Merge branch 'main' into starters-template-compatibility

astro-airflow-iris/{{ cookiecutter.repo_name }}/src/{{ cookiecutter.python_package }}/pipeline_registry.py

@@ -1,11 +1,10 @@
 """Project pipelines."""
-from typing import Dict
 
 from kedro.framework.project import find_pipelines
 from kedro.pipeline import Pipeline
 
 
-def register_pipelines() -> Dict[str, Pipeline]:
+def register_pipelines() -> dict[str, Pipeline]:
     """Register the project's pipelines.
 
     Returns:

astro-airflow-iris/{{ cookiecutter.repo_name }}/src/{{ cookiecutter.python_package }}/pipelines/data_engineering/nodes.py

@@ -4,12 +4,12 @@
 PLEASE DELETE THIS FILE ONCE YOU START WORKING ON YOUR OWN PROJECT!
 """
 
-from typing import Any, Dict
+from typing import Any
 
 import pandas as pd
 
 
-def split_data(data: pd.DataFrame, example_test_data_ratio: float) -> Dict[str, Any]:
+def split_data(data: pd.DataFrame, example_test_data_ratio: float) -> dict[str, Any]:
     """Node for splitting the classical Iris data set into training and test
     sets, each split into features and labels.
     The split ratio parameter is taken from conf/project/parameters.yml.

astro-airflow-iris/{{ cookiecutter.repo_name }}/src/{{ cookiecutter.python_package }}/pipelines/data_science/nodes.py

@@ -4,14 +4,14 @@
 Delete this when you start working on your own Kedro project.
 """
 import logging
-from typing import Any, Dict
+from typing import Any
 
 import numpy as np
 import pandas as pd
 
 
 def train_model(
-    train_x: pd.DataFrame, train_y: pd.DataFrame, parameters: Dict[str, Any]
+    train_x: pd.DataFrame, train_y: pd.DataFrame, parameters: dict[str, Any]
 ) -> np.ndarray:
     """Node for training a simple multi-class logistic regression model. The
     number of training iterations as well as the learning rate are taken from

databricks-iris/{{ cookiecutter.repo_name }}/src/{{ cookiecutter.python_package }}/nodes.py

@@ -4,14 +4,13 @@
 """
 
 import logging
-from typing import Dict, Tuple
 
 import numpy as np
 import pandas as pd
 from pyspark.sql import DataFrame
 
 
-def split_data(data: DataFrame, parameters: Dict) -> Tuple:
+def split_data(data: DataFrame, parameters: dict) -> tuple:
     """Splits data into features and targets training and test sets.
 
     Args:

databricks-iris/{{ cookiecutter.repo_name }}/src/{{ cookiecutter.python_package }}/pipeline_registry.py

@@ -1,11 +1,10 @@
 """Project pipelines."""
-from typing import Dict
 
 from kedro.framework.project import find_pipelines
 from kedro.pipeline import Pipeline
 
 
-def register_pipelines() -> Dict[str, Pipeline]:
+def register_pipelines() -> dict[str, Pipeline]:
     """Register the project's pipelines.
 
     Returns:

features/environment.py

@@ -8,9 +8,9 @@
 import tempfile
 import venv
 from pathlib import Path
-from typing import Any, Set
+from typing import Any
 
-_PATHS_TO_REMOVE: Set[Path] = set()
+_PATHS_TO_REMOVE: set[Path] = set()