DEPS: remove PY37 check from tests (pandas-dev#34472)

Author: fangchenli

pandas/__init__.py

@@ -184,181 +184,76 @@
 __git_version__ = v.get("full-revisionid")
 del get_versions, v
 
+
 # GH 27101
 # TODO: remove Panel compat in 1.0
-if pandas.compat.PY37:
-
-    def __getattr__(name):
-        import warnings
-
-        if name == "Panel":
-
-            warnings.warn(
-                "The Panel class is removed from pandas. Accessing it "
-                "from the top-level namespace will also be removed in the next version",
-                FutureWarning,
-                stacklevel=2,
-            )
-
-            class Panel:
-                pass
-
-            return Panel
-
-        elif name == "datetime":
-            warnings.warn(
-                "The pandas.datetime class is deprecated "
-                "and will be removed from pandas in a future version. "
-                "Import from datetime module instead.",
-                FutureWarning,
-                stacklevel=2,
-            )
-
-            from datetime import datetime as dt
-
-            return dt
-
-        elif name == "np":
-
-            warnings.warn(
-                "The pandas.np module is deprecated "
-                "and will be removed from pandas in a future version. "
-                "Import numpy directly instead",
-                FutureWarning,
-                stacklevel=2,
-            )
-            import numpy as np
-
-            return np
-
-        elif name in {"SparseSeries", "SparseDataFrame"}:
-            warnings.warn(
-                f"The {name} class is removed from pandas. Accessing it from "
-                "the top-level namespace will also be removed in the next version",
-                FutureWarning,
-                stacklevel=2,
-            )
-
-            return type(name, (), {})
-
-        elif name == "SparseArray":
-
-            warnings.warn(
-                "The pandas.SparseArray class is deprecated "
-                "and will be removed from pandas in a future version. "
-                "Use pandas.arrays.SparseArray instead.",
-                FutureWarning,
-                stacklevel=2,
-            )
-            from pandas.core.arrays.sparse import SparseArray as _SparseArray
+def __getattr__(name):
+    import warnings
 
-            return _SparseArray
+    if name == "Panel":
 
-        raise AttributeError(f"module 'pandas' has no attribute '{name}'")
+        warnings.warn(
+            "The Panel class is removed from pandas. Accessing it "
+            "from the top-level namespace will also be removed in the next version",
+            FutureWarning,
+            stacklevel=2,
+        )
 
+        class Panel:
+            pass
 
-else:
+        return Panel
 
-    class Panel:
-        pass
-
-    class SparseDataFrame:
-        pass
-
-    class SparseSeries:
-        pass
-
-    class __numpy:
-        def __init__(self):
-            import numpy as np
-            import warnings
-
-            self.np = np
-            self.warnings = warnings
-
-        def __getattr__(self, item):
-            self.warnings.warn(
-                "The pandas.np module is deprecated "
-                "and will be removed from pandas in a future version. "
-                "Import numpy directly instead",
-                FutureWarning,
-                stacklevel=2,
-            )
-
-            try:
-                return getattr(self.np, item)
-            except AttributeError as err:
-                raise AttributeError(f"module numpy has no attribute {item}") from err
-
-    np = __numpy()
-
-    class __Datetime(type):
+    elif name == "datetime":
+        warnings.warn(
+            "The pandas.datetime class is deprecated "
+            "and will be removed from pandas in a future version. "
+            "Import from datetime module instead.",
+            FutureWarning,
+            stacklevel=2,
+        )
 
         from datetime import datetime as dt
 
-        datetime = dt
-
-        def __getattr__(cls, item):
-            cls.emit_warning()
-
-            try:
-                return getattr(cls.datetime, item)
-            except AttributeError as err:
-                raise AttributeError(
-                    f"module datetime has no attribute {item}"
-                ) from err
-
-        def __instancecheck__(cls, other):
-            return isinstance(other, cls.datetime)
-
-    class __DatetimeSub(metaclass=__Datetime):
-        def emit_warning(dummy=0):
-            import warnings
-
-            warnings.warn(
-                "The pandas.datetime class is deprecated "
-                "and will be removed from pandas in a future version. "
-                "Import from datetime instead.",
-                FutureWarning,
-                stacklevel=3,
-            )
-
-        def __new__(cls, *args, **kwargs):
-            cls.emit_warning()
-            from datetime import datetime as dt
-
-            return dt(*args, **kwargs)
-
-    datetime = __DatetimeSub
+        return dt
 
