Require Python ^3.7 for all examples

examples/advanced_tensorflow/pyproject.toml

@@ -11,7 +11,7 @@ description = "Advanced Flower/TensorFlow Example"
 authors = ["The Flower Authors <enquiries@flower.dev>"]
 
 [tool.poetry.dependencies]
-python = "^3.6.2"
+python = "^3.7"
 flwr = "^0.17.0"
 # flwr = { path = "../../", develop = true }  # Development
 tensorflow-cpu = "^2.6.2"

examples/advanced_tensorflow/server.py

@@ -27,7 +27,11 @@ def main() -> None:
     )
 
     # Start Flower server for four rounds of federated learning
-    fl.server.start_server("[::]:8080", config={"num_rounds": 4}, strategy=strategy)
+    fl.server.start_server(
+        server_address="[::]:8080",
+        config={"num_rounds": 4},
+        strategy=strategy,
+    )
 
 
 def get_eval_fn(model):

examples/android/pyproject.toml

@@ -11,7 +11,7 @@ description = "Android Example"
 authors = ["The Flower Authors <enquiries@flower.dev>"]
 
 [tool.poetry.dependencies]
-python = "^3.6.2"
+python = "^3.7"
 flwr = "^0.17.0"
 # flwr = { path = "../../", develop = true }  # Development
 tensorflow-cpu = "^2.6.2"

examples/android/server.py

@@ -18,7 +18,11 @@ def main() -> None:
     )
 
     # Start Flower server for 10 rounds of federated learning
-    fl.server.start_server("[::]:8999", config={"num_rounds": 10}, strategy=strategy)
+    fl.server.start_server(
+        server_address="[::]:8999",
+        config={"num_rounds": 10},
+        strategy=strategy,
+    )
 
 
 def fit_config(rnd: int):

examples/dp-sgd-mnist/server.py

@@ -40,7 +40,10 @@ def main(args) -> None:
         eval_fn=get_eval_fn(model),
         initial_parameters=fl.common.weights_to_parameters(model.get_weights()),
     )
-    fl.server.start_server(strategy=strategy, config={"num_rounds": args.num_rounds})
+    fl.server.start_server(
+        strategy=strategy,
+        config={"num_rounds": args.num_rounds},
+    )
 
 
 if __name__ == "__main__":

examples/embedded_devices/server.py

@@ -117,8 +117,8 @@ def main() -> None:
 
     # Run server
     fl.server.start_server(
-        args.server_address,
-        server,
+        server_address=args.server_address,
+        server=server,
         config={"num_rounds": args.rounds},
     )
 

examples/jax_from_centralized_to_federated/server.py

@@ -3,4 +3,7 @@
 import flwr as fl
 
 if __name__ == "__main__":
-    fl.server.start_server("0.0.0.0:8080", config={"num_rounds": 3})
+    fl.server.start_server(
+        server_address="0.0.0.0:8080",
+        config={"num_rounds": 3},
+    )

examples/mxnet_from_centralized_to_federated/pyproject.toml

@@ -11,7 +11,7 @@ description = "MXNet example with MNIST and CNN"
 authors = ["The Flower Authors <enquiries@flower.dev>"]
 
 [tool.poetry.dependencies]
-python = "^3.6.2"
+python = "^3.7"
 flwr = "^0.17.0"
 # flwr = { path = "../../", develop = true }  # Development
 mxnet = "^1.7.0"

examples/mxnet_from_centralized_to_federated/server.py

@@ -3,4 +3,7 @@
 import flwr as fl
 
 if __name__ == "__main__":
-    fl.server.start_server("0.0.0.0:8080", config={"num_rounds": 3})
+    fl.server.start_server(
+        server_address="0.0.0.0:8080",
+        config={"num_rounds": 3},
+    )

examples/opacus/server.py

@@ -1,3 +1,5 @@
 import flwr as fl
 
-fl.server.start_server(config={"num_rounds": 3})
+fl.server.start_server(
+    config={"num_rounds": 3},
+)

examples/pytorch_federated_variational_autoencoder/server.py

@@ -2,7 +2,9 @@
 
 
 def main():
-    fl.server.start_server(config={"num_rounds": 3})
+    fl.server.start_server(
+        config={"num_rounds": 3},
+    )
 
 
 if __name__ == "__main__":

examples/pytorch_from_centralized_to_federated/pyproject.toml

@@ -11,7 +11,7 @@ description = "PyTorch: From Centralized To Federated with Flower"
 authors = ["The Flower Authors <enquiries@flower.dev>"]
 
 [tool.poetry.dependencies]
-python = "^3.6.2"
+python = "^3.7"
 flwr = "^0.15.0"
 torch = "1.7.1"
 torchvision = "0.8.2"

examples/pytorch_from_centralized_to_federated/server.py

@@ -4,4 +4,7 @@
 import flwr as fl
 
 if __name__ == "__main__":
-    fl.server.start_server("[::]:8080", config={"num_rounds": 3})
+    fl.server.start_server(
+        server_address="[::]:8080",
+        config={"num_rounds": 3},
+    )

examples/quickstart_cpp/server.py

@@ -11,4 +11,8 @@
     ]
     initial_parameters = weights_to_parameters(initial_weights)
     strategy = FedAvgCpp(initial_parameters=initial_parameters)
-    fl.server.start_server("127.0.0.1:8888", config={"num_rounds": 5}, strategy=strategy)
+    fl.server.start_server(
+        server_address="127.0.0.1:8888",
+        config={"num_rounds": 5},
+        strategy=strategy,
+    )

examples/quickstart_mlcube/pyproject.toml

@@ -11,7 +11,7 @@ description = "Keras Federated Learning Quickstart with Flower"
 authors = ["The Flower Authors <enquiries@flower.dev>"]
 
