lint and remove compat

momepy/coins.py

@@ -170,7 +170,7 @@ def _get_links(self):
 
             p2.append(item)
 
-        self.result = list(zip(range(len(p1)), p1, p2))
+        self.result = list(zip(range(len(p1)), p1, p2, strict=True))
 
         for a in self.result:
             n = a[0]
@@ -371,7 +371,7 @@ def _list_to_tuple(line):
 def _list_to_pairs(in_list):
     """Split a line at every point."""
     tmp_list = [list(point) for point in in_list]
-    return [list(pair) for pair in zip(tmp_list, tmp_list[1:])]
+    return [list(pair) for pair in zip(tmp_list, tmp_list[1:], strict=True)]
 
 
 def _compute_angle(point1, point2):

momepy/dimension.py

@@ -546,7 +546,7 @@ def __init__(
         end_markers = []
 
         lengths = shapely.length(lines)
-        for ix, (line, length) in enumerate(zip(lines, lengths)):
+        for ix, (line, length) in enumerate(zip(lines, lengths, strict=True)):
             pts = shapely.line_interpolate_point(
                 line, np.linspace(0, length, num=int((length) // distance))
             )
@@ -560,7 +560,7 @@ def __init__(
                 ids += [ix] * 2
 
         ticks = []
-        for num, (pt, end) in enumerate(zip(list_points, end_markers), 1):
+        for num, (pt, end) in enumerate(zip(list_points, end_markers, strict=True), 1):
             if end:
                 ticks.append([pt, pt])
                 ticks.append([pt, pt])
@@ -587,7 +587,7 @@ def __init__(
 
         min_distances = []
         min_inds = []
-        for dis, ind in zip(dist_per_res, inp_per_res):
+        for dis, ind in zip(dist_per_res, inp_per_res, strict=True):
             min_distances.append(np.min(dis))
             min_inds.append(ind[np.argmin(dis)])
 

momepy/distribution.py

@@ -70,7 +70,9 @@ def _dist(a, b):
 
         bboxes = shapely.minimum_rotated_rectangle(gdf.geometry)
         for geom, bbox in tqdm(
-            zip(gdf.geometry, bboxes), total=gdf.shape[0], disable=not verbose
+            zip(gdf.geometry, bboxes, strict=True),
+            total=gdf.shape[0],
+            disable=not verbose,
         ):
             if geom.geom_type in ["Polygon", "MultiPolygon", "LinearRing"]:
                 bbox = list(bbox.exterior.coords)
@@ -793,7 +795,9 @@ def __init__(
             print("Spatial weights ready...") if verbose else None
 
         self.sw = spatial_weights
-        patches = dict(zip(gdf[unique_id], spatial_weights.component_labels))
+        patches = dict(
+            zip(gdf[unique_id], spatial_weights.component_labels, strict=True)
+        )
 
         for uid in tqdm(
             self.id,

momepy/diversity.py

@@ -685,7 +685,7 @@ def p(n, sum_n):
         counts.update(data.value_counts())
     else:
         sample_bins = mc.UserDefined(data, bins)
-        counts = dict(zip(bins, sample_bins.counts))
+        counts = dict(zip(bins, sample_bins.counts, strict=True))
 
     return -sum(p(n, sum(counts.values())) for n in counts.values() if n != 0)
 

momepy/elements.py

@@ -9,7 +9,6 @@
 import numpy as np
 import pandas as pd
 import shapely
-from packaging.version import Version
 from scipy.spatial import Voronoi
 from shapely.geometry.base import BaseGeometry
 from shapely.ops import polygonize
@@ -25,8 +24,6 @@
     "get_network_ratio",
 ]
 
