Jupyter-resource-usage

For classic notebook users, there shouldn't be any major change or action to take. The classic notebook extension is still distributed with the Python package as before.

For JupyterLab 2.x users you will still need to use the previous `nbresuse` package. See below for more information.

For JupyterLab 3.x, the status bar item is now packaged in its own extension and distributed with the `jupyter-resource-usage` package. This means that a single `pip install jupyter-resource-usage` is enough to install the server extension, the classic notebook extension and the JupyterLab extension all at once.

To upgrade to the latest version:


python -m pip install -U nbresuse


If you use the classic notebook, there shouldn't be anything to do. The classic notebook extension already uses the new endpoint and is automatically installed.

If you use JupyterLab 2.x and want the memory usage indicator in the status bar to continue showing metrics:


Two options:

- continue using `nbresuse==0.3.6` instead of `0.4.0`
- enable the deprecated `/metrics` endpoint with:

bash
jupyter lab --ResourceUseDisplay.disable_legacy_endpoint=False

- Fix handling of cpu percent in the API endpoint [56](https://github.com/jupyter-server/jupyter-resource-usage/pull/56)
- Added Binder [53](https://github.com/jupyter-server/jupyter-resource-usage/pull/53) & RELEASE.md [#54](https://github.com/jupyter-server/jupyter-resource-usage/pull/54)

- Adding support for jupyterlab statusbar-extension [45](https://github.com/jupyter-server/jupyter-resource-usage/pull/45) [#36](https://github.com/jupyter-server/jupyter-resource-usage/issues/36)

**Note**: this release restores the `/metrics` endpoint returning a JSON response, that was removed in `0.3.4`.

- Autoformatting and documentation [33](https://github.com/jupyter-server/jupyter-resource-usage/pull/33)
- Add section about CPU usage to the README [30](https://github.com/jupyter-server/jupyter-resource-usage/pull/30)
- Make psutil optional dependency of NBResuse [25](https://github.com/jupyter-server/jupyter-resource-usage/pull/25)
- Report the memory usage metrics as prometheus metrics [22](https://github.com/jupyter-server/jupyter-resource-usage/pull/22)

**Note**: this release removed the `/metrics` endpoint that was returning a JSON response. As a result, JupyterLab does not display the memory usage indicator in the status bar with `nbresuse==0.3.4`.

- Made memory limit possibly dynamic via passing a callable in the config. [23](https://github.com/jupyter-server/jupyter-resource-usage/pull/23)
- Track CPU usage [21](https://github.com/jupyter-server/jupyter-resource-usage/pull/21)