Fix types according to mypy

src/primaite/__init__.py

@@ -72,7 +72,7 @@ class _LevelFormatter(Formatter):
     Credit to: https://stackoverflow.com/a/68154386
     """
 
-    def __init__(self, formats: Dict[int, str], **kwargs: Any) -> str:
+    def __init__(self, formats: Dict[int, str], **kwargs: Any) -> None:
         super().__init__()
 
         if "fmt" in kwargs:

src/primaite/acl/access_control_list.py

@@ -1,6 +1,6 @@
 # Crown Copyright (C) Dstl 2022. DEFCON 703. Shared in confidence.
 """A class that implements the access control list implementation for the network."""
-from typing import Dict, Optional
+from typing import Dict
 
 from primaite.acl.acl_rule import ACLRule
 
@@ -76,9 +76,7 @@ class AccessControlList:
         hash_value = hash(new_rule)
         self.acl[hash_value] = new_rule
 
-    def remove_rule(
+    def remove_rule(self, _permission: str, _source_ip: str, _dest_ip: str, _protocol: str, _port: str) -> None:
-        self, _permission: str, _source_ip: str, _dest_ip: str, _protocol: str, _port: str
-    ) -> Optional[int]:
         """
         Removes a rule.
 

src/primaite/agents/utils.py

@@ -34,7 +34,7 @@ def transform_action_node_readable(action: List[int]) -> List[Union[int, str]]:
     else:
         property_action = "NONE"
 
-    new_action = [action[0], action_node_property, property_action, action[3]]
+    new_action: list[Union[int, str]] = [action[0], action_node_property, property_action, action[3]]
     return new_action
 
 

src/primaite/config/training_config.py

@@ -88,7 +88,7 @@ class TrainingConfig:
     session_type: SessionType = SessionType.TRAIN
     "The type of PrimAITE session to run"
 
-    load_agent: str = False
+    load_agent: bool = False
     "Determine whether to load an agent from file"
 
     agent_load_file: Optional[str] = None
@@ -194,7 +194,7 @@ class TrainingConfig:
     "The random number generator seed to be used while training the agent"
 
     @classmethod
-    def from_dict(cls, config_dict: Dict[str, Union[str, int, bool]]) -> TrainingConfig:
+    def from_dict(cls, config_dict: Dict[str, Any]) -> TrainingConfig:
         """
         Create an instance of TrainingConfig from a dict.
 
@@ -211,9 +211,11 @@ class TrainingConfig:
             "hard_coded_agent_view": HardCodedAgentView,
         }
 
+        # convert the string representation of enums into the actual enum values themselves?
         for key, value in field_enum_map.items():
             if key in config_dict:
                 config_dict[key] = value[config_dict[key]]
+
         return TrainingConfig(**config_dict)
 
     def to_dict(self, json_serializable: bool = True) -> Dict:
@@ -335,7 +337,7 @@ def convert_legacy_training_config_dict(
     return config_dict
 
 
-def _get_new_key_from_legacy(legacy_key: str) -> str:
+def _get_new_key_from_legacy(legacy_key: str) -> Optional[str]:
     """
     Maps legacy training config keys to the new format keys.
 

src/primaite/environment/reward.py

@@ -1,6 +1,6 @@
 # Crown Copyright (C) Dstl 2022. DEFCON 703. Shared in confidence.
 """Implements reward function."""
-from typing import Dict, TYPE_CHECKING
+from typing import Dict, TYPE_CHECKING, Union
 
 from primaite import getLogger
 from primaite.common.custom_typing import NodeUnion
@@ -152,7 +152,10 @@ def score_node_operating_state(
 
 
 def score_node_os_state(
-    final_node: NodeUnion, initial_node: NodeUnion, reference_node: NodeUnion, config_values: "TrainingConfig"
+    final_node: Union[ActiveNode, ServiceNode],
+    initial_node: Union[ActiveNode, ServiceNode],
+    reference_node: Union[ActiveNode, ServiceNode],
+    config_values: "TrainingConfig",
 ) -> float:
     """
     Calculates score relating to the Software State of a node.
@@ -205,7 +208,7 @@ def score_node_os_state(
 
