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‎Dockerfile

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# Use an official Python runtime as a parent image
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FROM python:3.8-slim
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# Set the working directory in the container
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WORKDIR /app
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# Copy the Python scripts and the entrypoint script into the container
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COPY drawio2clab.py /app/
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COPY clab2drawio.py /app/
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COPY requirements.txt /app/
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COPY entrypoint.sh /app/
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# Install any needed packages specified in requirements.txt
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RUN pip install --no-cache-dir -r requirements.txt
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# Make the entrypoint script executable
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RUN chmod +x /app/entrypoint.sh
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# Use the entrypoint script to handle script execution
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ENTRYPOINT ["/app/entrypoint.sh"]
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# CMD can be used to specify default arguments or left as it is to pass commands through the docker run command

‎LICENSE

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MIT License
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Copyright (c) 2024 FloSch62
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal
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in the Software without restriction, including without limitation the rights
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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copies of the Software, and to permit persons to whom the Software is
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furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in all
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copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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SOFTWARE.

‎README.md

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# clab-io-draw
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The `clab-io-draw` project unifies two tools, `clab2drawio` and `drawio2clab`. These tools facilitate the conversion between [Containerlab](https://github.com/srl-labs/containerlab) YAML files and Draw.io diagrams, making it easier for network engineers and architects to visualize, document, and share their network topologies.
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![Drawio Example](img/drawio1.png)
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## clab2drawio
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`clab2drawio` is a Python script that automatically generates Draw.io diagrams from Containerlab YAML configurations. It aims to simplify the visualization of network designs by providing a graphical representation of container-based network topologies.
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For detailed information on `clab2drawio`, including features, options, and usage instructions, please refer to the [clab2drawio.md](clab2drawio.md) file located in the same directory as this README.
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## drawio2clab
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`drawio2clab` is a Python script that converts Draw.io diagrams into Containerlab-compatible YAML files. This tool is designed to assist in the setup of container-based networking labs by parsing .drawio XML files and generating structured YAML representations of the network.
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For more details on `drawio2clab`, including features, constraints for drawing, and how to run the tool, please see the [drawio2clab.md](drawio2clab.md) file in this directory.
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# Quick Usage
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## Running with Docker
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To simplify dependency management and execution, the tools can be run inside a Docker container. Follow these instructions to build and run the tool using Docker.
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### Pulling from dockerhub
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```bash
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docker pull flosch62/clab-io-draw:latest
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```
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### Building the Docker Image by yourself
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Navigate to the project directory and run:
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```bash
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docker build -t clab-io-draw .
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```
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This command builds the Docker image of clab-io-draw with the tag clab-io-draw, using the Dockerfile located in the docker/ directory.
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### Running the Tools
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Run drawio2clab or clab2drawio within a Docker container by mounting the directory containing your .drawio/.yaml files as a volume. Specify the input and output file paths relative to the mounted volume:
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```bash
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docker run -e SCRIPT_NAME=clab2drawio.py -v "$(pwd)":/data flosch62/clab-io-draw -i /data/lab-examples/clos03/cfg-clos.clab.yml -o /data/output.drawio
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```
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```bash
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docker run -e SCRIPT_NAME=drawio2clab.py -v "$(pwd)":/data flosch62/clab-io-draw -i /data/output.drawio -o /data/lab-examples/clos03/cfg-clos.clab.yml
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```
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Replace your_input_file.drawio and your_output_file.yaml with the names of your actual files. This command mounts your current directory to /data inside the container.
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## Running locally
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### Requirements
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- Python 3.6+
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### Installation
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#### Virtual Environment Setup
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It's recommended to use a virtual environment for Python projects. This isolates your project dependencies from the global Python environment. To set up and activate a virtual environment:
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```bash
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python3 -m venv venv
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source venv/bin/activate
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```
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#### Installing Dependencies
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After activating the virtual environment, install the required packages from the requirements.txt file:
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```bash
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pip install -r requirements.txt
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```
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# Usage
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This section provides a brief overview on how to use the `drawio2clab` and `clab2drawio` tools. For detailed instructions, including command-line options and examples, please refer to the dedicated usage sections in their respective documentation files.
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Detailed Usages: [drawio2clab.md](drawio2clab.md#usage) and [clab2drawio.md](drawio2clab.md#usage)
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## drawio2clab
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```bash
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python drawio2clab.py -i <input_file.drawio> -o <output_file.yaml>
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```
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`-i, --input`: Specifies the path to your input .drawio file.
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`-o, --output`: Specifies the path for the output YAML file.
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Make sure to replace `<input_file.drawio>` with the path to your .drawio file and `<output_file.yaml>` with the desired output YAML file path.
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For more comprehensive guidance, including additional command-line options, please see the Usage section in [drawio2clab.md](drawio2clab.md#usage)
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## clab2drawio
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```bash
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python clab2drawio.py -i <input_file.yaml> -o <output_file.drawio>
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```
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`-i, --input`: Specifies the path to your input YAML file.
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`-o, --output`: Specifies the path for the output drawio file.
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Make sure to replace `<input_file.yaml>` with the path to your .drawio file and `<output_file.drawio>` with the desired output YAML file path.
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For more comprehensive guidance, including additional command-line options, please see the Usage section in [clab2drawio.md](clab2drawio.md#usage)

