Docker Sandbox Runner for ComfyUI

This Custom Node provides a secure, isolated execution environment for Python scripts within ComfyUI, utilizing persistent Docker containers. Code execution is ultra-fast (milliseconds) and completely isolated from the host operating system.

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Key Features

• Maximum Security (Docker Isolation): Code runs in an ephemeral Docker container, blocked from accessing the Host's filesystem, network, or sensitive resources.
• Performance (Sidecar Pattern): The container is started only once (the Sidecar pattern) and reused via docker exec, eliminating Docker boot time latency.
• Dynamic Inputs: Allows adding execution inputs (*, STRING, INT, etc.) dynamically via the context menu.
• Multiple Outputs: Provides 6 result outputs (r1 to r6) and 1 log output (log).
• Non-Root Execution: Code runs as the nobody user inside the container, significantly minimizing internal security risk.

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Installation

1. Mandatory Prerequisites

You must have two pieces of software installed:

• Docker Desktop/Engine: The containerization engine itself.
• docker-py: The Python library to control Docker.

Execute the following command in your ComfyUI Python environment:

# Installs the Python library required to communicate with the Docker daemon
pip install docker

2. Node Installation

1. Clone this repository into your ComfyUI's custom_nodes folder:

   cd path/to/ComfyUI/custom_nodes/
   git clone https://github.com/fabioamigo/ComfyUI-DockerSandbox.git

2. Restart ComfyUI.

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Docker Engine Installation (Detailed CLI Instructions)

You must install and start the Docker service (Daemon) before using the node. Note: After installation, ensure your user is added to the docker group to run commands without sudo (e.g., sudo usermod -aG docker $USER).

OS / Distribution	Installation Command Set (Root/Sudo Required)	Verification & Service
Ubuntu/Debian	1. Install Prerequisites: sudo apt update && sudo apt install ca-certificates curl gnupg 2. Add GPG Key: sudo install -m 0755 -d /etc/apt/keyrings curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo gpg --dearmor -o /etc/apt/keyrings/docker.gpg 3. Add Repository: echo "deb [arch=$(dpkg --print-architecture) signed-by=/etc/apt/keyrings/docker.gpg] https://download.docker.com/linux/ubuntu $(lsb_release -cs) stable" | sudo tee /etc/apt/sources.list.d/docker.list > /dev/null 4. Install Docker: sudo apt update && sudo apt install docker-ce docker-ce-cli containerd.io docker-buildx-plugin docker-compose-plugin	sudo systemctl enable docker --now
Arch/Manjaro	1. Install Package: sudo pacman -Syu docker 2. Start Service: sudo systemctl start docker.service	sudo systemctl status docker.service
Fedora/RHEL	1. Install Package: sudo dnf -y install docker-ce docker-ce-cli containerd.io --repo docker-ce --repo docker-ce-stable 2. Start Service: sudo systemctl start docker	sudo systemctl enable docker --now
macOS	Install Docker Desktop (Recommended): Download the official .dmg installer from the Docker website.	Start the application. CLI tools (docker) are installed automatically.
Windows	Install Docker Desktop (Recommended): Download the official installer from the Docker website. Prerequisite: Ensure WSL 2 is installed and enabled for optimal performance.	Start the application. Verify in PowerShell: docker info

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Clarification on Windows Installation

WSL 2 and Windows: Docker Desktop for Windows uses a lightweight Linux virtual machine (VM) powered by WSL 2 by default. This VM hosts the Docker Engine. Therefore, while you install the Desktop app, you must have WSL 2 enabled for the container engine to function correctly and offer the best performance.

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Usage Guide

1. Add the Node

Find "Docker Sandbox Runner" in the Advanced/Scripting menu.

2. Define Inputs

1. Code (code): Insert your Python script. The desired outputs must be assigned to variables r1 through r6.
2. Dynamic Inputs: Right-click the node and use "+ Add Input (Dynamic)" to inject variables (e.g., my_int (INT)).

3. Example Code

# Access the injected variable "my_value" from the input slot
# Libraries like math, random, json, re, time are pre-loaded.

import math 

if my_value > 50:
    r1 = "Processed successfully."
    r2 = my_value * math.pi
else:
    r1 = "Value too low."
    r2 = None

4. Resource Management

The persistent container comfyui-sandbox-worker will run until explicitly stopped.

• To Stop Consumption: Stop the container manually via the Docker Desktop GUI or by CLI:

  docker stop comfyui-sandbox-worker

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License

This project is licensed under the MIT License.

MIT License

Copyright (c) 2025 [Your Name or Project Name]

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of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
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copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.