add py.typed file; apply ruff

nrel/routee/powertrain/core/metadata.py

@@ -2,8 +2,7 @@
 
 import json
 import warnings
-from dataclasses import dataclass, replace
-from typing import Optional
+from dataclasses import dataclass
 
 from nrel.routee.powertrain.core.model_config import ModelConfig
 from nrel.routee.powertrain.utils.fs import get_version

pyproject.toml

@@ -31,6 +31,7 @@ dev = [
     "mypy",
     "maturin",
     "ruff",
+    "shapely",
     "boxsdk",
     "jupyter-book",
     "sphinx-book-theme",
@@ -51,7 +52,7 @@ include = [
 ] # package names should match these glob patterns (["*"] by default)
 
 [tool.setuptools.package-data]
-"*" = ["py.typed"]
+"nrel.routee.powertrain" = ["py.typed"]
 
 [tool.ruff.per-file-ignores]
 "__init__.py" = ["F401"]

scripts/developers/train_model_catalog.py

@@ -183,27 +183,27 @@ def _azimuth(point1, point2):
 
 
 def add_entry_link_angles(group):
-    l = [0]  # can't determine first link entry angle so we set to 0
+    angles = [0]  # can't determine first link entry angle so we set to 0
     for i in range(1, len(group)):
         link1 = group.iloc[i - 1]
         link2 = group.iloc[i]
         line1, line2 = match_link_geoms(link1, link2)
         angle = compute_angle(line1, line2)
-        l.append(angle)
-    s = pd.Series(l, index=group.index)
+        angles.append(angle)
+    s = pd.Series(angles, index=group.index)
     return s
 
 
 def add_exit_link_angles(group):
-    l = []
+    angles = []
     for i in range(0, len(group) - 1):
         link1 = group.iloc[i]
         link2 = group.iloc[i + 1]
         line1, line2 = match_link_geoms(link1, link2)
         angle = compute_angle(line1, line2)
-        l.append(angle)
-    l.append(0)  # can't determine last link exit angle so we set to 0
-    s = pd.Series(l, index=group.index)
+        angles.append(angle)
+    angles.append(0)  # can't determine last link exit angle so we set to 0
+    s = pd.Series(angles, index=group.index)
     return s
 
 

tests/test_train_estimate_pipeline.py

@@ -77,7 +77,7 @@ def test_sklearn_random_forest(self):
         outfile = self.out_path / "estimator.onnx"
         estimator = list(vehicle_model.estimators.values())[0]
         estimator.to_file(outfile)
-        new_estimator = ONNXEstimator.from_file(outfile)
+        _ = ONNXEstimator.from_file(outfile)
         outfile.unlink()
 
         r2 = new_vehicle_model.predict(self.df)
@@ -104,13 +104,13 @@ def test_smartcore_random_forest(self):
         outfile = self.out_path / "estimator.json"
         estimator = list(vehicle_model.estimators.values())[0]
         estimator.to_file(outfile)
-        new_estimator = SmartCoreEstimator.from_file(outfile)
+        _ = SmartCoreEstimator.from_file(outfile)
         outfile.unlink()
 
         outfile = self.out_path / "estimator.bin"
         estimator = list(vehicle_model.estimators.values())[0]
         estimator.to_file(outfile)
-        new_estimator = SmartCoreEstimator.from_file(outfile)
+        _ = SmartCoreEstimator.from_file(outfile)
         outfile.unlink()
 
         r2 = new_vehicle_model.predict(self.df)