‎clab2drawio.md

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# clab2drawio
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`clab2drawio` is a tool designed to automatically generate network topology diagrams from [Containerlab](https://github.com/srl-labs/containerlab) YAML files, rendering them into visually appealing diagrams using Draw.io. This tool simplifies the process of visualizing network designs and configurations, making it easier for network engineers and architects to document and share their containerlab environments.
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![Drawio ](img/drawio1.png)
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## Features
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- **Automatic Diagram Generation**: Converts containerlab YAML configurations into detailed Draw.io diagrams in vertical and horizontal layouts.
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- **Intelligent Node Placement**: Attempts to determine the best placement for nodes automatically. However, for complex topologies, this can be challenging.
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- **Graph-level-Based Layout**: Organizes nodes into graph-level based on their connectivity for clearer topology visualization. Users can influence node placement by specifying graph-level directly in the containerlab configuration.
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- **Graph-icon Support**: Enhances node visualization by allowing users to specify graph-icon labels such as router, switch, or host to define custom icons for nodes in the generated diagrams.
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- **Customizable Styles**: Supports customization of node and link styles within the diagrams.
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## Installation
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Clone the repository to your local machine:
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```bash
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git clone https://github.com/FloSch62/clab2drawio.git
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cd clab2drawio
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```
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Ensure you have Python 3.x installed on your system. You can then install the required dependencies:
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```bash
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pip install -r requirements.txt
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```
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## Usage
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To generate a network topology diagram from a containerlab YAML file, run the following command:
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```bash
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python clab2drawio.py -i <path_to_your_yaml_file> -o <path_to_output_file>
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```
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The output will be a Draw.io diagram file saved in the output path. You can open this file with Draw.io to view and further edit your network topology diagram.
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## Advanced Usage
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### Influencing Node Placement
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The tool attempts to automatically determine the best placement for nodes. However, achieving an optimal layout for complex topologies might be challenging. You can influence node placement behavior through the `graph-level` and `graph-icon` labels in the containerlab file, which supports both vertical and horizontal layouts. The `graph-level` label impacts the placement of nodes along the primary axis of the chosen layout A lower `graph-level` number (e.g., `graph-level: 1`) indicates a position towards the start of the canvas, while a higher number places the node further along the primary axis. This feature allows you to suggest a specific hierarchy for each node, aiding the tool in organizing the topology more effectively.
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Example configuration to set node graph-level:
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```bash
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client1:
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kind: "linux"
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labels:
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graph-level: 1 # This node will be placed towards the top of the canvas
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graph-icon: host # This node will use the client icon
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```
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```bash
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spine1:
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kind: "linux"
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labels:
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graph-level: 2 # This node will be placed below graph-level 1 nodes on the canvas
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graph-icon: switch # This node will use the switch icon
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```
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Using graph-level helps manage the vertical alignment of nodes in the generated diagram, making it easier to visualize the hierarchical structure of your network.
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### Command-Line Arguments
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`clab2drawio` supports several command-line arguments to customize the diagram generation process. Use these arguments to fine-tune the output according to your specific requirements:
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- `-i, --input`: Specifies the filename of the input file. This file should be a containerlab YAML for diagram generation. This argument is required.
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```bash
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python clab2drawio.py -i <path_to_your_yaml_file>
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```
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- `-o, --output`: Specifies the output file path for the generated diagram in draw.io format. This argument is required.
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```bash
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python clab2drawio.py -i <path_to_your_yaml_file> -o <path_to_output_file>
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```
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- `--include-unlinked-nodes`: Include nodes without any links in the topology diagram. By default, only nodes with at least one connection are included.
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- `--no-links`: Do not draw links between nodes in the topology diagram. This option can be useful for focusing on node placement or when the connectivity between nodes is not relevant.
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- `--layout`: Specifies the layout of the topology diagram (either `vertical` or `horizontal`). The default layout is `vertical`.
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- `--verbose`: Enable verbose output for debugging purposes.
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## Customization
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The tool allows for basic customization of node and link styles within the generated diagram. To customize, edit the custom_styles dictionary within the clab2drawio.py file according to your preferences.

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