ENH: Use find_stack_level (#44416)

Author: rhshadrach

pandas/_testing/asserters.py

@@ -11,6 +11,7 @@
 )
 from pandas._libs.missing import is_matching_na
 import pandas._libs.testing as _testing
+from pandas.util._exceptions import find_stack_level
 
 from pandas.core.dtypes.common import (
     is_bool,
@@ -106,7 +107,7 @@ def assert_almost_equal(
             "is deprecated and will be removed in a future version. "
             "You can stop passing 'check_less_precise' to silence this warning.",
             FutureWarning,
-            stacklevel=2,
+            stacklevel=find_stack_level(),
         )
         # https://github.com/python/mypy/issues/7642
         # error: Argument 1 to "_get_tol_from_less_precise" has incompatible
@@ -340,7 +341,7 @@ def _get_ilevel_values(index, level):
             "is deprecated and will be removed in a future version. "
             "You can stop passing 'check_less_precise' to silence this warning.",
             FutureWarning,
-            stacklevel=2,
+            stacklevel=find_stack_level(),
         )
         # https://github.com/python/mypy/issues/7642
         # error: Argument 1 to "_get_tol_from_less_precise" has incompatible
@@ -818,7 +819,7 @@ def assert_extension_array_equal(
             "is deprecated and will be removed in a future version. "
             "You can stop passing 'check_less_precise' to silence this warning.",
             FutureWarning,
-            stacklevel=2,
+            stacklevel=find_stack_level(),
         )
         rtol = atol = _get_tol_from_less_precise(check_less_precise)
 
@@ -964,7 +965,7 @@ def assert_series_equal(
             "is deprecated and will be removed in a future version. "
             "You can stop passing 'check_less_precise' to silence this warning.",
             FutureWarning,
-            stacklevel=2,
+            stacklevel=find_stack_level(),
         )
         rtol = atol = _get_tol_from_less_precise(check_less_precise)
 
@@ -1247,7 +1248,7 @@ def assert_frame_equal(
             "is deprecated and will be removed in a future version. "
             "You can stop passing 'check_less_precise' to silence this warning.",
             FutureWarning,
-            stacklevel=2,
+            stacklevel=find_stack_level(),
         )
         rtol = atol = _get_tol_from_less_precise(check_less_precise)
 

pandas/io/common.py

@@ -49,6 +49,7 @@
     import_lzma,
 )
 from pandas.compat._optional import import_optional_dependency
+from pandas.util._exceptions import find_stack_level
 
 from pandas.core.dtypes.common import is_file_like
 
@@ -270,7 +271,7 @@ def _get_filepath_or_buffer(
         warnings.warn(
             "compression has no effect when passing a non-binary object as input.",
             RuntimeWarning,
-            stacklevel=2,
+            stacklevel=find_stack_level(),
         )
         compression_method = None
 

pandas/io/date_converters.py

@@ -4,6 +4,7 @@
 import numpy as np
 
 from pandas._libs.tslibs import parsing
+from pandas.util._exceptions import find_stack_level
 
 
 def parse_date_time(date_col, time_col):
@@ -18,7 +19,7 @@ def parse_date_time(date_col, time_col):
         Use pd.to_datetime(date_col + " " + time_col).to_pydatetime() instead to get a Numpy array.
 """,  # noqa: E501
         FutureWarning,
-        stacklevel=2,
+        stacklevel=find_stack_level(),
     )
     date_col = _maybe_cast(date_col)
     time_col = _maybe_cast(time_col)
@@ -38,7 +39,7 @@ def parse_date_fields(year_col, month_col, day_col):
         np.array([s.to_pydatetime() for s in ser]) instead to get a Numpy array.
 """,  # noqa: E501
         FutureWarning,
-        stacklevel=2,
+        stacklevel=find_stack_level(),
     )
 
     year_col = _maybe_cast(year_col)
@@ -63,7 +64,7 @@ def parse_all_fields(year_col, month_col, day_col, hour_col, minute_col, second_
         np.array([s.to_pydatetime() for s in ser]) instead to get a Numpy array.
 """,  # noqa: E501
         FutureWarning,
-        stacklevel=2,
+        stacklevel=find_stack_level(),
     )
 
     year_col = _maybe_cast(year_col)
@@ -89,7 +90,7 @@ def generic_parser(parse_func, *cols):
         Use pd.to_datetime instead.
 """,
         FutureWarning,
-        stacklevel=2,
+        stacklevel=find_stack_level(),
     )
 