-GPD_10 = Version(gpd.__version__) >= Version("0.10")
-
 
 def buffered_limit(gdf, buffer=100):
     """
@@ -241,7 +238,7 @@ def __init__(
                 n_chunks,
             )
         else:
-            if isinstance(limit, (gpd.GeoSeries, gpd.GeoDataFrame)):
+            if isinstance(limit, gpd.GeoSeries | gpd.GeoDataFrame):
                 limit = limit.unary_union
 
             bounds = shapely.bounds(limit)
@@ -275,10 +272,7 @@ def _morphological_tessellation(
             objects.loc[mask, objects.geometry.name] = objects[mask].buffer(
                 -shrink, cap_style=2, join_style=2
             )
-        if GPD_10:
-            objects = objects.reset_index(drop=True).explode(ignore_index=True)
-        else:
-            objects = objects.reset_index(drop=True).explode().reset_index(drop=True)
+        objects = objects.reset_index(drop=True).explode(ignore_index=True)
         objects = objects.set_index(unique_id)
 
         print("Generating input point array...") if verbose else None
@@ -331,7 +325,7 @@ def _dense_point_array(self, geoms, distance, index):
         else:
             lines = geoms
         lengths = shapely.length(lines)
-        for ix, line, length in zip(index, lines, lengths):
+        for ix, line, length in zip(index, lines, lengths, strict=True):
             if length > distance:  # some polygons might have collapsed
                 pts = shapely.line_interpolate_point(
                     line,
@@ -621,45 +615,28 @@ def __init__(self, tessellation, edges, buildings, id_name, unique_id):
             gpd.GeoDataFrame(geometry=edges.buffer(0.001)),
             how="difference",
         )
-        cut = cut.explode(ignore_index=True) if GPD_10 else cut.explode()
-
+        cut = cut.explode(ignore_index=True)
         weights = libpysal.weights.Queen.from_dataframe(cut, silence_warnings=True)
         cut["component"] = weights.component_labels
         buildings_c = buildings.copy()
         buildings_c.geometry = buildings_c.representative_point()  # make points
-        if GPD_10:
-            centroids_temp_id = gpd.sjoin(
-                buildings_c,
-                cut[[cut.geometry.name, "component"]],
-                how="left",
-                predicate="within",
-            )
-        else:
-            centroids_temp_id = gpd.sjoin(
-                buildings_c,
-                cut[[cut.geometry.name, "component"]],
-                how="left",
-                op="within",
-            )
+        centroids_temp_id = gpd.sjoin(
+            buildings_c,
+            cut[[cut.geometry.name, "component"]],
+            how="left",
+            predicate="within",
+        )
 
         cells_copy = tessellation[[unique_id, tessellation.geometry.name]].merge(
             centroids_temp_id[[unique_id, "component"]], on=unique_id, how="left"
         )
-        if GPD_10:
-            blocks = cells_copy.dissolve(by="component").explode(ignore_index=True)
-        else:
-            blocks = (
-                cells_copy.dissolve(by="component").explode().reset_index(drop=True)
-            )
+        blocks = cells_copy.dissolve(by="component").explode(ignore_index=True)
         blocks[id_name] = range(len(blocks))
         blocks = blocks[[id_name, blocks.geometry.name]]
 
-        if GPD_10:
-            centroids_w_bl_id2 = gpd.sjoin(
-                buildings_c, blocks, how="left", predicate="within"
-            )
-        else:
-            centroids_w_bl_id2 = gpd.sjoin(buildings_c, blocks, how="left", op="within")
+        centroids_w_bl_id2 = gpd.sjoin(
+            buildings_c, blocks, how="left", predicate="within"
+        )
 
         self.buildings_id = centroids_w_bl_id2[id_name]
 
@@ -823,7 +800,7 @@ def get_node_id(
         edges = edges.set_index(edge_id)
         centroids = objects.centroid
         for eid, centroid in tqdm(
-            zip(objects[edge_id], centroids),
+            zip(objects[edge_id], centroids, strict=True),
             total=objects.shape[0],
             disable=not verbose,
         ):
@@ -844,7 +821,9 @@ def get_node_id(
 
     elif edge_keys is not None and edge_values is not None:
         for edge_i, edge_r, geom in tqdm(
-            zip(objects[edge_keys], objects[edge_values], objects.geometry),
+            zip(
+                objects[edge_keys], objects[edge_values], objects.geometry, strict=True
+            ),
             total=objects.shape[0],
             disable=not verbose,
         ):
@@ -903,9 +882,6 @@ def get_network_ratio(df, edges, initial_buffer=500):
     4        [26]                                        [1]
     """
 
