Support Pandas 2.2, unpin Pyarrow, and fail on warnings in tests

pixi.toml

@@ -24,9 +24,10 @@ lint = ["py311", "lint"]
 dask-core = "*"
 fsspec = "*"
 numba = "*"
-pandas = "<2.2" # FIX: Temporary upper pin
+packaging = "*"
+pandas = "*"
 pip = "*"
-pyarrow = ">=10,<15" # FIX: Temporary upper pin
+pyarrow = ">=10"
 retrying = "*"
 
 [feature.py39.dependencies]

pyproject.toml

@@ -26,7 +26,15 @@ classifiers = [
     "Topic :: Scientific/Engineering",
     "Topic :: Software Development :: Libraries",
 ]
-dependencies = ['dask', 'fsspec >=2022.8', 'numba', 'pandas', 'pyarrow >=10', 'retrying']
+dependencies = [
+    'dask',
+    'fsspec >=2022.8',
+    'numba',
+    'packaging',
+    'pandas',
+    'pyarrow >=10',
+    'retrying',
+]
 
 [project.urls]
 Homepage = "https://github.com/holoviz/spatialpandas"
@@ -61,7 +69,10 @@ addopts = [
 minversion = "7"
 xfail_strict = true
 log_cli_level = "INFO"
-filterwarnings = []
+filterwarnings = [
+    "error",
+    "ignore:datetime.datetime.utcnow():DeprecationWarning:botocore", # https://github.com/boto/boto3/issues/3889
+]
 
 [tool.ruff]
 fix = true

spatialpandas/dask.py

@@ -9,6 +9,7 @@
 import pyarrow as pa
 import pyarrow.parquet as pq
 from retrying import retry
+from packaging.version import Version
 
 import dask
 import dask.dataframe as dd
@@ -190,7 +191,11 @@ def pack_partitions(self, npartitions=None, p=15, shuffle='tasks'):
 
         # Set index to distance. This will trigger an expensive shuffle
         # sort operation
-        ddf = ddf.set_index('hilbert_distance', npartitions=npartitions, shuffle=shuffle)
+        if Version(dask.__version__) >= Version('2024.1'):
+            shuffle_kwargs = {'shuffle_method': shuffle}
+        else:
+            shuffle_kwargs = {'shuffle': shuffle}
+        ddf = ddf.set_index('hilbert_distance', npartitions=npartitions, **shuffle_kwargs)
 
         if ddf.npartitions != npartitions:
             # set_index doesn't change the number of partitions if the partitions

spatialpandas/geodataframe.py

@@ -63,10 +63,26 @@ def __init__(self, data=None, index=None, geometry=None, **kwargs):
     def _constructor(self):
         return _MaybeGeoDataFrame
 
+    def _constructor_from_mgr(self, mgr, axes):
+        if not any(isinstance(block.dtype, GeometryDtype) for block in mgr.blocks):
+            return pd.DataFrame._from_mgr(mgr, axes)
+
+        gdf = GeoDataFrame._from_mgr(mgr, axes)
+        if (gdf.columns == "geometry").sum() == 1:  # only if "geometry" is single col
+            gdf._geometry = "geometry"
+        return gdf
+
     @property
     def _constructor_sliced(self):
         return _MaybeGeoSeries
 
+    def _constructor_sliced_from_mgr(self, mgr, axes):
+        is_row_proxy = mgr.index.is_(self.columns)
+
+        if isinstance(mgr.blocks[0].dtype, GeometryDtype) and not is_row_proxy:
+            return GeoSeries._from_mgr(mgr, axes)
+        return pd.Series._from_mgr(mgr, axes)
+
     def set_geometry(self, geometry, inplace=False):
         if (geometry not in self or
                 not isinstance(self[geometry].dtype, GeometryDtype)):

spatialpandas/geoseries.py

@@ -1,5 +1,4 @@
 import pandas as pd
-from packaging.version import Version
 
 from .geometry import GeometryDtype, Geometry
 
@@ -36,24 +35,13 @@ def __init__(self, data, index=None, name=None, dtype=None, **kwargs):
         super().__init__(data, index=index, name=name, **kwargs)
 
     def _constructor_from_mgr(self, mgr, axes):
-        if Version(pd.__version__) < Version('2.1'):
-            return super()._constructor_from_mgr(mgr, axes)
+        from pandas.core.internals import SingleBlockManager
+        assert isinstance(mgr, SingleBlockManager)
 
