Installation#

This section provides instructions on how to install DataLab-Kernel.

How to install#

DataLab-Kernel is available in several forms:

As a Python package via Package manager pip
From Installing from source for development

Package manager `pip`#

GNU/Linux Windows macOS

Installing DataLab-Kernel from PyPI:

$ pip install datalab-kernel[cli]

This will install the kernel and all required dependencies including Sigima.

Note

The [cli] extra installs jupyter-client, which is required for the install/uninstall CLI commands. See JupyterLite (browser-based) for environments where this is not needed.

Installing the Jupyter Kernel#

After installing the package, register the kernel with Jupyter:

$ datalab-kernel-install

This makes the “DataLab” kernel available in Jupyter Notebook, JupyterLab, and VS Code.

JupyterLite (browser-based)#

DataLab-Kernel is compatible with JupyterLite, a browser-based Jupyter environment running on WebAssembly.

In JupyterLite, kernels are bundled at build time and the install/uninstall commands are not used. Instead, you load DataLab-Kernel as an IPython extension.

Step 1: Add to your JupyterLite environment

Create or edit your environment.yml:

name: xeus-python-kernel
channels:
  - https://repo.mamba.pm/emscripten-forge
  - conda-forge
dependencies:
  - numpy
  - matplotlib
  - h5py
  - datalab-kernel
  - sigima

Step 2: Load the extension in your notebook

In the first cell of your notebook, load the extension:

%load_ext datalab_kernel

This injects the DataLab namespace (workspace, plotter, sigima, etc.) into your environment, just like the native kernel does.

Why no ``[cli]`` extra?

The [cli] extra includes jupyter-client, which depends on pyzmq (ZeroMQ). Since ZeroMQ requires native sockets unavailable in WebAssembly environments, this dependency is not needed in JupyterLite.

Optional: DataLab Integration#

To enable live mode (synchronization with DataLab), install DataLab:

$ pip install datalab-platform

Or install both together:

$ pip install datalab-kernel[datalab]

Installing from source#

Clone the repository and install in development mode:

$ git clone https://github.com/DataLab-Platform/DataLab-Kernel.git
$ cd DataLab-Kernel
$ pip install -e .

For development with all tools:

$ pip install -e ".[dev]"

Verifying the Installation#

Check that the kernel is properly installed:

from datalab_kernel import Workspace, Plotter
from sigima import create_signal
import numpy as np

# Create workspace
workspace = Workspace()
print(f"Mode: {workspace.mode}")

# Create a test signal
x = np.linspace(0, 10, 100)
y = np.sin(x)
signal = create_signal("Test", x, y)
workspace.add("test", signal)

print(f"Objects: {workspace.list()}")