-    if not GPD_10:
-        raise ImportError("`get_network_ratio` requires geopandas 0.10 or newer.")
-
     (df_ix, edg_ix), dist = edges.sindex.nearest(
         df.geometry, max_distance=initial_buffer, return_distance=True
     )

momepy/preprocessing.py

@@ -10,7 +10,6 @@
 import numpy as np
 import pandas as pd
 import shapely
-from packaging.version import Version
 from scipy.signal import find_peaks
 from scipy.stats import gaussian_kde
 from shapely.geometry import LineString, Point
@@ -30,9 +29,6 @@
     "FaceArtifacts",
 ]
 
-GPD_10 = Version(gpd.__version__) >= Version("0.10")
-GPD_09 = Version(gpd.__version__) >= Version("0.9")
-
 
 def preprocess(
     buildings, size=30, compactness=0.2, islands=True, loops=2, verbose=True
@@ -80,11 +76,7 @@ def preprocess(
         GeoDataFrame containing preprocessed geometry
     """
     blg = buildings.copy()
-    if GPD_10:
-        blg = blg.explode(ignore_index=True)
-    else:
-        blg = blg.explode()
-        blg.reset_index(drop=True, inplace=True)
+    blg = blg.explode(ignore_index=True)
     for loop in range(0, loops):
         print("Loop", loop + 1, f"out of {loops}.") if verbose else None
         blg.reset_index(inplace=True, drop=True)
@@ -182,13 +174,10 @@ def remove_false_nodes(gdf):
     momepy.extend_lines
     momepy.close_gaps
     """
-    if isinstance(gdf, (gpd.GeoDataFrame, gpd.GeoSeries)):
+    if isinstance(gdf, gpd.GeoDataFrame | gpd.GeoSeries):
         # explode to avoid MultiLineStrings
         # reset index due to the bug in GeoPandas explode
-        if GPD_10:
-            df = gdf.reset_index(drop=True).explode(ignore_index=True)
-        else:
-            df = gdf.reset_index(drop=True).explode().reset_index(drop=True)
+        df = gdf.reset_index(drop=True).explode(ignore_index=True)
 
         # get underlying shapely geometry
         geom = df.geometry.array
@@ -242,10 +231,7 @@ def remove_false_nodes(gdf):
 
         # remove incorrect geometries and append fixed versions
         df = df.drop(merge)
-        if GPD_10:
-            final = gpd.GeoSeries(new).explode(ignore_index=True)
-        else:
-            final = gpd.GeoSeries(new).explode().reset_index(drop=True)
+        final = gpd.GeoSeries(new).explode(ignore_index=True)
         if isinstance(gdf, gpd.GeoDataFrame):
             return pd.concat(
                 [
@@ -472,10 +458,7 @@ def extend_lines(gdf, tolerance, target=None, barrier=None, extension=0):
     """
     # explode to avoid MultiLineStrings
     # reset index due to the bug in GeoPandas explode
-    if GPD_10:
-        df = gdf.reset_index(drop=True).explode(ignore_index=True)
-    else:
-        df = gdf.reset_index(drop=True).explode().reset_index(drop=True)
+    df = gdf.reset_index(drop=True).explode(ignore_index=True)
 
     if target is None:
         target = df
@@ -758,10 +741,7 @@ def _selecting_rabs_from_poly(
         rab["rab_diameter"] = rab[["deltax", "deltay"]].max(axis=1)
 
         # selecting the adjacent areas that are of smaller than itself
-        if GPD_10:
-            rab_adj = gpd.sjoin(gdf, rab, predicate="intersects")
-        else:
-            rab_adj = gpd.sjoin(gdf, rab, op="intersects")
+        rab_adj = gpd.sjoin(gdf, rab, predicate="intersects")
 
