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!

Comece revisando a issue 112 vinculada do ipympl e a recomendação oficial de instalação atual. Determine se os ambientes do Jupyter e do kernel podem ser compatíveis separadamente e, em seguida, documente as instruções corretas de frontend/backend ou declare claramente que esse caso de uso não é compatível.