    channels: int
10    sample_rate: int
11    sample_width_bits: int
12    frame_count: int
13    duration_seconds: float
14    file_size_bytes: int
15    bitrate_kbps: float
16 
17 
18def read_wav_metadata(path: str) -> WavInfo:
19    with wave.open(path, "rb") as wav:
20        channels = wav.getnchannels()
21        sample_rate = wav.getframerate()
22        sample_width = wav.getsampwidth()
23        frame_count = wav.getnframes()
24 
25    if sample_rate == 0:
26        raise ValueError(f"{path}: invalid sample rate of 0")
27 
28    duration = frame_count / sample_rate
29    file_size = os.path.getsize(path)
30    bitrate = sample_rate * sample_width * 8 * channels / 1000
31 
32    return WavInfo(
33        path=path,
34        channels=channels,
35        sample_rate=sample_rate,
36        sample_width_bits=sample_width * 8,
37        frame_count=frame_count,
38        duration_seconds=round(duration, 3),
39        file_size_bytes=file_size,
40        bitrate_kbps=round(bitrate, 1),
41    )

01 / 01

STEP 01

Walkthrough

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Three takeaways

1A dataclass gives you a typed, self-documenting container for structured results with almost no boilerplate.
2Reading with a context manager guarantees the file handle closes even before you compute derived values.
3Guarding against divide-by-zero inputs turns a cryptic crash into a clear, actionable error.

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