Jupyter Metapackage

1.1.1 · active · verified Sun Apr 05

The `jupyter` package is a metapackage designed for user convenience, providing a single command to install core Project Jupyter components like Jupyter Notebook, JupyterLab, and the IPython Kernel. It is an empty package that simply declares dependencies on other Jupyter projects, rather than providing direct functionality itself. The current version is 1.1.1, released on August 30, 2024. While the metapackage version updates infrequently, installing it typically pulls in the latest stable versions of its constituent components.

Warnings

gotcha The version number of the `jupyter` metapackage (e.g., 1.1.1) updates rarely and does not reflect the versions of its underlying components like JupyterLab or Jupyter Notebook. Installing `jupyter` will pull in the latest stable versions of these components (e.g., JupyterLab 4+ and Notebook 7+).
Fix: Refer to the individual component packages (e.g., `jupyterlab`, `notebook`) for their specific version numbers and changelogs if precise versioning is required. Use `pip show jupyterlab` or `pip show notebook` to check installed versions.
gotcha The `jupyter` metapackage is strictly for end-user installation convenience and should NOT be listed as a dependency in `setup.py`, `pyproject.toml`, or `requirements.txt` for other Python packages. Instead, explicitly list the specific Jupyter components your project requires (e.g., `jupyterlab`, `notebook`).
Fix: When defining project dependencies, specify individual Jupyter components (e.g., `jupyterlab>=4.0`, `notebook>=7.0`) instead of the `jupyter` metapackage.
gotcha While `pip install jupyter` installs both, users should understand the differences between the classic Jupyter Notebook and JupyterLab. JupyterLab is the 'next-generation' IDE-like interface with more features, flexibility, and extensibility, whereas Jupyter Notebook offers a simpler, single-document experience.
Fix: For complex projects requiring multiple files, terminals, or advanced features, prefer starting with `jupyter lab`. For simpler, sequential notebook tasks, `jupyter notebook` might suffice.
gotcha JupyterLab, due to its richer feature set and IDE-like environment, can be more resource-intensive (in terms of memory and CPU) than the classic Jupyter Notebook. Users on resource-constrained systems might experience slower performance.
Fix: If experiencing performance issues, consider using the classic Jupyter Notebook (`jupyter notebook`) for simpler tasks or ensure your system meets the recommended specifications for JupyterLab.
breaking Migrating from JupyterLab 3 to JupyterLab 4 (which the current `jupyter` metapackage will install) can introduce breaking changes for existing lifecycle configurations or Jupyter/JupyterLab extensions due to significant package version updates within the ecosystem (e.g., Jupyter Notebook 6.x to 7.x).
Fix: Review the official JupyterLab 4 migration guide. Be prepared to update or re-install extensions, and test any custom configurations thoroughly after upgrading.

Install

pip install jupyter Install Jupyter

Imports

Not Applicable

The 'jupyter' metapackage is not intended for direct Python imports. Users should import symbols from specific components like 'notebook', 'jupyterlab', or 'ipykernel' (e.g., `from notebook.notebookapp import NotebookApp`).

The 'jupyter' package is a metapackage for installation convenience; it does not expose Python symbols for direct use.

Quickstart

After installing the `jupyter` metapackage, launch either the classic Jupyter Notebook or the modern JupyterLab interface from your terminal.

# After installation:
# To start the classic Jupyter Notebook interface:
jupyter notebook

# To start the JupyterLab interface:
jupyter lab

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