         area_right = area_col + "_right"
         area_left = area_col + "_left"
@@ -870,16 +850,10 @@ def _selecting_incoming_lines(rab_multipolygons, edges, angle_threshold=0):
     is used to select the line to be extended further.
     """
     # selecting the lines that are touching but not covered by
-    if GPD_10:
-        touching = gpd.sjoin(edges, rab_multipolygons, predicate="touches")
-        edges_idx, rabs_idx = rab_multipolygons.sindex.query_bulk(
-            edges.geometry, predicate="covered_by"
-        )
-    else:
-        touching = gpd.sjoin(edges, rab_multipolygons, op="touches")
-        edges_idx, rabs_idx = rab_multipolygons.sindex.query_bulk(
-            edges.geometry, op="covered_by"
-        )
+    touching = gpd.sjoin(edges, rab_multipolygons, predicate="touches")
+    edges_idx, rabs_idx = rab_multipolygons.sindex.query_bulk(
+        edges.geometry, predicate="covered_by"
+    )
     idx_drop = edges.index.take(edges_idx)
     touching_idx = touching.index
     ls = list(set(touching_idx) - set(idx_drop))
@@ -1035,12 +1009,6 @@ def roundabout_simplification(
         GeoDataFrame with an updated geometry and an additional
         column labeling modified edges.
     """
-    if not GPD_09:
-        raise ImportError(
-            "`roundabout_simplification` requires geopandas 0.9.0 or newer. "
-            f"Your current version is {gpd.__version__}."
-        )
-
     if len(edges[edges.geom_type != "LineString"]) > 0:
         raise TypeError(
             "Only LineString geometries are allowed. "
@@ -1223,7 +1191,7 @@ def __init__(
             # find index (in linspace) of highest peak
             highest_peak_index = self.peaks[highest_peak_listindex]
             # define all possible peak ranges fitting our definition
-            peak_bounds = list(zip(self.peaks, self.peaks[1:]))
+            peak_bounds = list(zip(self.peaks, self.peaks[1:], strict=True))
             peak_bounds_accepted = [b for b in peak_bounds if highest_peak_index in b]
             # find all valleys that lie between two peaks
             valleys_accepted = [

momepy/tests/test_elements.py

@@ -12,10 +12,6 @@
 
 import momepy as mm
 
-# https://github.com/geopandas/geopandas/issues/2282
-GPD_REGR = Version("0.10.2") < Version(gpd.__version__) < Version("0.11")
-GPD_10 = Version(gpd.__version__) >= Version("0.10")
-
 
 class TestElements:
     def setup_method(self):
@@ -152,7 +148,6 @@ def test_get_network_id_duplicate(self):
         buildings_id = mm.get_network_id(self.df_buildings, self.df_streets, "nID")
         assert not buildings_id.isna().any()
 
-    @pytest.mark.skipif(GPD_REGR, reason="regression in geopandas")
     def test_get_node_id(self):
         nx = mm.gdf_to_nx(self.df_streets)
         nodes, edges = mm.nx_to_gdf(nx)
@@ -162,8 +157,6 @@ def test_get_node_id(self):
         ids = mm.get_node_id(self.df_buildings, nodes, edges, "nodeID", "nID")
         assert not ids.isna().any()
 
-    @pytest.mark.skipif(GPD_REGR, reason="regression in geopandas")
-    @pytest.mark.skipif(not GPD_10, reason="requires sindex.nearest")
     def test_get_node_id_ratio(self):
         nx = mm.gdf_to_nx(self.df_streets)
         nodes, edges = mm.nx_to_gdf(nx)
@@ -219,7 +212,6 @@ def test_enclosures(self):
         encl = mm.enclosures(self.df_streets, limit=gpd.GeoSeries([limit]), clip=True)
         assert len(encl) == 18
 
-    @pytest.mark.skipif(not GPD_10, reason="requires sindex.nearest")
     def test_get_network_ratio(self):
         convex_hull = self.df_streets.unary_union.convex_hull
         enclosures = mm.enclosures(self.df_streets, limit=gpd.GeoSeries([convex_hull]))
@@ -246,7 +238,6 @@ def test_get_network_ratio(self):
         for i, idx in enumerate(expected_tail):
             assert sorted(links2.edgeID_keys.tail(5).iloc[i]) == sorted(idx)
 
-    @pytest.mark.skipif(GPD_10, reason="requires sindex.nearest")
     def test_get_network_ratio_error(self):
         convex_hull = self.df_streets.unary_union.convex_hull
         enclosures = mm.enclosures(self.df_streets, limit=gpd.GeoSeries([convex_hull]))

momepy/tests/test_graph.py

@@ -5,8 +5,6 @@
 
 import momepy as mm
 
-NX_26 = Version(nx.__version__) < Version("2.6")
-
 
 class TestGraph:
     def setup_method(self):
@@ -171,7 +169,6 @@ def test_mean_nodes(self):
             == edge
         )
 
-    @pytest.mark.skipif(NX_26, reason="networkx<2.6 has a bug")
     def test_clustering(self):
         net = mm.clustering(self.network)
         check = 0.05555555555555555