MLIA-386 Simplify typing in the source code

- Enable deferred annotations evaluation
- Use builtin types for type hints whenever possible
- Use | syntax for union types
- Rename mlia.core._typing into mlia.core.typing

Change-Id: I3f6ffc02fa069c589bdd9e8bddbccd504285427a

1 files changed, 7 insertions, 8 deletions

diff --git a/src/mlia/core/workflow.py b/src/mlia/core/workflow.py
index 03f3d1c..d862a86 100644
--- a/src/mlia/core/workflow.py
+++ b/src/mlia/core/workflow.py
@@ -5,16 +5,15 @@
 This module contains implementation of the workflow
 executors.
 """
+from __future__ import annotations
+
 import itertools
 from abc import ABC
 from abc import abstractmethod
 from functools import wraps
 from typing import Any
 from typing import Callable
-from typing import List
-from typing import Optional
 from typing import Sequence
-from typing import Tuple
 
 from mlia.core.advice_generation import Advice
 from mlia.core.advice_generation import AdviceEvent
@@ -57,7 +56,7 @@ STAGE_ANALYSIS = (DataAnalysisStageStartedEvent(), DataAnalysisStageFinishedEven
 STAGE_ADVICE = (AdviceStageStartedEvent(), AdviceStageFinishedEvent())
 
 
-def on_stage(stage_events: Tuple[Event, Event]) -> Callable:
+def on_stage(stage_events: tuple[Event, Event]) -> Callable:
     """Mark start/finish of the stage with appropriate events."""
 
     def wrapper(method: Callable) -> Callable:
@@ -87,7 +86,7 @@ class DefaultWorkflowExecutor(WorkflowExecutor):
         collectors: Sequence[DataCollector],
         analyzers: Sequence[DataAnalyzer],
         producers: Sequence[AdviceProducer],
-        startup_events: Optional[Sequence[Event]] = None,
+        startup_events: Sequence[Event] | None = None,
     ):
         """Init default workflow executor.
 
@@ -130,7 +129,7 @@ class DefaultWorkflowExecutor(WorkflowExecutor):
             self.publish(event)
 
     @on_stage(STAGE_COLLECTION)
-    def collect_data(self) -> List[DataItem]:
+    def collect_data(self) -> list[DataItem]:
         """Collect data.
 
         Run each of data collector components and return list of
@@ -148,7 +147,7 @@ class DefaultWorkflowExecutor(WorkflowExecutor):
         return collected_data
 
     @on_stage(STAGE_ANALYSIS)
-    def analyze_data(self, collected_data: List[DataItem]) -> List[DataItem]:
+    def analyze_data(self, collected_data: list[DataItem]) -> list[DataItem]:
         """Analyze data.
 
         Pass each collected data item into each data analyzer and
@@ -168,7 +167,7 @@ class DefaultWorkflowExecutor(WorkflowExecutor):
         return analyzed_data
 
     @on_stage(STAGE_ADVICE)
-    def produce_advice(self, analyzed_data: List[DataItem]) -> None:
+    def produce_advice(self, analyzed_data: list[DataItem]) -> None:
         """Produce advice.
 
         Pass each analyzed data item into each advice producer and