LECC · Linked Electronic Communication Core

Linked Electronic Communication Core (LECC) is a modular Python framework for communication across multiple protocols, drawing inspiration from Ray Kurzweil's vision in The Age of Spiritual Machines. In the book, Kurzweil imagines a future with a shared electronic communication language, a concept that sparked the idea for this system. LECC enables sending and receiving messages via protocols like HTTP, TCP, UDP, MQTT, UART, I2C, and more, with built-in emulation and failure recovery through the unique Maskpert mechanism.

👁 The creator has tested this successfully, but functionality may vary depending on your system.

Features

• 🌐 Multi-Protocol Support: Compatible with UART, HTTP, TCP, UDP, WebSocket, FTP, MQTT, I2C, Ethernet, Bluetooth, and Zigbee.
• 🔄 Automatic Emulation: Activates an emulator if a protocol fails due to missing hardware or connectivity issues.
• 👺 Maskpert: A smart routing and rescue system ensuring message delivery using alternative protocols when the primary one fails.
• 🧩 Modular and Extensible: Easy to add new protocols or customize existing ones.
• ⚡ Concurrency: Uses threading to handle simultaneous communications without blocking.
• 💪 Resilience: Automatic retries and failed message queues to guarantee delivery.

What Does It Achieve?

LECC provides a unified system for connecting heterogeneous devices and services. It's perfect for IoT projects, automation, network testing, or any application requiring protocol interoperability.

What is Maskpert?

Maskpert 👺 (Masked Expert) is LECC's intelligent failure management system:

• 🎯 Dynamic Routing: Sends messages across all available protocols and confirms success with a priority protocol (HTTP or TCP by default).
• 🧰 Message Rescue: Retrieves failed messages from a queue and resends them via available alternative protocols.

This ensures messages reach their destination even under network or hardware failures.

Installation

Requirements

• Python 3.7 or higher
• Operating System: Tested on Linux (may require adjustments for Windows/macOS)

Dependencies

Install the required libraries with:

pip install -r requirements.txt

See requirements.txt for the full list.

Steps

1. Clone the repository:

   git clone https://github.com/[your-username]/lecc-universal-system.gitcd lecc-universal-system
   

2. Install dependencies:

   pip install -r requirements.txt
   

3. Run the system:

   python3 lecc.py
   

Usage

1. Configuration: Edit protocol_configs in lecc.py to adjust ports, hosts, or URLs for your environment:

   protocol_configs = {    "http": {"port": 5000, "host": "localhost", "url": "http://localhost:5000/api/data"},    "tcp": {"port": 65433, "host": "127.0.0.1"},    # ...}
   

2. Execution: Running the script initializes all modules, tests availability, and sends a test message.

3. Expected Output:

   LECC Universal System CompleteStarting HTTP server: Running on all addresses (0.0.0.0) ||| http://127.0.0.1:5000Available (11): ['uart', 'http', 'tcp', ...]Sending from tcp: Automatic test messageSent with maskpert via uart, http, tcp, ..., success with httpLECC System Running...
   

4. Customization: Add your own logic in LECCCore.route_message() to process received messages.

Example

Send a custom message by modifying main():

core.route_message({"data": "Hello world", "destination_protocol": "http"})

Output:

Sending from http: Hello worldSent with maskpert via ..., success with http

Important Notes

• MQTT: Requires a broker (e.g., Mosquitto) on localhost:1883. If unavailable, it switches to emulation.
• UART/I2C: Needs connected hardware (e.g., /dev/ttyUSB0). Without hardware, it simulates.
• Ports: Ensure configured ports are free.

Contributing

Contributions are welcome! Please:

1. Fork the repository.
2. Create a branch (git checkout -b feature/new-feature).
3. Submit a pull request.

License

Distributed under the MIT License. See LICENSE for details.

Credits

	Name	Role	GitHub
	Alejo	Author & Development	@alejomalia

Inspired by The Age of Spiritual Machines by Ray Kurzweil. Developed with assistance from Grok3, created by xAI.