RENDA

RENDA is a high-fidelity media identification, enrichment, and physical organization pipeline designed for large-scale video libraries. It automates the process of scanning raw media files, matching them against online databases, and reorganizing them into a standardized filesystem structure.

Core Features

• Automated Scanning: Recursive discovery of video files and associated extras (subtitles, images, NFOs).
• Metadata Enrichment: Integration with TMDB API for multi-language metadata, posters, and person profiles.
• Intelligent Formatting: Customizable naming templates for movies, series, seasons, and episodes using advanced parsing (GuessIt).
• Extra File Handling: Automatic linkage and renaming of supplementary files based on the primary media item.
• Hardware Accelerated Probing: Fast FFprobe integration for technical media analysis (codecs, bitrates, resolution).
• Robust Database Tracking: Highly indexed, ACID-compliant SQLite database with SQLAlchemy ORM for managing file states, matches, and configurations.
• Safe Operations: Integration with Send2Trash for safe file deletion during reorganization.
• Modular Architecture: Cleanly separated backend logic (FastAPI) and modern, scalable frontend UI (React inside Electron).

Technical Stack

Backend

• Language: Python 3.10+
• Framework: FastAPI (with Uvicorn)
• Database: SQLite via SQLAlchemy ORM
• Parsing & Image Processing: GuessIt, Pillow
• Metadata: TMDB API (via Requests)
• Probing: FFmpeg / FFprobe
• Utils: python-dotenv, colorama, Send2Trash

Frontend

• Framework: React 18+ (Vite)
• State Management: React Context API
• Styling: Custom CSS with modern UI/UX principles
• Platform: Electron (for native filesystem access and IPC)

Architecture Overview

The application is strictly divided into modular domains:

Backend (app/)

• api/routes: Modular FastAPI endpoints for scanner, media management, metadata, and settings.
• db/models: Segmented SQLAlchemy models (media, metadata, action logs, persons).
• scanner: Directory traversal, metadata parsing, and API enrichment logic.
• formatter: Formatting engine for determining planned paths for movies and TV series.

Frontend (frontend/src/)

• components/: Modular React components grouped by feature (Discovery, Navigation, Modals).
• context/: Centralized state management via AppContext.
• locales/: i18n localization support.

Prerequisites

Before running the application, ensure you have the following installed:

• Node.js (version 18 or higher)
• Python 3.10 or higher
• FFmpeg and FFprobe (must be added to the system PATH)

Installation and Execution

1. Clone the repository.
2. Install the backend Python dependencies:

   pip install -r requirements.txt

3. Navigate to the frontend directory:

   cd frontend

4. Install the frontend Node.js dependencies:

   npm install

5. Run the development server (this concurrently launches the Python backend, Vite bundler, and Electron application):

   npm run dev