Enable Bugbear Ruff (#154)

pyproject.toml

@@ -80,7 +80,7 @@ line-length = 100
 
 [tool.ruff.lint]
 select = [
-    # "B",
+    "B",
     "E",
     "F",
     "FLY",
@@ -119,7 +119,6 @@ extend-unsafe-fixes = [
 [tool.ruff.lint.per-file-ignores]
 "spatialpandas/tests/**" = [
     "NPY002", # Replace legacy `np.random.rand` call with Generator
-    # "B904", # Within an `except` clause, raise exceptions with from err or None
 ]
 
 [tool.ruff.lint.isort]

spatialpandas/dask.py

@@ -504,7 +504,7 @@ def write_metadata_file():
         # Build spatial metadata for parquet dataset
         partition_bounds = {}
         for col, bounds in all_bounds.items():
-            partition_bounds[col] = pd.DataFrame(all_bounds[col]).to_dict()
+            partition_bounds[col] = pd.DataFrame(bounds).to_dict()
 
         spatial_metadata = {'partition_bounds': partition_bounds}
         b_spatial_metadata = json.dumps(spatial_metadata).encode('utf')

spatialpandas/geometry/base.py

@@ -72,16 +72,17 @@ def construct_from_string(cls, string):
                 raise AttributeError
         except AttributeError:
             raise TypeError(
-                f"'construct_from_string' expects a string, got {type(string)}")
+                f"'construct_from_string' expects a string, got {type(string)}"
+            ) from None
 
         msg = f"Cannot construct a '{cls.__name__}' from '{{}}'"
         if string.startswith(cls._geometry_name.lower()):
             # Extract subtype
             try:
                 subtype_string = cls._parse_subtype(string)
                 return cls(subtype_string)
-            except Exception:
-                raise TypeError(msg.format(string))
+            except Exception as e:
+                raise TypeError(msg.format(string)) from e
         else:
             raise TypeError(msg.format(string))
 

spatialpandas/geometry/baselist.py

@@ -17,7 +17,7 @@ def _validate_nested_arrow_type(nesting_levels, pyarrow_type):
         return pa.null()
 
     pyarrow_element_type = pyarrow_type
-    for i in range(nesting_levels):
+    for _ in range(nesting_levels):
         if not isinstance(pyarrow_element_type, pa.ListType):
             raise ValueError(
                 f"Expected input data to have {nesting_levels} nested layer(s)"
@@ -192,7 +192,7 @@ def _arrow_type_from_numpy_element_dtype(cls, dtype):
         arrow_dtype = pa.from_numpy_dtype(dtype)
 
         # Wrap dtype with appropriate number of nesting levels
-        for i in range(cls._nesting_levels):
+        for _ in range(cls._nesting_levels):
             arrow_dtype = pa.list_(arrow_dtype)
 
         return arrow_dtype
@@ -202,7 +202,7 @@ def _numpy_element_dtype_from_arrow_type(self, pyarrow_type):
             return pa.null()
 
         pyarrow_element_type = pyarrow_type
-        for i in range(self._nesting_levels):
+        for _ in range(self._nesting_levels):
             pyarrow_element_type = pyarrow_element_type.value_type
 
         return pyarrow_element_type.to_pandas_dtype()

spatialpandas/io/utils.py

@@ -36,10 +36,10 @@ def validate_coerce_filesystem(
     else:
         try:
             return fsspec.filesystem(filesystem, **fsspec_opts)
-        except ValueError:
+        except ValueError as e:
             raise ValueError(
                 f"Received invalid filesystem value with type: {type(filesystem)}"
-            )
+            ) from e
 
 
 def _maybe_prepend_protocol(

spatialpandas/tests/geometry/strategies.py

@@ -33,7 +33,7 @@
 def st_point_array(draw, min_size=0, max_size=30, geoseries=False):
     n = draw(st.integers(min_size, max_size))
     points = []
-    for i in range(n):
+    for _ in range(n):
         x_mid = draw(st.floats(-50, 50))
         y_mid = draw(st.floats(-50, 50))
         point = (np.random.rand(2) - 0.5) * 5
@@ -51,7 +51,7 @@ def st_point_array(draw, min_size=0, max_size=30, geoseries=False):
 def st_multipoint_array(draw, min_size=0, max_size=30, geoseries=False):
     n = draw(st.integers(min_size, max_size))
     lines = []
-    for i in range(n):
+    for _ in range(n):
         num_points = draw(st.integers(1, 10))
         x_mid = draw(st.floats(-50, 50))
         y_mid = draw(st.floats(-50, 50))
@@ -70,7 +70,7 @@ def st_multipoint_array(draw, min_size=0, max_size=30, geoseries=False):
 def st_line_array(draw, min_size=0, max_size=30, geoseries=False):
     n = draw(st.integers(min_size, max_size))
     lines = []
-    for i in range(n):
+    for _ in range(n):
         line_len = draw(st.integers(2, 10))
         x_mid = draw(st.floats(-50, 50))
         y_mid = draw(st.floats(-50, 50))
@@ -105,7 +105,7 @@ def st_ring_array(draw, min_size=3, max_size=30, geoseries=False):
     assert min_size >= 3
     n = draw(st.integers(min_size, max_size))
     rings = []
-    for i in range(n):
+    for _ in range(n):
         rings.append(sg.LinearRing(get_unique_points(n)))
 
     result = from_shapely(rings)
@@ -118,10 +118,10 @@ def st_ring_array(draw, min_size=3, max_size=30, geoseries=False):
 def st_multiline_array(draw, min_size=0, max_size=5, geoseries=False):
     n = draw(st.integers(min_size, max_size))
     multilines = []
-    for i in range(n):
+    for _ in range(n):
         m = draw(st.integers(1, 5))
         lines = []
-        for j in range(m):
+        for _ in range(m):
             line_len = draw(st.integers(2, 3))
             x_mid = draw(st.floats(-50, 50))
             y_mid = draw(st.floats(-50, 50))

spatialpandas/tests/test_geodataframe.py

@@ -48,7 +48,7 @@ def test_active_geometry(use_dask):
     # Select columns not including active geometry
     selected_gdf = gdf[['a', 'points']]
     with pytest.raises(ValueError):
-        selected_gdf.geometry
+        selected_gdf.geometry  # noqa: B018
 
     assert selected_gdf.set_geometry('points').geometry.name == 'points'
 

spatialpandas/tools/sjoin.py

@@ -111,7 +111,7 @@ def _sjoin_dask_pandas(
 
     # Build list of delayed sjoin results
     joined_dfs = []
-    for df, (i, bounds) in zip(dfs, partition_bounds.iterrows()):
+    for df, (_idx, bounds) in zip(dfs, partition_bounds.iterrows()):
         right_inds = right_sindex.intersects(bounds.values)
         if how == "left" or len(right_inds) > 0:
             joined_dfs.append(