 [tool.poetry.dependencies]
-python = "^3.6.2"
+python = "^3.7"
 flwr = "^0.17.0"  # For development: { path = "../../", develop = true }
 tensorflow-cpu = "^2.6.2"
 mlcube = "0.0.4"

examples/quickstart_mxnet/pyproject.toml

@@ -11,7 +11,7 @@ description = "MXNet example with MNIST and CNN"
 authors = ["The Flower Authors <enquiries@flower.dev>"]
 
 [tool.poetry.dependencies]
-python = "^3.6.2"
+python = "^3.7"
 flwr = "^0.17.0"
 # flwr = { path = "../../", develop = true }  # Development
 mxnet = "^1.7.0"

examples/quickstart_mxnet/server.py

@@ -3,4 +3,7 @@
 import flwr as fl
 
 if __name__ == "__main__":
-    fl.server.start_server("0.0.0.0:8080", config={"num_rounds": 3})
+    fl.server.start_server(
+        server_address="0.0.0.0:8080",
+        config={"num_rounds": 3},
+    )

examples/quickstart_simulation/pyproject.toml

@@ -11,7 +11,7 @@ description = "Federated Learning Simulation Quickstart with Flower"
 authors = ["The Flower Authors <enquiries@flower.dev>"]
 
 [tool.poetry.dependencies]
-python = "^3.6.2"
+python = "^3.7"
 flwr = { extras = ["simulation"], version = "^0.17.0" }
 # flwr = { extras = ["simulation"], path = "../../", develop = true }  # Development
 tensorflow-cpu = "2.6.2"

examples/quickstart_tensorflow/pyproject.toml

@@ -11,7 +11,7 @@ description = "Keras Federated Learning Quickstart with Flower"
 authors = ["The Flower Authors <enquiries@flower.dev>"]
 
 [tool.poetry.dependencies]
-python = "^3.6.2"
+python = "^3.7"
 flwr = "^0.17.0"
 # flwr = { path = "../../", develop = true }  # Development
 tensorflow-cpu = "^2.6.2"

examples/simulation/pyproject.toml

@@ -11,7 +11,7 @@ description = "Single-Machine Federated Learning Simulation with Flower"
 authors = ["The Flower Authors <enquiries@flower.dev>"]
 
 [tool.poetry.dependencies]
-python = "^3.6.2"
+python = "^3.7"
 flwr = "==0.15.0"  # For development: { path = "../../", develop = true }
 numpy = "^1.19.0"
 tensorflow-cpu = "==2.4.1"

examples/simulation/simulation.py

@@ -20,7 +20,10 @@ def start_server(num_rounds: int, num_clients: int, fraction_fit: float):
     """Start the server with a slightly adjusted FedAvg strategy."""
     strategy = FedAvg(min_available_clients=num_clients, fraction_fit=fraction_fit)
     # Exposes the server by default on port 8080
-    fl.server.start_server(strategy=strategy, config={"num_rounds": num_rounds})
+    fl.server.start_server(
+        strategy=strategy,
+        config={"num_rounds": num_rounds},
+    )
 
 
 def start_client(dataset: DATASET) -> None:

examples/simulation_pytorch/pyproject.toml

@@ -11,7 +11,7 @@ description = "Federated Learning Simulation with Flower and PyTorch"
 authors = ["The Flower Authors <enquiries@flower.dev>"]
 
 [tool.poetry.dependencies]
-python = "^3.6.2"
+python = "^3.7"
 flwr = {extras = ["simulation"], version = "^0.17.0"}
 # flwr = {extras = ["simulation"], path = "../../", develop = true }  # Development
 torch = "1.7.1"

examples/simulation_pytorch_legacy/pyproject.toml

@@ -11,7 +11,7 @@ description = "Single-Machine Federated Learning Simulation with Flower in Pytor
 authors = ["Mayank Gulati <damanmayank@gmail.com>"]
 
 [tool.poetry.dependencies]
-python = "^3.6.2"
+python = "^3.7"
 flwr = "==0.15.0"  # For development: { path = "../../", develop = true }
 numpy = "^1.19.0"
 torch= "==1.8.1" 

examples/simulation_pytorch_legacy/simulation.py

@@ -20,7 +20,10 @@ def start_server(num_rounds: int, num_clients: int, fraction_fit: float):
     """Start the server with a slightly adjusted FedAvg strategy."""
     strategy = FedAvg(min_available_clients=num_clients, fraction_fit=fraction_fit)
     # Exposes the server by default on port 8080
-    fl.server.start_server(strategy=strategy, config={"num_rounds": num_rounds})
+    fl.server.start_server(
+        strategy=strategy,
+        config={"num_rounds": num_rounds},
+    )
 
 
 def start_client(dataset: DATASET) -> None:

examples/sklearn-logreg-mnist/server.py

@@ -36,4 +36,8 @@ def evaluate(parameters: fl.common.Weights):
         eval_fn=get_eval_fn(model),
         on_fit_config_fn=fit_round,
     )
-    fl.server.start_server("0.0.0.0:8080", strategy=strategy, config={"num_rounds": 5})
+    fl.server.start_server(
+        server_address="0.0.0.0:8080",
+        strategy=strategy,
+        config={"num_rounds": 5},
+    )