https://github.com/srl-labs/clab-io-draw
Containerlab and Draw.io Integration
https://github.com/srl-labs/clab-io-draw
containerlab drawio grafana
Last synced: about 1 month ago
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Containerlab and Draw.io Integration
- Host: GitHub
- URL: https://github.com/srl-labs/clab-io-draw
- Owner: srl-labs
- License: mit
- Created: 2024-03-17T11:57:14.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2025-03-02T13:00:26.000Z (2 months ago)
- Last Synced: 2025-04-05T22:08:19.326Z (about 1 month ago)
- Topics: containerlab, drawio, grafana
- Language: Python
- Homepage:
- Size: 2.59 MB
- Stars: 47
- Watchers: 3
- Forks: 8
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# clab-io-draw
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.
## Overview
| Tool | Description |
| :-----------: | :------------------------------------------------------------------------------------------------: |
| **clab2drawio** | Converts Containerlab YAML files into Draw.io diagrams (with optional [Grafana](docs/grafana.md) support). |
| **drawio2clab** | Converts Draw.io diagrams back into Containerlab-compatible YAML files, supporting quick lab setup.|
> [!NOTE]
> For detailed information on `clab2drawio`, options, and usage instructions, please refer to the [clab2drawio.md](docs/clab2drawio.md)
> [!NOTE]
> For more details on `drawio2clab`, including features, constraints for drawing, and how to run the tool, please see the [drawio2clab.md](docs/drawio2clab.md)
## Quick Usage
### Running with Containerlab
```bash
containerlab graph --drawio -t topo.clab.yml
containerlab graph --drawio -t topo.clab.drawio
```
> [!TIP]
> The `containerlab graph --drawio` command simplifies your workflow by automatically detecting the input file type (`.yml` or `.drawio`) and running the appropriate script internally (`clab2drawio` or `drawio2clab`).
>
> You can also enhance your output by passing additional arguments. For example:
> ~~~bash
> sudo containerlab graph --drawio -t topo.clab.yml --drawio-args "--theme nokia_modern"
> ~~~
> This example applies the "nokia_modern" theme to your generated diagram.
### Running with Docker
You can also use a Docker container for a quick start without installing Python and other dependencies locally.
#### Pulling from Container registry
```bash
docker pull ghcr.io/srl-labs/clab-io-draw:latest
```
#### Running the Tools
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:
```bash
docker run -it -v "$(pwd)":/data ghcr.io/srl-labs/clab-io-draw -i lab-examples/br01.clab.yml
```
> [!NOTE]
> The `-it` option is used for interactive mode (`-I`).
> If you do not need interactive prompts, you can omit `-it`.
```bash
docker run -v "$(pwd)":/data ghcr.io/srl-labs/clab-io-draw -i output.drawio
```
Replace `your_input_file.drawio` or `your_output_file.yaml` with the
actual file names in your environment.
## Running locally
> [!IMPORTANT]
> Python 3.11+ is required if you prefer running these tools locally.
### Installation
> [!TIP]
> **Why uv?**
> [uv](https://docs.astral.sh/uv) is a single, ultra-fast tool that can replace `pip`, `pipx`, `virtualenv`, `pip-tools`, `poetry`, and more. It automatically manages Python versions, handles ephemeral or persistent virtual environments (`uv venv`), lockfiles, and often runs **10–100× faster** than pip installs.
1. **Install uv** (no Python or Rust needed):
```
# On macOS and Linux
curl -LsSf https://astral.sh/uv/install.sh | sh
```
2. **Run the tool** (uv automatically installs dependencies in a venv from `pyproject.toml`):
```
uv run python clab2drawio.py --help
```
## Alternative: Using pip
If you’d rather use pip or can’t install uv:
1. **(Optional) Create & Activate a Virtual Environment**:
```
python -m venv venv
source venv/bin/activate
```
2. **Installing Dependencies**
After activating the virtual environment, install the required packages from the requirements.txt file:
```bash
pip install -r requirements.txt
```
> [!NOTE]
> If you installed dependencies using pip instead of uv, simply run the commands using `python` directly instead of `uv run python`
# Usage
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.
Detailed Usages: [drawio2clab.md](docs/drawio2clab.md#usage) and [clab2drawio.md](docs/clab2drawio.md#usage)
## drawio2clab
```bash
uv run python drawio2clab.py -i
```
- `-i, --input`: path to your `.drawio` file.
- `-o, --output`: path to your output `.yaml` file (optional).
> [!NOTE]
> For more details on node-label constraints, usage examples, and additional
> command-line options, refer to
> [drawio2clab.md](docs/drawio2clab.md#usage).
## clab2drawio
```bash
uv run python clab2drawio.py -i
```
- `-i, --input`: path to your Containerlab YAML file.
- `-o, --output`: path to your output `.drawio` file (optional).
> [!NOTE]
> For advanced functionality—like
> [Grafana Dashboard](docs/grafana.md) generation (`-g, --gf_dashboard`),interactive mode (`-I`), layout customizations, or theming (`--theme`) refer to [clab2drawio.md](docs/clab2drawio.md#usage).
## Contributions & Feedback
All feedback and contributions are welcome! If you have suggestions, please open an issue or pull request on the GitHub repository.
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