Mastering Program Development Guidelines

When working in this repository, adhere strictly to the following core requirements and architectural constraints:

1. Core Audio Processing Requirements

• Audio Data Format: You must use 32-bit float or 64-bit float representations for ALL audio processing stages. This is critical to prevent clipping during intermediate DSP operations and to maintain maximum dynamic range.
• DSP Libraries: Prioritize high-performance DSP libraries. Rely heavily on numpy for fast vectorized array operations and scipy.signal for filtering and complex signal processing algorithms.
• Output Normalization: By default, all final audio output MUST be peak-normalized to -1.0 dBFS to ensure safe headroom before final export or playback.

2. Proposed Project Folder Structure

To ensure clean, maintainable code, strictly separate the Audio Engine from the User Interface.

C:\Users\abejh\Mastering-Program-V1\
├── engine/                 # Audio Engine (Core DSP and Processing)
│   ├── __init__.py
│   ├── dsp/                # Signal processing algorithms (EQ, Compression, Limiting, etc.)
│   ├── io/                 # Audio file loading, saving, and formatting
│   └── utils.py            # DSP helpers (e.g., peak normalization functions)
├── ui/                     # User Interface (Frontend components)
│   ├── __init__.py
│   ├── components/         # Reusable functional widgets (knobs, meters, sliders)
│   ├── views/              # Main application screens and layouts
│   └── controller.py       # Intermediary bridge logic between UI actions and the Engine
├── tests/                  # Automated Testing
│   ├── test_engine/        # DSP logic and math validation tests
│   └── test_ui/            # UI unit tests
├── main.py                 # Application entry point
└── requirements.txt        # Project dependencies (e.g., numpy, scipy, pyqt/tkinter)

Architectural Rule: The engine/ module must NEVER import from or depend on the ui/ module. The engine must remain entirely headless and UI-agnostic to allow for easy automated testing and potential CLI usage.