-        # Copied from pandas.Series._constructor_from_mgr
-        # https://github.com/pandas-dev/pandas/blob/80a1a8bc3e07972376284ffce425a2abd1e58604/pandas/core/series.py#L582-L590
-        # Changed if statement to use GeoSeries instead of Series.
-        # REF: https://github.com/pandas-dev/pandas/pull/52132
-        # REF: https://github.com/pandas-dev/pandas/pull/53871
+        if not isinstance(mgr.blocks[0].dtype, GeometryDtype):
+            return pd.Series._from_mgr(mgr, axes)
 
-        ser = self._from_mgr(mgr, axes=axes)
-        ser._name = None  # caller is responsible for setting real name
-
-        if type(self) is GeoSeries:  # Changed line
-            # fastpath avoiding constructor call
-            return ser
-        else:
-            assert axes is mgr.axes
-            return self._constructor(ser, copy=False)
+        return GeoSeries._from_mgr(mgr, axes)
 
     @property
     def _constructor(self):
@@ -64,6 +52,19 @@ def _constructor_expanddim(self):
         from .geodataframe import GeoDataFrame
         return GeoDataFrame
 
+    def _constructor_expanddim_from_mgr(self, mgr, axes):
+        from .geodataframe import GeoDataFrame
+        df = pd.DataFrame._from_mgr(mgr, axes)
+        geo_cols = [col for col in df.columns if isinstance(df[col].dtype, GeometryDtype)]
+        if geo_cols:
+            geo_col_name = geo_cols if len(geo_cols) == 1 else None
+
+            if geo_col_name is None or not isinstance(getattr(df[geo_col_name], "dtype", None), GeometryDtype):
+                df = GeoDataFrame(df)
+            else:
+                df = df.set_geometry(geo_col_name)
+        return df
+
     @property
     def bounds(self):
         return pd.DataFrame(

spatialpandas/io/parquet.py

@@ -8,7 +8,6 @@
 
 import fsspec
 import pandas as pd
-import pyarrow as pa
 from dask import delayed
 from dask.dataframe import from_delayed, from_pandas
 from dask.dataframe import read_parquet as dd_read_parquet
@@ -29,9 +28,6 @@
 # improve pandas compatibility, based on geopandas _compat.py
 PANDAS_GE_12 = Version(pd.__version__) >= Version("1.2.0")
 
-# When we drop support for pyarrow < 5 all code related to this can be removed.
-LEGACY_PYARROW = Version(pa.__version__) < Version("5.0.0")
-
 
 def _load_parquet_pandas_metadata(
     path,
@@ -45,35 +41,20 @@ def _load_parquet_pandas_metadata(
         raise ValueError("Path not found: " + path)
 
     if filesystem.isdir(path):
-        if LEGACY_PYARROW:
-            basic_kwargs = dict(validate_schema=False)
-        else:
-            basic_kwargs = dict(use_legacy_dataset=False)
-
         pqds = ParquetDataset(
             path,
             filesystem=filesystem,
-            **basic_kwargs,
             **engine_kwargs,
         )
 
-        if LEGACY_PYARROW:
-            common_metadata = pqds.common_metadata
-            if common_metadata is None:
-                # Get metadata for first piece
-                piece = pqds.pieces[0]
-                metadata = piece.get_metadata().metadata
-            else:
-                metadata = pqds.common_metadata.metadata
-        else:
-            filename = "/".join([_get_parent_path(pqds.files[0]), "_common_metadata"])
-            try:
-                common_metadata = _read_metadata(filename, filesystem=filesystem)
-            except FileNotFoundError:
-                # Common metadata doesn't exist, so get metadata for first piece instead
-                filename = pqds.files[0]
-                common_metadata = _read_metadata(filename, filesystem=filesystem)
-            metadata = common_metadata.metadata
+        filename = "/".join([_get_parent_path(pqds.files[0]), "_common_metadata"])
+        try:
+            common_metadata = _read_metadata(filename, filesystem=filesystem)
+        except FileNotFoundError:
+            # Common metadata doesn't exist, so get metadata for first piece instead
+            filename = pqds.files[0]
+            common_metadata = _read_metadata(filename, filesystem=filesystem)
+        metadata = common_metadata.metadata
     else:
         with filesystem.open(path) as f:
             pf = ParquetFile(f)
@@ -128,29 +109,15 @@ def read_parquet(
     engine_kwargs = engine_kwargs or {}
     filesystem = validate_coerce_filesystem(path, filesystem, storage_options)
 
