Document upgrade process to Flower 1.0 (#1305)

doc/source/index.rst

@@ -47,6 +47,7 @@ Flower's design goals was to make this simple. Read on to learn more.
    example-jax-from-centralized-to-federated
    fedbn-example-pytorch-from-centralized-to-federated
    recommended-env-setup
+   upgrade-to-flower-1.0
    changelog
    faq
 

doc/source/upgrade-to-flower-1.0.rst

@@ -0,0 +1,28 @@
+Upgrade to Flower 1.0
+=====================
+
+Flower 1.0 is finally here! Along with new features, Flower 1.0 provides a stable foundation for future growth. Compared to Flower 0.19 (and other 0.x series releases), there are a few breaking changes that might make it necessary to change the code of existing 0.x-series projects.
+
+Install update
+--------------
+
+Install the latest version of Flower using `python -m pip install -U flwr` (or `python -m pip install -U flwr[simulation]`).
+
+Required changes
+----------------
+
+A few breaking changes require small manual updates:
+
+- Subclasses of ``NumPyClient``: change ``def get_parameters(self):``` to ``def get_parameters(self, config):``
+- Subclasses of ``Client``: change ``def get_parameters(self):``` to ``def get_parameters(self, ins: GetParametersIns):``
+- Rename ``parameters_to_weights`` to ``parameters_to_ndarrays`` and ``weights_to_parameters`` to ``ndarrays_to_parameters``
+- ``start_simulation``: change ``num_rounds=1`` to ``config={"num_rounds": 1}``
+- Strategy initialization: if the strategy relies on the default values for ``fraction_fit`` and ``fraction_eval``, set ``fraction_fit`` and ``fraction_eval`` manually to ``0.1``. Projects that do not manually create a strategy (by calling ``start_server`` or ``start_simulation`` without passing a strategy instance) should now initialize FedAvg with ``fraction_fit`` and ``fraction_eval`` set to ``0.1``.
+
+Optional improvements
+---------------------
+
+Along with the necessary changes above, there are a number of potential improvements that just became possible:
+
+- Remove "placeholder" methods from subclasses of ``Client`` or ``NumPyClient``. If you, for example, use server-side evaluation, then empy placeholder implementations of ``evaluate`` are no longer necessary.
+- Configure the round timeout via ``start_simulation``: ``start_simulation(..., config={"num_rounds": 3, "round_timeout": 600.0}, ...)``