-    class __SparseArray(type):
+    elif name == "np":
 
-        from pandas.core.arrays.sparse import SparseArray as sa
+        warnings.warn(
+            "The pandas.np module is deprecated "
+            "and will be removed from pandas in a future version. "
+            "Import numpy directly instead",
+            FutureWarning,
+            stacklevel=2,
+        )
+        import numpy as np
 
-        SparseArray = sa
+        return np
 
-        def __instancecheck__(cls, other):
-            return isinstance(other, cls.SparseArray)
+    elif name in {"SparseSeries", "SparseDataFrame"}:
+        warnings.warn(
+            f"The {name} class is removed from pandas. Accessing it from "
+            "the top-level namespace will also be removed in the next version",
+            FutureWarning,
+            stacklevel=2,
+        )
 
-    class __SparseArraySub(metaclass=__SparseArray):
-        def emit_warning(dummy=0):
-            import warnings
+        return type(name, (), {})
 
-            warnings.warn(
-                "The pandas.SparseArray class is deprecated "
-                "and will be removed from pandas in a future version. "
-                "Use pandas.arrays.SparseArray instead.",
-                FutureWarning,
-                stacklevel=3,
-            )
+    elif name == "SparseArray":
 
-        def __new__(cls, *args, **kwargs):
-            cls.emit_warning()
-            from pandas.core.arrays.sparse import SparseArray as sa
+        warnings.warn(
+            "The pandas.SparseArray class is deprecated "
+            "and will be removed from pandas in a future version. "
+            "Use pandas.arrays.SparseArray instead.",
+            FutureWarning,
+            stacklevel=2,
+        )
+        from pandas.core.arrays.sparse import SparseArray as _SparseArray
 
-            return sa(*args, **kwargs)
+        return _SparseArray
 
-    SparseArray = __SparseArraySub
+    raise AttributeError(f"module 'pandas' has no attribute '{name}'")
 
 
 # module level doc-string

pandas/compat/__init__.py

@@ -14,7 +14,6 @@
 
 from pandas._typing import F
 
-PY37 = sys.version_info >= (3, 7)
 PY38 = sys.version_info >= (3, 8)
 PY39 = sys.version_info >= (3, 9)
 PYPY = platform.python_implementation() == "PyPy"

pandas/core/frame.py

@@ -56,7 +56,6 @@
     Renamer,
     ValueKeyFunc,
 )
-from pandas.compat import PY37
 from pandas.compat._optional import import_optional_dependency
 from pandas.compat.numpy import function as nv
 from pandas.util._decorators import (
@@ -1066,9 +1065,7 @@ def itertuples(self, index=True, name="Pandas"):
         # use integer indexing because of possible duplicate column names
         arrays.extend(self.iloc[:, k] for k in range(len(self.columns)))
 
-        # Python versions before 3.7 support at most 255 arguments to constructors
-        can_return_named_tuples = PY37 or len(self.columns) + index < 255
-        if name is not None and can_return_named_tuples:
+        if name is not None:
             itertuple = collections.namedtuple(name, fields, rename=True)
             return map(itertuple._make, zip(*arrays))
 

pandas/tests/api/test_api.py

@@ -100,11 +100,6 @@ class TestPDApi(Base):
     # these should be deprecated in the future
     deprecated_classes_in_future: List[str] = ["SparseArray"]
 
-    if not compat.PY37:
-        classes.extend(["Panel", "SparseSeries", "SparseDataFrame"])
-        # deprecated_modules.extend(["np", "datetime"])
-        # deprecated_classes_in_future.extend(["SparseArray"])
-
     # external modules exposed in pandas namespace
     modules: List[str] = []
 
@@ -216,14 +211,6 @@ def test_api(self):
             + self.funcs_to
             + self.private_modules
         )
-        if not compat.PY37:
-            checkthese.extend(
-                self.deprecated_modules
-                + self.deprecated_classes
-                + self.deprecated_classes_in_future
-                + self.deprecated_funcs_in_future
-                + self.deprecated_funcs
-            )
         self.check(pd, checkthese, self.ignored)
 
     def test_depr(self):
@@ -236,14 +223,7 @@ def test_depr(self):
         )
         for depr in deprecated_list:
             with tm.assert_produces_warning(FutureWarning):
-                deprecated = getattr(pd, depr)
-                if not compat.PY37:
-                    if depr == "datetime":
-                        deprecated.__getattr__(dir(pd.datetime.datetime)[-1])
-                    elif depr == "SparseArray":
-                        deprecated([])
-                    else:
-                        deprecated.__getattr__(dir(deprecated)[-1])
+                _ = getattr(pd, depr)
 
