Avoid failing when a dependency is too old

(some of them are pulled in by other dependencies, so
just not including them in d/control doesn't stop them being installed)

Most of the content of this patch was generated by the following Python code:

import pathlib
import re

basedir = pathlib.Path.cwd()
if not (basedir / 'pandas/tests').exists():
    raise FileNotFoundError('must be run from the pandas root')
for source_file in basedir.glob('pandas/**/*.py'):
    with open(source_file, 'r') as fd:
        source_text = fd.read()
    if 'pytest.importorskip' in source_text:
        source_text = re.sub(r'pytest\.importorskip(.*)minversion', r'td.versioned_importorskip\1min_version', source_text)
        source_text = re.sub(r'pytest\.importorskip', r'td.versioned_importorskip', source_text)
        if '_test_decorators as td' not in source_text:
            # add the import if it isn't already present
            source_text, count = re.subn(r'^(import pandas|from pandas.*import)',r'import pandas.util._test_decorators as td\n\1', source_text, count=1, flags=re.MULTILINE)
            if count != 1:
                raise KeyError("failed to add import")
        with open(source_file, 'w') as fd:
            fd.write(source_text)

Author: Rebecca N. Palmer <[email protected]>
Forwarded: no


Gbp-Pq: Name versioned_importorskip.patch

Author: Debian Science Team

pandas/_testing/_io.py

@@ -107,9 +107,9 @@ def round_trip_localpath(writer, reader, path: str | None = None):
     pandas object
         The original object that was serialized and then re-read.
     """
-    import pytest
+    import pandas.util._test_decorators as td
 
-    LocalPath = pytest.importorskip("py.path").local
+    LocalPath = td.versioned_importorskip("py.path").local
     if path is None:
         path = "___localpath___"
     with ensure_clean(path) as path:

pandas/conftest.py

@@ -1816,7 +1816,7 @@ def ip():
 
     Will raise a skip if IPython is not installed.
     """
-    pytest.importorskip("IPython", minversion="6.0.0")
+    td.versioned_importorskip("IPython", min_version="6.0.0")
     from IPython.core.interactiveshell import InteractiveShell
 
     # GH#35711 make sure sqlite history file handle is not leaked
@@ -1833,7 +1833,7 @@ def spmatrix(request):
     """
     Yields scipy sparse matrix classes.
     """
-    sparse = pytest.importorskip("scipy.sparse")
+    sparse = td.versioned_importorskip("scipy.sparse")
 
     return getattr(sparse, request.param + "_matrix")
 

pandas/tests/apply/test_frame_apply.py

@@ -4,6 +4,7 @@
 import numpy as np
 import pytest
 
+import pandas.util._test_decorators as td
 from pandas.core.dtypes.dtypes import CategoricalDtype
 
 import pandas as pd
@@ -35,7 +36,7 @@ def int_frame_const_col():
 @pytest.fixture(params=["python", pytest.param("numba", marks=pytest.mark.single_cpu)])
 def engine(request):
     if request.param == "numba":
-        pytest.importorskip("numba")
+        td.versioned_importorskip("numba")
     return request.param
 
 

pandas/tests/apply/test_numba.py

@@ -26,7 +26,7 @@ def test_numba_vs_python_noop(float_frame, apply_axis):
 
 def test_numba_vs_python_string_index():
     # GH#56189
-    pytest.importorskip("pyarrow")
+    td.versioned_importorskip("pyarrow")
     df = DataFrame(
         1,
         index=Index(["a", "b"], dtype="string[pyarrow_numpy]"),

pandas/tests/arrays/categorical/test_warnings.py

@@ -1,12 +1,13 @@
 import pytest
 
+import pandas.util._test_decorators as td
 import pandas._testing as tm
 
 
 class TestCategoricalWarnings:
     def test_tab_complete_warning(self, ip):
         # https://github.com/pandas-dev/pandas/issues/16409
-        pytest.importorskip("IPython", minversion="6.0.0")
+        td.versioned_importorskip("IPython", min_version="6.0.0")
         from IPython.core.completer import provisionalcompleter
 
         code = "import pandas as pd; c = pd.Categorical([])"

pandas/tests/arrays/datetimes/test_constructors.py

@@ -1,6 +1,7 @@
 import numpy as np
 import pytest
 
+import pandas.util._test_decorators as td
 from pandas._libs import iNaT
 
 from pandas.core.dtypes.dtypes import DatetimeTZDtype
@@ -226,7 +227,7 @@ def test_2d(self, order):
 def test_from_arrow_with_different_units_and_timezones_with(
     pa_unit, pd_unit, pa_tz, pd_tz, data
 ):
-    pa = pytest.importorskip("pyarrow")
+    pa = td.versioned_importorskip("pyarrow")
 
