chore: don't ignore missing imports mypy (#996)

Author: jsolaas

.pre-commit-config.yaml

@@ -25,8 +25,16 @@ repos:
           - types-PyYAML
           - pydantic
           - numpy
+          - typer
+          - pytest
+          - orjson
+          - py4j
           - types-requests
           - pandas-stubs
+          - types-networkx
+          - types-shapely
+          - scipy-stubs
+          - "ruamel.yaml"
   - repo: https://github.com/alessandrojcm/commitlint-pre-commit-hook
     rev: v9.17.0
     hooks:

poetry.lock

@@ -67,6 +67,9 @@ mypy = "^1.15.0"
 types-PyYAML = "*"
 types-requests = "*"
 pandas-stubs = "*"
+types-networkx = "^3.5.0.20250701"
+types-shapely = "^2.1.0.20250512"
+scipy-stubs = "^1.16.0.2"
 
 [tool.poetry.extras]
 notebooks = ["jupyter", "matplotlib"]
@@ -97,8 +100,9 @@ markers = [
 
 [tool.mypy]
 mypy_path = "./src"
-ignore_missing_imports = true
+ignore_missing_imports = false
 warn_return_any = false
+# warn_unreachable = true
 warn_unused_configs = true
 warn_redundant_casts = true
 warn_unused_ignores = true
@@ -112,7 +116,11 @@ warn_no_return = false
 disable_error_code = ["call-overload", "union-attr", "valid-type", "return-value", "attr-defined", "assignment"]
 namespace_packages = true
 explicit_package_bases = true
-plugins = ['pydantic.mypy', 'numpy.typing.mypy_plugin']
+plugins = ['pydantic.mypy']
+
+[[tool.mypy.overrides]]
+module = ["py4j.*"]
+ignore_missing_imports = true
 
 [tool.coverage.run]
 omit = ["^./__init__.py", "^api/.*"]

pyproject.toml

@@ -17,7 +17,7 @@ def id(self) -> NodeID: ...
 
 class Graph(Generic[TNode]):
     def __init__(self):
-        self.graph = nx.DiGraph()
+        self.graph: nx.DiGraph = nx.DiGraph()
         self.nodes: dict[NodeID, TNode] = {}
 
     def add_node(self, node: TNode) -> Self:

src/libecalc/common/graph.py

@@ -42,7 +42,7 @@ def to_stream_day(calendar_day_rates: NDArray[np.float64], regularity: list[floa
         Returns:
             The corresponding stream day rates
         """
-        regularity = np.asarray(regularity, dtype=np.float64)  # type: ignore[assignment]
+        regularity = np.asarray(regularity, dtype=np.float64)
         return np.divide(calendar_day_rates, regularity, out=np.zeros_like(calendar_day_rates), where=regularity != 0.0)  # type: ignore[comparison-overlap]
 
     @staticmethod

src/libecalc/common/utils/rates.py

@@ -75,7 +75,7 @@ def evaluate(self, load: NDArray[np.float64], fuel_lower_heating_value: float =
 
         # Convert arrays to lists, providing empty lists as fallback for None values
         load_list = array_to_list(load_adjusted) or []
-        efficiency_list = array_to_list(efficiency) or []
+        efficiency_list = array_to_list(efficiency) or []  # type: ignore[arg-type]
         fuel_usage_list = array_to_list(fuel_usage) or []
         exceeds_max_list = array_to_list(load > self._maximum_load) or []
 

src/libecalc/domain/infrastructure/energy_components/turbine/turbine.py

@@ -191,7 +191,7 @@ def evaluate(
         if rate is not None:
             # Find indices where rate is zero and set result to zero (zero rate means machine is off)
             zero_rate = list(rate <= 0 if rate is not None else False)
-            indices_set_to_zero = self._get_indices_from_condition(condition=zero_rate)  # type: ignore[arg-type]
+            indices_set_to_zero = self._get_indices_from_condition(condition=zero_rate)
             interpolated_consumer_values[indices_set_to_zero] = 0.0
 
         """
@@ -358,7 +358,7 @@ def calculate_turbine_power_usage(self, fuel_usage_values: NDArray[np.float64])
                 return TurbineResult(
                     fuel_rate=array_to_list(fuel_usage_values),
                     efficiency=array_to_list(np.ones_like(fuel_usage_values)),
-                    load=array_to_list(load),
+                    load=array_to_list(load),  # type: ignore[arg-type]
                     energy_usage=array_to_list(fuel_usage_values),  # type: ignore[arg-type]
                     energy_usage_unit=Unit.STANDARD_CUBIC_METER_PER_DAY,
                     power=array_to_list(power),  # type: ignore

src/libecalc/domain/process/compressor/core/sampled/compressor_model_sampled.py

@@ -128,11 +128,11 @@ def evaluate(
         **kwargs,
     ) -> NDArray[np.float64]:
         if self._x_column_name == RATE_NAME:
-            return np.array(self._energy_function(rate))
+            return np.array(self._energy_function(rate))  # type: ignore[arg-type]
         if self._x_column_name == PS_NAME:
-            return np.array(self._energy_function(suction_pressure))
+            return np.array(self._energy_function(suction_pressure))  # type: ignore[arg-type]
         if self._x_column_name == PD_NAME:
-            return np.array(self._energy_function(discharge_pressure))
+            return np.array(self._energy_function(discharge_pressure))  # type: ignore[arg-type]
         raise IllegalStateException(
             f"Unknown column name '{self._x_column_name}', allowed column names are '{RATE_NAME}', '{PS_NAME}' or '{PD_NAME}'"
         )

src/libecalc/domain/process/compressor/core/sampled/compressor_model_sampled_1d.py

@@ -51,7 +51,7 @@ def __init__(self, sampled_data: pd.DataFrame, function_header: str):
         # the interpolator we use when calculating energy usage
         self._interpolator = LinearNDInterpolator(
             sampled_data[self.variable_order_2d][:].values,
-            sampled_data[function_header[:]][:].values,
+            sampled_data[function_header[:]][:].values,  # type: ignore[arg-type]
             fill_value=np.nan,
             rescale=True,
         )
@@ -218,7 +218,7 @@ class CompressorModelSampled2DRatePs:
     def __init__(self, sampled_data: pd.DataFrame, function_header: str):
         self._interpolator = LinearNDInterpolator(
             sampled_data[self.variable_order_2d][:].values,
-            sampled_data[function_header[:]][:].values,
+            sampled_data[function_header[:]][:].values,  # type: ignore[arg-type]
             fill_value=np.nan,
             rescale=True,
         )
@@ -293,7 +293,7 @@ class CompressorModelSampled2DPsPd:
     def __init__(self, sampled_data: pd.DataFrame, function_header: str):
         self._interpolator = LinearNDInterpolator(
             sampled_data[self.variable_order_2d][:].values,
-            sampled_data[function_header[:]][:].values,
+            sampled_data[function_header[:]][:].values,  # type: ignore[arg-type]
             fill_value=np.nan,
             rescale=True,
         )

src/libecalc/domain/process/compressor/core/sampled/compressor_model_sampled_2d.py

@@ -134,7 +134,7 @@ def __init__(
         delaunay = Delaunay(qhull_points)
         interpolator = LinearNDInterpolator(
             points=delaunay,
-            values=sampled_data[function_header[:]][:].values,
+            values=sampled_data[function_header[:]][:].values,  # type: ignore[arg-type]
             fill_value=np.nan,
             rescale=False,
         )