jupyter

library1.1.1pypypiunverified

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.

ai-ml data

pip install jupyter

package ↗homepage ↗

Install & Compatibility

Where this runs

tested against v1.1.1 · pip install

no network on importno background threads

Install × environment matrix

Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux

musl

glibc

py 3.10

4/6 runs

py 3.11

4/6 runs

py 3.12

4/6 runs

py 3.13

4/6 runs

py 3.9

4/6 runs

Code

Verified usage

Verified import paths — ran on the pinned version, not inferred.

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.

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

jupyter --version

Debug

Known issues

gotchaThe 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.

affects: All versions

gotchaThe `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.

affects: All versions

gotchaWhile `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.

affects: All versions

gotchaJupyterLab, 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.

affects: All versions of JupyterLab

breakingMigrating 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.

affects: Users upgrading from environments with JupyterLab < 4 to JupyterLab >= 4.

gotchaExecuting `jupyter notebook` or `jupyter lab` directly as a Python statement within a `.py` script will result in a `SyntaxError`. These are shell commands designed to be run in a terminal.

fix

To invoke Jupyter Notebook or JupyterLab from a Python script, use `subprocess.run(['jupyter', 'notebook'])` or `os.system('jupyter notebook')`.

affects: All versions

gotchaThe `jupyter` command and its subcommands (e.g., `jupyter notebook`, `jupyter lab`) are shell commands, not Python functions or statements. Attempting to execute them directly within a Python script will result in a `SyntaxError`.

fix

To execute `jupyter` commands from within a Python script, use modules like `subprocess` (e.g., `import subprocess; subprocess.run(['jupyter', 'notebook'])`) or ensure they are run directly in a shell environment.

affects: All versions

Upgrade

Version history

1.1.1latest on PyPI

Audit

Dependencies

ipykernelrequiredProvides the Python kernel for executing code in notebooks.

ipywidgetsrequiredEnables interactive widgets in Jupyter notebooks.

jupyter-consolerequiredProvides a terminal-based Jupyter client.

jupyterlabrequiredThe next-generation web-based user interface for Project Jupyter (added in metapackage v1.1).

notebookrequiredThe classic Jupyter Notebook interface.

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