     pa_type = pa.timestamp(pa_unit, tz=pa_tz)
     arr = pa.array(data, type=pa_type)
@@ -253,7 +254,7 @@ def test_from_arrow_with_different_units_and_timezones_with(
     ],
 )
 def test_from_arrow_from_empty(unit, tz):
-    pa = pytest.importorskip("pyarrow")
+    pa = td.versioned_importorskip("pyarrow")
 
     data = []
     arr = pa.array(data)
@@ -269,7 +270,7 @@ def test_from_arrow_from_empty(unit, tz):
 
 
 def test_from_arrow_from_integers():
-    pa = pytest.importorskip("pyarrow")
+    pa = td.versioned_importorskip("pyarrow")
 
     data = [0, 123456789, None, 2**63 - 1, iNaT, -123456789]
     arr = pa.array(data)

pandas/tests/arrays/interval/test_interval_pyarrow.py

@@ -1,13 +1,14 @@
 import numpy as np
 import pytest
 
+import pandas.util._test_decorators as td
 import pandas as pd
 import pandas._testing as tm
 from pandas.core.arrays import IntervalArray
 
 
 def test_arrow_extension_type():
-    pa = pytest.importorskip("pyarrow")
+    pa = td.versioned_importorskip("pyarrow")
 
     from pandas.core.arrays.arrow.extension_types import ArrowIntervalType
 
@@ -23,7 +24,7 @@ def test_arrow_extension_type():
 
 
 def test_arrow_array():
-    pa = pytest.importorskip("pyarrow")
+    pa = td.versioned_importorskip("pyarrow")
 
     from pandas.core.arrays.arrow.extension_types import ArrowIntervalType
 
@@ -52,7 +53,7 @@ def test_arrow_array():
 
 
 def test_arrow_array_missing():
-    pa = pytest.importorskip("pyarrow")
+    pa = td.versioned_importorskip("pyarrow")
 
     from pandas.core.arrays.arrow.extension_types import ArrowIntervalType
 
@@ -89,7 +90,7 @@ def test_arrow_array_missing():
     ids=["float", "datetime64[ns]"],
 )
 def test_arrow_table_roundtrip(breaks):
-    pa = pytest.importorskip("pyarrow")
+    pa = td.versioned_importorskip("pyarrow")
 
     from pandas.core.arrays.arrow.extension_types import ArrowIntervalType
 
@@ -125,7 +126,7 @@ def test_arrow_table_roundtrip(breaks):
     ids=["float", "datetime64[ns]"],
 )
 def test_arrow_table_roundtrip_without_metadata(breaks):
-    pa = pytest.importorskip("pyarrow")
+    pa = td.versioned_importorskip("pyarrow")
 
     arr = IntervalArray.from_breaks(breaks)
     arr[1] = None
@@ -145,7 +146,7 @@ def test_from_arrow_from_raw_struct_array():
     # in case pyarrow lost the Interval extension type (eg on parquet roundtrip
     # with datetime64[ns] subtype, see GH-45881), still allow conversion
     # from arrow to IntervalArray
-    pa = pytest.importorskip("pyarrow")
+    pa = td.versioned_importorskip("pyarrow")
 
     arr = pa.array([{"left": 0, "right": 1}, {"left": 1, "right": 2}])
     dtype = pd.IntervalDtype(np.dtype("int64"), closed="neither")

pandas/tests/arrays/masked/test_arrow_compat.py

@@ -1,14 +1,15 @@
 import numpy as np
 import pytest
 
+import pandas.util._test_decorators as td
 import pandas as pd
 import pandas._testing as tm
 
 pytestmark = pytest.mark.filterwarnings(
     "ignore:Passing a BlockManager to DataFrame:DeprecationWarning"
 )
 
-pa = pytest.importorskip("pyarrow")
+pa = td.versioned_importorskip("pyarrow")
 
 from pandas.core.arrays.arrow._arrow_utils import pyarrow_array_to_numpy_and_mask
 

pandas/tests/arrays/period/test_arrow_compat.py

@@ -1,5 +1,6 @@
 import pytest
 
+import pandas.util._test_decorators as td
 from pandas.compat.pyarrow import pa_version_under10p1
 
 from pandas.core.dtypes.dtypes import PeriodDtype
@@ -16,7 +17,7 @@
 )
 
