Local evaluation with multiprocessing environment

## What
When running the client with local evaluation in a gunicorn server (or any multiprocessed environment), the workers environment is never updated

## Why
Gunicorn is designed around the pre-fork worker model (see [docs](https://docs.gunicorn.org/en/stable/design.html#server-model)). When instantiating the Flagsmith client, the polling updates the `_environment` variable in the master worker, but these changes will not affect the other workers. We would need to run a polling thread for each worker, which is not ideal

## Sharing the `_environment` between workers
Would you be open to a new feature that would allow pickling and sharing the data between processes using a [multiprocessing.Manager](https://docs.python.org/3/library/multiprocessing.html#multiprocessing.Manager) or a redis?