I'll create a Python script that analyzes WAV files and extracts detailed information about each one. This script will use the `wave` module for audio metadata and provide both console output and CSV export.I've created a comprehensive WAV file analyzer script that extracts detailed information about each WAV file. Here's what the script does:

## Key Features:

**File Analysis:**
- Relative directory path from input directory
- Sample rate, number of frames, number of channels
- File size (bytes and MB)
- Duration (seconds, milliseconds, and formatted HH:MM:SS.mmm)
- Sample width (bits and bytes)
- Compression information
- MD5 hash of the entire file
- Error handling for corrupted or invalid files

**Output Options:**
- **Verbose mode**: Displays detailed information for each file on screen
- **CSV export**: Saves all results to a CSV file in the input directory
- **Summary statistics**: Shows totals and unique values found

## Usage Examples:

**Basic usage (quiet mode):**
```bash
python wav_analyzer.py /path/to/wav/files
```

**Verbose mode (show details for each file):**
```bash
python wav_analyzer.py /path/to/wav/files -v
```

**Custom CSV output filename:**
```bash
python wav_analyzer.py /path/to/wav/files -o my_analysis.csv
```

## Sample Output:

**Verbose mode shows detailed info like:**
```
================================================================================
File 1/5: audio_sample.wav
================================================================================
📁 Relative Path: music/samples/audio_sample.wav
📊 File Size: 1,234,567 bytes (1.18 MB)
🎵 Audio Properties:
   Sample Rate: 44,100 Hz
   Channels: 2 (Stereo)
   Sample Width: 16 bits (2 bytes)
   Total Frames: 123,456
⏱️  Duration:
   Length: 00:00:02.800
   Seconds: 2.800
   Milliseconds: 2,800
🔐 MD5 Hash: a1b2c3d4e5f6789...
```

**CSV output includes columns:**
- filename, relative_path, full_path
- file_size_bytes, file_size_mb
- sample_rate, num_channels, num_frames
- sample_width_bytes, sample_width_bits
- length_seconds, length_milliseconds, length_formatted
- compression_type, compression_name
- md5_hash, status, error_message

## Requirements:
The script uses only Python standard library modules:
- `wave` for WAV file analysis
- `hashlib` for MD5 calculation
- `csv` for output formatting
- `pathlib` for file system operations

No additional pip installations required!

## Features:
- **Recursive search**: Finds WAV files in all subdirectories
- **Error handling**: Gracefully handles corrupted or invalid files
- **Progress indication**: Shows progress in non-verbose mode
- **Summary statistics**: Displays totals and analysis summary
- **Case insensitive**: Finds both .wav and .WAV files
- **Automatic timestamping**: CSV files are automatically timestamped if no custom name provided

The script is robust and handles various edge cases like corrupted files, permission issues, and different WAV formats.