typing

src/bonsai/bonsai/bim/module/model/decorator.py

@@ -1077,7 +1077,7 @@ class ProductDecorator:
         data["verts"] = []
 
         # Verts
-        polyline_vertices = []
+        polyline_vertices: list[Vector] = []
         polyline_props = tool.Model.get_polyline_props()
         polyline_data = polyline_props.insertion_polyline
         polyline_points = polyline_data[0].polyline_points if polyline_data else []
@@ -1197,7 +1197,7 @@ class ProductDecorator:
         data = {}
         data["verts"] = []
         # Verts
-        polyline_vertices = []
+        polyline_vertices: list[Vector] = []
         polyline_props = tool.Model.get_polyline_props()
         polyline_data = polyline_props.insertion_polyline
         polyline_points = polyline_data[0].polyline_points if polyline_data else []

src/bonsai/bonsai/bim/module/search/operator.py

@@ -19,7 +19,7 @@
 import bisect
 import json
 import traceback
-from typing import TYPE_CHECKING, Literal, assert_never, get_args
+from typing import TYPE_CHECKING, Any, Literal, assert_never, get_args
 
 import bpy
 import ifcopenshell
@@ -695,9 +695,9 @@ class EditFilterQuery(Operator, tool.Ifc.Operator):
         filter_groups = tool.Search.get_filter_groups(module)
 
         if tool.Blender.get_addon_preferences().chain_filter_with_set_operations:
-            filter_structure = []
+            filter_structure: list[list[dict[str, Any]]] = []
             for filter_group in filter_groups:
-                group_data = []
+                group_data: list[dict[str, Any]] = []
                 for ifc_filter in filter_group.filters:
                     filter_data = {
                         "type": ifc_filter.type,
@@ -852,9 +852,9 @@ class SaveSearch(Operator, tool.Ifc.Operator):
             query = tool.Search.export_filter_query(filter_groups)
             results = tool.Search.execute_filter_groups(filter_groups)
 
-            filter_structure = []
+            filter_structure: list[list[dict[str, Any]]] = []
             for filter_group in filter_groups:
-                group_data = []
+                group_data: list[dict[str, Any]] = []
                 for ifc_filter in filter_group.filters:
                     filter_data = {
                         "type": ifc_filter.type,

src/bonsai/bonsai/tool/model.py

@@ -2626,7 +2626,7 @@ class Model(bonsai.core.tool.Model):
         reference_obj: bpy.types.Object,
         objs: Iterable[bpy.types.Object],
         align_type: Literal["CENTER", "POSITIVE", "NEGATIVE"],
-    ):
+    ) -> None:
         if align_type == "CENTER":
             point = reference_obj.matrix_world @ (Vector(reference_obj.bound_box[0]) + (reference_obj.dimensions / 2))
         elif align_type == "POSITIVE":
@@ -2771,7 +2771,7 @@ class Model(bonsai.core.tool.Model):
             SvIfcStore.use_bonsai_file = False
 
     @classmethod
-    def create_bmesh_from_vertices(cls, vertices, is_closed=False):
+    def create_bmesh_from_vertices(cls, vertices: list[Vector], is_closed: bool = False) -> bmesh.types.BMesh:
         bm = bmesh.new()
 
         new_verts = [bm.verts.new(v) for v in vertices]

src/bonsai/bonsai/tool/search.py

@@ -20,7 +20,7 @@ from __future__ import annotations
 
 import json
 from itertools import cycle
-from typing import TYPE_CHECKING, Literal, Union
+from typing import TYPE_CHECKING, Any, Literal, Union
 
 import bpy
 import ifcopenshell.guid
@@ -51,7 +51,9 @@ class Search(bonsai.core.tool.Search):
 
     @classmethod
     def import_filter_structure(
-        cls, filter_structure: list, filter_groups: bpy.types.bpy_prop_collection_idprop[BIMFilterGroup]
+        cls,
+        filter_structure: list[list[dict[str, Any]]],
+        filter_groups: bpy.types.bpy_prop_collection_idprop[BIMFilterGroup],
     ) -> None:
         filter_groups.clear()
 
@@ -188,7 +190,9 @@ class Search(bonsai.core.tool.Search):
         return ""
 
     @classmethod
-    def execute_filter_groups(cls, filter_groups: bpy.types.bpy_prop_collection_idprop[BIMFilterGroup]) -> set:
+    def execute_filter_groups(
+        cls, filter_groups: bpy.types.bpy_prop_collection_idprop[BIMFilterGroup]
+    ) -> set[ifcopenshell.entity_instance]:
         """
         Execute filter groups with simplified chaining support.
         Within a single group chain, all filters chain sequentially with ADD/SUBTRACT/FILTER modes.
@@ -196,10 +200,10 @@ class Search(bonsai.core.tool.Search):
         """
         preferences = tool.Blender.get_addon_preferences()
 
-        all_group_results = []
+        all_group_results: list[set[ifcopenshell.entity_instance]] = []
 
-        for group_idx, filter_group in enumerate(filter_groups):
+        for filter_group in filter_groups:
-            group_results = set()
+            group_results: set[ifcopenshell.entity_instance] = set()
 
             for filter_index, ifc_filter in enumerate(filter_group.filters):
                 if not ifc_filter.value:
@@ -245,7 +249,7 @@ class Search(bonsai.core.tool.Search):
             if group_results:
                 all_group_results.append(group_results)
 
-        final_results = set()
+        final_results: set[ifcopenshell.entity_instance] = set()
         for group_results in all_group_results:
             final_results.update(group_results)
 
@@ -262,9 +266,9 @@ class Search(bonsai.core.tool.Search):
         """
         filter_structure = data.get("filter_structure", [])
 
-        all_group_results = []
+        all_group_results: list[set[ifcopenshell.entity_instance]] = []
         for group_data in filter_structure:
-            group_results = set()
+            group_results: set[ifcopenshell.entity_instance] = set()
 
             for filter_data in group_data:
                 filter_mode = filter_data.get("filter_mode", "ADD")
@@ -332,7 +336,7 @@ class Search(bonsai.core.tool.Search):
             if group_results:
                 all_group_results.append(group_results)
 
-        final_results = set()
+        final_results: set[ifcopenshell.entity_instance] = set()
         for group_results in all_group_results:
             final_results.update(group_results)