Migrate fed kaplan to flwr next (#2996)

Co-authored-by: Daniel J. Beutel <[email protected]>

examples/federated-kaplan-meier-fitter/README.md

@@ -35,7 +35,6 @@ This will create a new directory called `federated-kaplan-meier-fitter` containi
 -- client.py
 -- server.py
 -- centralized.py
--- run.sh
 -- README.md
 ```
 
@@ -68,24 +67,32 @@ pip install -r requirements.txt
 
 ## Run Federated Survival Analysis with Flower and lifelines's KaplanMeierFitter
 
-Afterwards you are ready to start the Flower server as well as the clients. You can simply start the server in a terminal as follows:
+### Start the long-running Flower server (SuperLink)
 
-```shell
-$ python3 server.py
+```bash
+flower-superlink --insecure
 ```
 
-Now you are ready to start the Flower clients which will participate in the learning. To do so simply open two more terminal windows and run the following commands.
+### Start the long-running Flower client (SuperNode)
 
-Start client 1 in the first terminal:
+In a new terminal window, start the first long-running Flower client:
 
-```shell
-$ python3 client.py --node-id 0
+```bash
+flower-client-app client:node_1_app --insecure
 ```
 
-Start client 2 in the second terminal:
+In yet another new terminal window, start the second long-running Flower client:
 
-```shell
-$ python3 client.py --node-id 1
+```bash
+flower-client-app client:node_2_app --insecure
+```
+
+### Run the Flower App
+
+With both the long-running server (SuperLink) and two clients (SuperNode) up and running, we can now run the actual Flower App:
+
+```bash
+flower-server-app server:app --insecure
 ```
 
 You will see that the server is printing survival function, median survival time and saves the plot with the survival function.

examples/federated-kaplan-meier-fitter/centralized.py

@@ -12,5 +12,5 @@
     print(fitter.median_survival_time_)
     fitter.plot_survival_function()
     plt.title("Survival function of fruit flies (Walton's data)", fontsize=16)
-    plt.savefig("./survival_function_centralized.png", dpi=200)
+    plt.savefig("./_static/survival_function_centralized.png", dpi=200)
     print("Centralized survival function saved.")

examples/federated-kaplan-meier-fitter/client.py

@@ -1,4 +1,3 @@
-import argparse
 from typing import Dict, List, Tuple
 
 import flwr as fl
@@ -41,28 +40,26 @@ def fit(
         )
 
 
-if __name__ == "__main__":
-    parser = argparse.ArgumentParser(description="Flower")
-    parser.add_argument(
-        "--node-id",
-        type=int,
-        required=True,
-        help="Node id. Each node holds different part of the dataset.",
-    )
-    args = parser.parse_args()
-    partition_id = args.node_id
+# Prepare data
+X = load_waltons()
+partitioner = NaturalIdPartitioner(partition_by="group")
+partitioner.dataset = Dataset.from_pandas(X)
 
-    # Prepare data
-    X = load_waltons()
-    partitioner = NaturalIdPartitioner(partition_by="group")
-    partitioner.dataset = Dataset.from_pandas(X)
-    partition = partitioner.load_partition(partition_id).to_pandas()
-    events = partition["E"].values
-    times = partition["T"].values
 
-    # Start Flower client
-    client = FlowerClient(times=times, events=events).to_client()
-    fl.client.start_client(
-        server_address="127.0.0.1:8080",
-        client=client,
-    )
+def get_client_fn(partition_id: int):
+    def client_fn(cid: str):
+        partition = partitioner.load_partition(partition_id).to_pandas()
+        events = partition["E"].values
+        times = partition["T"].values
+        return FlowerClient(times=times, events=events).to_client()
+
+    return client_fn
+
+
+# Run via `flower-client-app client:app`
+node_1_app = fl.client.ClientApp(
+    client_fn=get_client_fn(0),
+)
+node_2_app = fl.client.ClientApp(
+    client_fn=get_client_fn(1),
+)

examples/federated-kaplan-meier-fitter/pyproject.toml

@@ -11,7 +11,7 @@ maintainers = ["The Flower Authors <[email protected]>"]
 
 [tool.poetry.dependencies]
 python = ">=3.9,<3.11"
-flwr = ">=1.0,<2.0"
+flwr-nightly = "*"
 flwr-datasets = ">=0.0.2,<1.0.0"
 numpy = ">=1.23.2"
 pandas = ">=2.0.0"

examples/federated-kaplan-meier-fitter/requirements.txt

@@ -1,4 +1,4 @@
-flwr>=1.0, <2.0
+flwr-nightly
 flwr-datasets>=0.0.2, <1.0.0
 numpy>=1.23.2
 pandas>=2.0.0

examples/federated-kaplan-meier-fitter/server.py

@@ -97,6 +97,13 @@ def aggregate_fit(
         sorted_times = combined_times[args_sorted]
         sorted_events = combined_events[args_sorted]
         self.fitter.fit(sorted_times, sorted_events)
+        print("Survival function:")
+        print(self.fitter.survival_function_)
+        self.fitter.plot_survival_function()
+        plt.title("Survival function of fruit flies (Walton's data)", fontsize=16)
+        plt.savefig("./_static/survival_function_federated.png", dpi=200)
+        print("Mean survival time:")
+        print(self.fitter.median_survival_time_)
         return None, {}
 
     # The methods below return None or empty results.
@@ -129,19 +136,10 @@ def configure_evaluate(
         return []
 
 
-if __name__ == "__main__":
-    fitter = KaplanMeierFitter()  # You can choose other method that work on E, T data
-    strategy = EventTimeFitterStrategy(min_num_clients=2, fitter=fitter)
-    # Start Flower server
-    fl.server.start_server(
-        server_address="127.0.0.1:8080",
-        config=fl.server.ServerConfig(num_rounds=1),
-        strategy=strategy,
-    )
-    print("Survival function:")
-    print(strategy.fitter.survival_function_)
-    strategy.fitter.plot_survival_function()
-    plt.title("Survival function of fruit flies (Walton's data)", fontsize=16)
-    plt.savefig("./survival_function_federated.png", dpi=200)
-    print("Mean survival time:")
-    print(strategy.fitter.median_survival_time_)
+fitter = KaplanMeierFitter()  # You can choose other method that work on E, T data
+strategy = EventTimeFitterStrategy(min_num_clients=2, fitter=fitter)
+
+app = fl.server.ServerApp(
+    config=fl.server.ServerConfig(num_rounds=1),
+    strategy=strategy,
+)