rda 0.0.1

The rda package provides a Python-based toolkit for automating and managing remote desktop actions, including capturing and replaying keyboard and mouse events

Remote Control Application

Overview

This project provides a Python-based remote control application that allows users to remotely control another computer's mouse and keyboard and view its screen in real-time. It uses sockets for communication, OpenCV for screen display, and pynput for capturing and simulating mouse and keyboard events.

Features

• Remote Mouse and Keyboard Control: Capture and replay mouse movements, clicks, scrolls, and keyboard presses/releases.
• Real-time Screen Sharing: Capture and display the screen in real-time.
• Client-Server Architecture: Connects a client to a server using a base64-encoded code representing the IP and port.

Prerequisites

• Python 3.x
• Poetry for managing dependencies

You can install Poetry by following the instructions on the Poetry installation page.

Installation

1. Clone the repository:

   git clone https://github.com/your-username/remote-control.git
   cd remote-control
   

2. Install the dependencies using Poetry:

   poetry install
   

3. Activate the virtual environment:

   poetry shell
   

Usage

Running the Server

To start the server, run:

poetry run python remote_control.py -s

The server will display a code which can be used by the client to connect.

Running the Client

To start the client, run:

poetry run python remote_control.py -c <code>

Replace <code> with the code provided by the server.

Interactive Mode

If no arguments are provided, the script will prompt you to choose between running as a server or client:

poetry run python remote_control.py

Follow the prompts to run the application.

Code Structure

ActionReplayer Class

Handles the replaying of mouse and keyboard events.

• Attributes:

  • screen_width, screen_height: Screen dimensions.
  • events: List of events to replay.
  • kController: Keyboard controller.
  • mController: Mouse controller.

• Methods:

  • get_key(key_str): Converts a key string to a pynput key object.
  • replay(event): Replays a single event.

ActionRecorder Class

Handles the recording of mouse and keyboard events.

• Attributes:

  • screen_width, screen_height: Screen dimensions.
  • mController: Mouse controller.
  • mouse: Mouse event handler.
  • kController: Keyboard controller.
  • keyboard: Keyboard event handler.

• Methods:

  • on_move(x, y): Handles mouse move events.
  • on_click(x, y, button, pressed): Handles mouse click events.
  • on_scroll(x, y, dx, dy): Handles mouse scroll events.
  • on_press(key): Handles key press events.
  • on_release(key): Handles key release events.

ScreenReplayer Class

Handles the display of screen data.

• Methods:
  • display_image(image_data): Displays the received screen data.
  • stop(): Stops the screen display.

ScreenRecorder Class

Captures and encodes the screen.

• Static Methods:
  • get_screen_image(): Captures the screen and returns the encoded image data.

Host Class

Manages the server-side of the connection.

• Attributes:

  • mouse, keyboard, screen: Sockets for mouse, keyboard, and screen data.

• Methods:

  • create_socket(port): Creates and binds a socket to a given port.
  • connect_socket(server_socket): Listens for and accepts a connection.
  • show_screen(screen_replayer): Continuously receives and displays screen data.
  • handle_mouse(data): Handles mouse data received from the client.
  • handle_keyboard(data): Handles keyboard data received from the client.

Client Class

Manages the client-side of the connection.

• Attributes:

  • mouse, keyboard, screen: Sockets for mouse, keyboard, and screen data.

• Methods:

  • create_socket(ip, port): Creates a socket and connects it to a given IP and port.
  • screen_share(): Continuously captures and sends screen data.
  • handle_mouse(): Continuously receives and replays mouse events.
  • handle_keyboard(): Continuously receives and replays keyboard events.

License

This project is licensed under the MIT License.

Acknowledgments

This project uses the following libraries and resources:

• OpenCV for image processing.
• pynput for capturing and controlling input devices.
• Pillow for image manipulation.
• pyautogui for screen size and resolution detection.

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