Architecture & Dependency Disclosure
A concise technical overview of runtime components, data isolation, and network policies for users who require clarity on what runs on their machine.
Runtime Stack & Libraries
MySoundLib is distributed as a self-contained desktop binary. It runs directly on the local operating system without requiring web runtimes, background servers, or containerization.
| Component | Role |
|---|---|
| PySide6 (Qt) | Native windowing, hotkey overlays, audio output subsystem, OS drag-and-drop. |
| soundfile (libsndfile) | Low-level C-based PCM stream decoding and waveform sample extraction. |
| NumPy | SIMD-vectorized waveform peak calculations and buffer downsampling. |
| pydub + tinytag | Audio header inspection, container metadata parsing, and format transcoding. |
| SQLite 3 | Embedded local relational database for indexed audio cataloging. |
| sentry-sdk | Optional unhandled crash reporting. Strictly opt-out via app settings. |
Storage & Data Isolation
- Data Locations: Database records and cache files reside exclusively within standard OS user-data directories (
%APPDATA%on Windows,~/Library/Application Supporton macOS,~/.configon Linux). - Non-Destructive Access: User audio folders are read in read-only mode during indexing. No source files are modified, tagged, or renamed on disk.
- Audio Snippet Dragging: Waveform trimming generates isolated temporary audio clips in a scratch directory; master files remain untouched.
Network & Privacy Policies
- 100% Offline Core Operation: Searching, indexing, waveform rendering, and timeline drag-and-drop operate entirely offline without internet connectivity.
- No Content Telemetry: Audio waveforms, file paths, sound library names, and project assets are never transmitted to any external server.
- Crash Reports (Optional): When enabled, error reports capture only anonymized execution stack traces with
send_default_pii=False. Telemetry can be toggled off at any time in Settings (telemetry_enabled: false).
Development Context
MySoundLib was created independently by Thiago Neppel (video editor and graphic designer) to resolve workflow bottlenecks in post-production environments. Built using modern development workflows and AI-assisted programming tools for code generation and automated testing.