 
 def score_node_service_state(
-    final_node: NodeUnion, initial_node: NodeUnion, reference_node: NodeUnion, config_values: "TrainingConfig"
+    final_node: ServiceNode, initial_node: ServiceNode, reference_node: ServiceNode, config_values: "TrainingConfig"
 ) -> float:
     """
     Calculates score relating to the service state(s) of a node.
@@ -279,7 +282,10 @@ def score_node_service_state(
 
 
 def score_node_file_system(
-    final_node: NodeUnion, initial_node: NodeUnion, reference_node: NodeUnion, config_values: "TrainingConfig"
+    final_node: Union[ActiveNode, ServiceNode],
+    initial_node: Union[ActiveNode, ServiceNode],
+    reference_node: Union[ActiveNode, ServiceNode],
+    config_values: "TrainingConfig",
 ) -> float:
     """
     Calculates score relating to the file system state of a node.

src/primaite/pol/green_pol.py

@@ -1,6 +1,6 @@
 # Crown Copyright (C) Dstl 2022. DEFCON 703. Shared in confidence.
 """Implements Pattern of Life on the network (nodes and links)."""
-from typing import Dict, Union
+from typing import Dict
 
 from networkx import MultiGraph, shortest_path
 
@@ -10,7 +10,6 @@ from primaite.common.enums import HardwareState, NodePOLType, NodeType, Software
 from primaite.links.link import Link
 from primaite.nodes.active_node import ActiveNode
 from primaite.nodes.node_state_instruction_green import NodeStateInstructionGreen
-from primaite.nodes.node_state_instruction_red import NodeStateInstructionRed
 from primaite.nodes.service_node import ServiceNode
 from primaite.pol.ier import IER
 
@@ -65,6 +64,8 @@ def apply_iers(
             dest_node = nodes[dest_node_id]
 
             # 1. Check the source node situation
+            # TODO: should be using isinstance rather than checking node type attribute. IE. just because it's a switch
+            # doesn't mean it has a software state? It could be a PassiveNode or ActiveNode
             if source_node.node_type == NodeType.SWITCH:
                 # It's a switch
                 if (
@@ -215,7 +216,7 @@ def apply_iers(
 
 def apply_node_pol(
     nodes: Dict[str, NodeUnion],
-    node_pol: Dict[any, Union[NodeStateInstructionGreen, NodeStateInstructionRed]],
+    node_pol: Dict[str, NodeStateInstructionGreen],
     step: int,
 ) -> None:
     """

src/primaite/pol/red_agent_pol.py

@@ -74,6 +74,9 @@ def apply_red_agent_iers(
                 pass
             else:
                 # It's not a switch or an actuator (so active node)
+                # TODO: this occurs after ruling out the possibility that the node is a switch or an actuator, but it
+                # could still be a passive/active node, therefore it won't have a hardware_state. The logic here needs
+                # to change according to duck typing.
                 if source_node.hardware_state == HardwareState.ON:
                     if source_node.has_service(protocol):
                         # Red agents IERs can only be valid if the source service is in a compromised state

src/primaite/transactions/transaction.py

@@ -1,7 +1,7 @@
 # Crown Copyright (C) Dstl 2022. DEFCON 703. Shared in confidence.
 """The Transaction class."""
 from datetime import datetime
-from typing import List, Tuple, TYPE_CHECKING, Union
+from typing import List, Optional, Tuple, TYPE_CHECKING, Union
 
 from primaite.common.enums import AgentIdentifier
 
@@ -31,15 +31,15 @@ class Transaction(object):
         "The step number"
         self.obs_space: "spaces.Space" = None
         "The observation space (pre)"
-        self.obs_space_pre: Union["np.ndarray", Tuple["np.ndarray"]] = None
+        self.obs_space_pre: Optional[Union["np.ndarray", Tuple["np.ndarray"]]] = None
         "The observation space before any actions are taken"
-        self.obs_space_post: Union["np.ndarray", Tuple["np.ndarray"]] = None
+        self.obs_space_post: Optional[Union["np.ndarray", Tuple["np.ndarray"]]] = None
         "The observation space after any actions are taken"
-        self.reward: float = None
+        self.reward: Optional[float] = None
         "The reward value"
-        self.action_space: int = None
+        self.action_space: Optional[int] = None
         "The action space invoked by the agent"
-        self.obs_space_description: List[str] = None
+        self.obs_space_description: Optional[List[str]] = None
         "The env observation space description"
 
     def as_csv_data(self) -> Tuple[List, List]: