pyarrow: Check compatibility of pyarrow-backed pandas objects with numeric dtypes

.github/workflows/ci_tests.yaml

@@ -71,7 +71,7 @@ jobs:
             optional-packages: ''
           - python-version: '3.12'
             numpy-version: '1.26'
-            optional-packages: ' contextily geopandas ipython rioxarray sphinx-gallery'
+            optional-packages: ' contextily geopandas ipython pyarrow rioxarray sphinx-gallery'
 
     timeout-minutes: 30
     defaults:

pygmt/tests/test_clib_virtualfiles.py

@@ -13,6 +13,11 @@
 from pygmt.helpers import GMTTempFile
 from pygmt.tests.test_clib import mock
 
+try:
+    import pyarrow as pa
+except ImportError:
+    pa = None
+
 TEST_DATA_DIR = os.path.join(os.path.dirname(__file__), "data")
 POINTS_DATA = os.path.join(TEST_DATA_DIR, "points.txt")
 
@@ -321,16 +326,21 @@ def test_virtualfile_from_matrix_slice(dtypes):
 
 def test_virtualfile_from_vectors_pandas(dtypes):
     """
-    Pass vectors to a dataset using pandas Series.
+    Pass vectors to a dataset using pandas Series, checking both numpy and
+    pyarrow dtypes.
     """
     size = 13
+    if pa is not None:
+        dtypes.extend([f"{dtype}[pyarrow]" for dtype in dtypes])
+
     for dtype in dtypes:
         data = pd.DataFrame(
             data={
-                "x": np.arange(size, dtype=dtype),
-                "y": np.arange(size, size * 2, 1, dtype=dtype),
-                "z": np.arange(size * 2, size * 3, 1, dtype=dtype),
-            }
+                "x": np.arange(size),
+                "y": np.arange(size, size * 2, 1),
+                "z": np.arange(size * 2, size * 3, 1),
+            },
+            dtype=dtype,
         )
         with clib.Session() as lib:
             with lib.virtualfile_from_vectors(data.x, data.y, data.z) as vfile:

pygmt/tests/test_geopandas.py

@@ -3,6 +3,7 @@
 """
 import numpy.testing as npt
 import pandas as pd
+import pandas.util._test_decorators as td
 import pytest
 from pygmt import Figure, info, makecpt, which
 
@@ -141,6 +142,24 @@ def test_geopandas_plot3d_non_default_circle():
         "int64",
         pd.Int32Dtype(),
         pd.Int64Dtype(),
+        pytest.param(
+            "int32[pyarrow]",
+            marks=[
+                td.skip_if_no(package="pyarrow"),
+                pytest.mark.xfail(
+                    reason="geopandas doesn't support writing columns with pyarrow dtypes to OGR_GMT yet."
+                ),
+            ],
+        ),
+        pytest.param(
+            "int64[pyarrow]",
+            marks=[
+                td.skip_if_no(package="pyarrow"),
+                pytest.mark.xfail(
+                    reason="geopandas doesn't support writing columns with pyarrow dtypes to OGR_GMT yet."
+                ),
+            ],
+        ),
     ],
 )
 @pytest.mark.mpl_image_compare(filename="test_geopandas_plot_int_dtypes.png")

pygmt/tests/test_info.py

@@ -8,6 +8,7 @@
 import numpy as np
 import numpy.testing as npt
 import pandas as pd
+import pandas.util._test_decorators as td
 import pytest
 import xarray as xr
 from pygmt import info
@@ -74,16 +75,30 @@ def test_info_2d_list():
     assert output == expected_output
 
 
-def test_info_series():
+@pytest.mark.parametrize(
+    "dtype",
+    [
+        "int64",
+        pytest.param("int64[pyarrow]", marks=td.skip_if_no(package="pyarrow")),
+    ],
+)
+def test_info_series(dtype):
     """
     Make sure info works on a pandas.Series input.
     """
-    output = info(pd.Series(data=[0, 4, 2, 8, 6]))
+    output = info(pd.Series(data=[0, 4, 2, 8, 6], dtype=dtype))
     expected_output = "<vector memory>: N = 5 <0/8>\n"
     assert output == expected_output
 
 
-def test_info_dataframe():
+@pytest.mark.parametrize(
+    "dtype",
+    [
+        "float64",
+        pytest.param("float64[pyarrow]", marks=td.skip_if_no(package="pyarrow")),
+    ],
+)
+def test_info_dataframe(dtype):
     """
     Make sure info works on pandas.DataFrame inputs.
     """