 
-pa = pytest.importorskip("pyarrow")
+pa = td.versioned_importorskip("pyarrow")
 
 
 def test_arrow_extension_type():

pandas/tests/arrays/sparse/test_accessor.py

@@ -3,6 +3,7 @@
 import numpy as np
 import pytest
 
+import pandas.util._test_decorators as td
 import pandas as pd
 from pandas import SparseDtype
 import pandas._testing as tm
@@ -26,7 +27,7 @@ def test_get_attributes(self, attr):
         assert result == expected
 
     def test_from_coo(self):
-        scipy_sparse = pytest.importorskip("scipy.sparse")
+        scipy_sparse = td.versioned_importorskip("scipy.sparse")
 
         row = [0, 3, 1, 0]
         col = [0, 3, 1, 2]
@@ -64,7 +65,7 @@ def test_from_coo(self):
     def test_to_coo(
         self, sort_labels, expected_rows, expected_cols, expected_values_pos
     ):
-        sp_sparse = pytest.importorskip("scipy.sparse")
+        sp_sparse = td.versioned_importorskip("scipy.sparse")
 
         values = SparseArray([0, np.nan, 1, 0, None, 3], fill_value=0)
         index = pd.MultiIndex.from_tuples(
@@ -107,7 +108,7 @@ def test_accessor_raises(self):
     @pytest.mark.parametrize("labels", [None, list(string.ascii_letters[:10])])
     @pytest.mark.parametrize("dtype", ["float64", "int64"])
     def test_from_spmatrix(self, format, labels, dtype):
-        sp_sparse = pytest.importorskip("scipy.sparse")
+        sp_sparse = td.versioned_importorskip("scipy.sparse")
 
         sp_dtype = SparseDtype(dtype, np.array(0, dtype=dtype).item())
 
@@ -120,7 +121,7 @@ def test_from_spmatrix(self, format, labels, dtype):
 
     @pytest.mark.parametrize("format", ["csc", "csr", "coo"])
     def test_from_spmatrix_including_explicit_zero(self, format):
-        sp_sparse = pytest.importorskip("scipy.sparse")
+        sp_sparse = td.versioned_importorskip("scipy.sparse")
 
         mat = sp_sparse.random(10, 2, density=0.5, format=format)
         mat.data[0] = 0
@@ -134,7 +135,7 @@ def test_from_spmatrix_including_explicit_zero(self, format):
         [["a", "b"], pd.MultiIndex.from_product([["A"], ["a", "b"]]), ["a", "a"]],
     )
     def test_from_spmatrix_columns(self, columns):
-        sp_sparse = pytest.importorskip("scipy.sparse")
+        sp_sparse = td.versioned_importorskip("scipy.sparse")
 
         dtype = SparseDtype("float64", 0.0)
 
@@ -147,7 +148,7 @@ def test_from_spmatrix_columns(self, columns):
         "colnames", [("A", "B"), (1, 2), (1, pd.NA), (0.1, 0.2), ("x", "x"), (0, 0)]
     )
     def test_to_coo(self, colnames):
-        sp_sparse = pytest.importorskip("scipy.sparse")
+        sp_sparse = td.versioned_importorskip("scipy.sparse")
 
         df = pd.DataFrame(
             {colnames[0]: [0, 1, 0], colnames[1]: [1, 0, 0]}, dtype="Sparse[int64, 0]"
@@ -158,7 +159,7 @@ def test_to_coo(self, colnames):
 
     @pytest.mark.parametrize("fill_value", [1, np.nan])
     def test_to_coo_nonzero_fill_val_raises(self, fill_value):
-        pytest.importorskip("scipy")
+        td.versioned_importorskip("scipy")
         df = pd.DataFrame(
             {
                 "A": SparseArray(
@@ -174,7 +175,7 @@ def test_to_coo_nonzero_fill_val_raises(self, fill_value):
 
     def test_to_coo_midx_categorical(self):
         # GH#50996
-        sp_sparse = pytest.importorskip("scipy.sparse")
+        sp_sparse = td.versioned_importorskip("scipy.sparse")
 
         midx = pd.MultiIndex.from_arrays(
             [
@@ -219,7 +220,7 @@ def test_density(self):
     @pytest.mark.parametrize("dtype", ["int64", "float64"])
     @pytest.mark.parametrize("dense_index", [True, False])
     def test_series_from_coo(self, dtype, dense_index):
-        sp_sparse = pytest.importorskip("scipy.sparse")
+        sp_sparse = td.versioned_importorskip("scipy.sparse")
 
         A = sp_sparse.eye(3, format="coo", dtype=dtype)
         result = pd.Series.sparse.from_coo(A, dense_index=dense_index)
@@ -239,7 +240,7 @@ def test_series_from_coo(self, dtype, dense_index):
 
     def test_series_from_coo_incorrect_format_raises(self):
         # gh-26554
-        sp_sparse = pytest.importorskip("scipy.sparse")
+        sp_sparse = td.versioned_importorskip("scipy.sparse")
 
         m = sp_sparse.csr_matrix(np.array([[0, 1], [0, 0]]))
         with pytest.raises(