Docs request (feature request?): Using ipympl when Jupyter and kernel are in different environments

Describe the issue

This issue is a continuation from https://github.com/matplotlib/ipympl/issues/112.

A very common use case involves a centrally-installed Jupyter instance running Jupyter kernels in various task-specific environments.

Examples include a shared Jupyterlab instance installed by a server administrator, or a single user with a highly-customized personal Jupyter configuration.

In these situations, it's usually undesirable (and sometimes impossible) for users to install and run Jupyter within their task-specific environment in order to make use of ipympl as per the official recommendation to use pip install ipympl for both the server/kernel-side package and the client/frontend-side extension.

What are the correct instructions for installing the "frontend" and "backend" components of ipympl separately, so that they can be used in two different environments?

If this is not currently a supported use case, consider this issue a much-desired feature request!

Beginnen Sie mit der Durchsicht des verlinkten ipympl-Issues 112 und der aktuellen offiziellen Installationsempfehlung. Ermitteln Sie, ob Jupyter- und Kernel-Umgebungen separat unterstützt werden können, und dokumentieren Sie anschließend die korrekten frontend/backend-Anweisungen oder geben Sie klar an, dass dieser Anwendungsfall nicht unterstützt wird.