Fix typos in src/py* src/flwr/* e2e/* dev (#3042)

Co-authored-by: Taner Topal <taner@flower.dev>

dev/publish-nightly.sh

@@ -20,7 +20,7 @@ cd "$( cd "$( dirname "${BASH_SOURCE[0]}" )" >/dev/null 2>&1 && pwd )"/../
 
 # This script will build and publish a nightly release of Flower under the condition
 # that at least one commit was made in the last 24 hours.
-# It will rename the the package name in the pyproject.toml to from "flwr" to "flwr-nightly".
+# It will rename the package name in the pyproject.toml to from "flwr" to "flwr-nightly".
 # The version name in the pyproject.toml will be appended with "-dev" and the current date.
 # The result will be a release on PyPi of the package "flwr-nightly" of version e.g. 
 # "0.1.1.dev20200716" as seen at https://pypi.org/project/flwr-nightly/

e2e/scikit-learn/utils.py

@@ -10,7 +10,7 @@
 
 
 def get_model_parameters(model: LogisticRegression) -> LogRegParams:
-    """Returns the paramters of a sklearn LogisticRegression model."""
+    """Returns the parameters of a sklearn LogisticRegression model."""
     if model.fit_intercept:
         params = [
             model.coef_,

src/py/flwr/common/record/recordset_test.py

@@ -70,7 +70,7 @@ def test_parameters_to_array_and_back() -> None:
     """Test conversion between legacy Parameters and Array."""
     ndarrays = get_ndarrays()
 
-    # Array represents a single array, unlike Paramters, which represent a
+    # Array represents a single array, unlike parameters, which represent a
     # list of arrays
     ndarray = ndarrays[0]
 
@@ -296,7 +296,7 @@ def test_set_metrics_to_metricsrecord_with_and_without_keeping_input(
         (str, lambda x: x.flatten().astype("float").tolist()),  # str: List[float]
         (str, lambda x: x.flatten().astype("bool").tolist()),  # str: List[bool]
         (str, lambda x: [x.flatten().tobytes()]),  # str: List[bytes]
-        (str, lambda x: []),  # str: empyt list
+        (str, lambda x: []),  # str: emptyt list
     ],
 )
 def test_set_configs_to_configsrecord_with_correct_types(

src/py/flwr/server/strategy/dp_adaptive_clipping.py

@@ -63,7 +63,7 @@ class DifferentialPrivacyServerSideAdaptiveClipping(Strategy):
     num_sampled_clients : int
         The number of clients that are sampled on each round.
     initial_clipping_norm : float
-        The initial value of clipping norm. Deafults to 0.1.
+        The initial value of clipping norm. Defaults to 0.1.
         Andrew et al. recommends to set to 0.1.
     target_clipped_quantile : float
         The desired quantile of updates which should be clipped. Defaults to 0.5.
@@ -263,7 +263,7 @@ class DifferentialPrivacyClientSideAdaptiveClipping(Strategy):
     num_sampled_clients : int
         The number of clients that are sampled on each round.
     initial_clipping_norm : float
-        The initial value of clipping norm. Deafults to 0.1.
+        The initial value of clipping norm. Defaults to 0.1.
         Andrew et al. recommends to set to 0.1.
     target_clipped_quantile : float
         The desired quantile of updates which should be clipped. Defaults to 0.5.

src/py/flwr_example/tensorflow_fashion_mnist/fashion_mnist_test.py

@@ -21,7 +21,7 @@
 
 
 def test_shuffle() -> None:
-    """Test if shuffle is deterministic depending on the the provided seed."""
+    """Test if shuffle is deterministic depending on the provided seed."""
     # Prepare
     x_tt = np.arange(8)
     y_tt = np.arange(8)

src/py/flwr_experimental/baseline/config/config.py

@@ -23,7 +23,7 @@
 from flwr_experimental.ops.instance import Instance
 
 # We assume that devices which are older will have at most
-# ~80% of the the Samsung Galaxy Note 5 compute performance.
+# ~80% of the Samsung Galaxy Note 5 compute performance.
 SCORE_MISSING = int(226 * 0.80)
 
 DEVICE_DISTRIBUTION = [

src/py/flwr_experimental/ops/cluster.py

@@ -139,7 +139,7 @@ def group_instances_by_specs(instances: List[Instance]) -> List[List[Instance]]:
 
 
 class Cluster:
-    """Compute enviroment independend compute cluster."""
+    """Compute environment independend compute cluster."""
 
     def __init__(
         self,