 
 def test_datetime():

pandas/tests/extension/arrow/test_bool.py

@@ -1,8 +1,6 @@
 import numpy as np
 import pytest
 
-from pandas.compat import PY37
-
 import pandas as pd
 import pandas._testing as tm
 from pandas.tests.extension import base
@@ -62,13 +60,11 @@ def test_from_dtype(self, data):
     def test_from_sequence_from_cls(self, data):
         super().test_from_sequence_from_cls(data)
 
-    @pytest.mark.skipif(not PY37, reason="timeout on Linux py36_locale")
     @pytest.mark.xfail(reason="pa.NULL is not recognised as scalar, GH-33899")
     def test_series_constructor_no_data_with_index(self, dtype, na_value):
         # pyarrow.lib.ArrowInvalid: only handle 1-dimensional arrays
         super().test_series_constructor_no_data_with_index(dtype, na_value)
 
-    @pytest.mark.skipif(not PY37, reason="timeout on Linux py36_locale")
     @pytest.mark.xfail(reason="pa.NULL is not recognised as scalar, GH-33899")
     def test_series_constructor_scalar_na_with_index(self, dtype, na_value):
         # pyarrow.lib.ArrowInvalid: only handle 1-dimensional arrays

pandas/tests/frame/test_api.py

@@ -6,7 +6,6 @@
 import numpy as np
 import pytest
 
-from pandas.compat import PY37
 from pandas.util._test_decorators import async_mark, skip_if_no
 
 import pandas as pd
@@ -274,10 +273,7 @@ def test_itertuples(self, float_frame):
         # will raise SyntaxError if trying to create namedtuple
         tup3 = next(df3.itertuples())
         assert isinstance(tup3, tuple)
-        if PY37:
-            assert hasattr(tup3, "_fields")
-        else:
-            assert not hasattr(tup3, "_fields")
+        assert hasattr(tup3, "_fields")
 
         # GH 28282
         df_254_columns = DataFrame([{f"foo_{i}": f"bar_{i}" for i in range(254)}])
@@ -288,12 +284,7 @@ def test_itertuples(self, float_frame):
         df_255_columns = DataFrame([{f"foo_{i}": f"bar_{i}" for i in range(255)}])
         result_255_columns = next(df_255_columns.itertuples(index=False))
         assert isinstance(result_255_columns, tuple)
-
-        # Dataframes with >=255 columns will fallback to regular tuples on python < 3.7
-        if PY37:
-            assert hasattr(result_255_columns, "_fields")
-        else:
-            assert not hasattr(result_255_columns, "_fields")
+        assert hasattr(result_255_columns, "_fields")
 
     def test_sequence_like_with_categorical(self):
 

pandas/tests/frame/test_constructors.py

@@ -10,7 +10,7 @@
 import pytest
 import pytz
 
-from pandas.compat import PY37, is_platform_little_endian
+from pandas.compat import is_platform_little_endian
 from pandas.compat.numpy import _np_version_under1p19
 
 from pandas.core.dtypes.common import is_integer_dtype
@@ -1382,7 +1382,6 @@ def test_constructor_list_of_namedtuples(self):
         result = DataFrame(tuples, columns=["y", "z"])
         tm.assert_frame_equal(result, expected)
 
-    @pytest.mark.skipif(not PY37, reason="Requires Python >= 3.7")
     def test_constructor_list_of_dataclasses(self):
         # GH21910
         from dataclasses import make_dataclass
@@ -1394,7 +1393,6 @@ def test_constructor_list_of_dataclasses(self):
         result = DataFrame(datas)
         tm.assert_frame_equal(result, expected)
 
-    @pytest.mark.skipif(not PY37, reason="Requires Python >= 3.7")
     def test_constructor_list_of_dataclasses_with_varying_types(self):
         # GH21910
         from dataclasses import make_dataclass
@@ -1411,7 +1409,6 @@ def test_constructor_list_of_dataclasses_with_varying_types(self):
         result = DataFrame(datas)
         tm.assert_frame_equal(result, expected)
 
-    @pytest.mark.skipif(not PY37, reason="Requires Python >= 3.7")
     def test_constructor_list_of_dataclasses_error_thrown(self):
         # GH21910
         from dataclasses import make_dataclass