Feature type defined using dynamic type assertion to work around limi…

…tations of python's type system

(lack of type-based method overloading)

.vscode/settings.json

@@ -28,9 +28,6 @@
     "jupyter.jupyterServerType": "local",
     "jupyter.notebookFileRoot": "${workspaceFolder}",
     "files.trimFinalNewlines": true,
-    "editor.defaultFormatter": "ms-python.flake8",
-    "flake8.args": [
-    ],
+    "editor.defaultFormatter": "ms-python.black-formatter",
     "files.trimTrailingWhitespace": true,
-
 }

cyberbattle/_env/cyberbattle_env.py

@@ -1317,7 +1317,7 @@ def get_explored_network_node_properties_bitmap_as_numpy(
             ]
         )
 
-    def step(self, action: Action) -> Tuple[Observation, float, bool, bool, StepInfo]:
+    def step(self, action: Action) -> Tuple[Observation, float, bool, bool, StepInfo]:  # type: ignore
         if self.__done:
             raise RuntimeError("new episode must be started with env.reset()")
 

cyberbattle/_env/discriminatedunion.py

@@ -14,7 +14,7 @@
 T_cov = TypeVar("T_cov", covariant=True)
 
 
-class DiscriminatedUnion(spaces.Dict, Generic[T_cov]):  # type: ignore
+class DiscriminatedUnion(spaces.Dict, Generic[T_cov]):
     """
     A discriminated union of simpler spaces.
 
@@ -23,6 +23,9 @@ class DiscriminatedUnion(spaces.Dict, Generic[T_cov]):  # type: ignore
     self.observation_space = discriminatedunion.DiscriminatedUnion(
         {"foo": spaces.Discrete(2), "Bar": spaces.Discrete(3)})
 
+    Generic type T_cov is the type of the contained discriminated values.
+    It should be defined as  a typed dictionary, e.g.:  TypedDict('Choices', {'foo': int, 'Bar': int})
+
     """
 
     def __init__(
@@ -47,7 +50,7 @@ def __init__(
     def seed(self, seed: Union[dict, None, int] = None):
         return super().seed(seed)
 
-    def sample(self, mask=None) -> T_cov:  # dict[str, object]:
+    def sample(self, mask=None) -> T_cov:   # type: ignore
         space_count = len(self.spaces.items())
         index_k = self.union_np_random.integers(0, space_count)
         kth_key, kth_space = list(self.spaces.items())[index_k]