-    if LEGACY_PYARROW:
-        basic_kwargs = dict(validate_schema=False)
-    else:
-        basic_kwargs = dict(use_legacy_dataset=False)
-
     # Load using pyarrow to handle parquet files and directories across filesystems
     dataset = ParquetDataset(
         path,
         filesystem=filesystem,
-        **basic_kwargs,
         **engine_kwargs,
         **kwargs,
     )
 
-    if LEGACY_PYARROW:
-        metadata = _load_parquet_pandas_metadata(
-            path,
-            filesystem=filesystem,
-            storage_options=storage_options,
-            engine_kwargs=engine_kwargs,
-        )
-    else:
-        metadata = dataset.schema.pandas_metadata
+    metadata = dataset.schema.pandas_metadata
 
     # If columns specified, prepend index columns to it
     if columns is not None:
@@ -338,11 +305,6 @@ def _perform_read_parquet_dask(
         filesystem,
         storage_options,
     )
-    if LEGACY_PYARROW:
-        basic_kwargs = dict(validate_schema=False)
-    else:
-        basic_kwargs = dict(use_legacy_dataset=False)
-
     datasets = []
     for path in paths:
         if filesystem.isdir(path):
@@ -353,7 +315,6 @@ def _perform_read_parquet_dask(
         d = ParquetDataset(
             path,
             filesystem=filesystem,
-            **basic_kwargs,
             **engine_kwargs,
         )
         datasets.append(d)
@@ -420,10 +381,7 @@ def _perform_read_parquet_dask(
     else:
         cols_no_index = None
 
-    if LEGACY_PYARROW:
-        files = paths
-    else:
-        files = getattr(datasets[0], "files", paths)
+    files = getattr(datasets[0], "files", paths)
 
     meta = dd_read_parquet(
         files[0],
@@ -524,14 +482,11 @@ def _read_metadata(filename, filesystem):
 def _load_partition_bounds(pqds, filesystem=None):
     partition_bounds = None
 
-    if LEGACY_PYARROW:
-        common_metadata = pqds.common_metadata
-    else:
-        filename = "/".join([_get_parent_path(pqds.files[0]), "_common_metadata"])
-        try:
-            common_metadata = _read_metadata(filename, filesystem=filesystem)
-        except FileNotFoundError:
-            common_metadata = None
+    filename = "/".join([_get_parent_path(pqds.files[0]), "_common_metadata"])
+    try:
+        common_metadata = _read_metadata(filename, filesystem=filesystem)
+    except FileNotFoundError:
+        common_metadata = None
 
     if common_metadata is not None and b'spatialpandas' in common_metadata.metadata:
         spatial_metadata = json.loads(

spatialpandas/tests/geometry/strategies.py

@@ -1,3 +1,4 @@
+import os
 import numpy as np
 from geopandas import GeoSeries
 from geopandas.array import from_shapely
@@ -11,7 +12,7 @@
 
 hyp_settings = settings(
     deadline=None,
-    max_examples=100,
+    max_examples=int(os.environ.get('HYPOTHESIS_MAX_EXAMPLES', 100)),
     suppress_health_check=[HealthCheck.too_slow],
 )
 

spatialpandas/tests/spatialindex/test_hilbert_curve.py

@@ -1,3 +1,4 @@
+import os
 from itertools import product
 
 import hypothesis.strategies as st
@@ -18,7 +19,7 @@
     distances_from_coordinates,
 )
 
-hyp_settings = settings(deadline=None)
+hyp_settings = settings(deadline=None, max_examples=int(os.environ.get('HYPOTHESIS_MAX_EXAMPLES', 100)))
 
 # ### strategies ###
 st_p = st.integers(min_value=1, max_value=5)

spatialpandas/tests/spatialindex/test_rtree.py

@@ -1,3 +1,4 @@
+import os
 import pickle
 
 import hypothesis.strategies as st
@@ -9,7 +10,7 @@
 from spatialpandas.spatialindex import HilbertRtree
 
 # ### hypothesis settings ###
-hyp_settings = settings(deadline=None)
+hyp_settings = settings(deadline=None, max_examples=int(os.environ.get('HYPOTHESIS_MAX_EXAMPLES', 100)))
 
 
 # ### Custom strategies ###