     N = _check_columns(cols)

pandas/io/excel/_base.py

@@ -833,7 +833,7 @@ def __new__(
             warnings.warn(
                 "Use of **kwargs is deprecated, use engine_kwargs instead.",
                 FutureWarning,
-                stacklevel=2,
+                stacklevel=find_stack_level(),
             )
 
         # only switch class if generic(ExcelWriter)
@@ -868,7 +868,7 @@ def __new__(
                         "deprecated and will also raise a warning, it can "
                         "be globally set and the warning suppressed.",
                         FutureWarning,
-                        stacklevel=4,
+                        stacklevel=find_stack_level(),
                     )
 
             cls = get_writer(engine)

pandas/io/parsers/base_parser.py

@@ -32,6 +32,7 @@
     ParserError,
     ParserWarning,
 )
+from pandas.util._exceptions import find_stack_level
 
 from pandas.core.dtypes.cast import astype_nansafe
 from pandas.core.dtypes.common import (
@@ -558,7 +559,7 @@ def _convert_to_ndarrays(
                             f"for column {c} - only the converter will be used."
                         ),
                         ParserWarning,
-                        stacklevel=7,
+                        stacklevel=find_stack_level(),
                     )
 
                 try:
@@ -830,7 +831,7 @@ def _check_data_length(self, columns: list[str], data: list[ArrayLike]) -> None:
                 "Length of header or names does not match length of data. This leads "
                 "to a loss of data with index_col=False.",
                 ParserWarning,
-                stacklevel=6,
+                stacklevel=find_stack_level(),
             )
 
     def _evaluate_usecols(self, usecols, names):

pandas/io/parsers/c_parser_wrapper.py

@@ -10,6 +10,7 @@
     FilePathOrBuffer,
 )
 from pandas.errors import DtypeWarning
+from pandas.util._exceptions import find_stack_level
 
 from pandas.core.dtypes.common import (
     is_categorical_dtype,
@@ -387,7 +388,7 @@ def _concatenate_chunks(chunks: list[dict[int, ArrayLike]]) -> dict:
                 f"Specify dtype option on import or set low_memory=False."
             ]
         )
-        warnings.warn(warning_message, DtypeWarning, stacklevel=8)
+        warnings.warn(warning_message, DtypeWarning, stacklevel=find_stack_level())
     return result
 
 

pandas/io/parsers/python_parser.py

@@ -24,6 +24,7 @@
     EmptyDataError,
     ParserError,
 )
+from pandas.util._exceptions import find_stack_level
 
 from pandas.core.dtypes.common import is_integer
 from pandas.core.dtypes.inference import is_dict_like
@@ -555,7 +556,7 @@ def _handle_usecols(
                         "Defining usecols with out of bounds indices is deprecated "
                         "and will raise a ParserError in a future version.",
                         FutureWarning,
-                        stacklevel=8,
+                        stacklevel=find_stack_level(),
                     )
                 col_indices = self.usecols
 

pandas/io/parsers/readers.py

@@ -1041,7 +1041,7 @@ def _clean_options(self, options, engine):
                     "engine='python'."
                 ),
                 ParserWarning,
-                stacklevel=5,
+                stacklevel=find_stack_level(),
             )
 
         index_col = options["index_col"]
@@ -1573,7 +1573,9 @@ def _merge_with_dialect_properties(
                 conflict_msgs.append(msg)
 
         if conflict_msgs:
-            warnings.warn("\n\n".join(conflict_msgs), ParserWarning, stacklevel=2)
+            warnings.warn(
+                "\n\n".join(conflict_msgs), ParserWarning, stacklevel=find_stack_level()
+            )
         kwds[param] = dialect_val
     return kwds
 

pandas/io/pytables.py

@@ -45,6 +45,7 @@
 from pandas.compat.pickle_compat import patch_pickle
 from pandas.errors import PerformanceWarning
 from pandas.util._decorators import cache_readonly
+from pandas.util._exceptions import find_stack_level
 
 from pandas.core.dtypes.common import (
     ensure_object,
@@ -2190,7 +2191,9 @@ def update_info(self, info):
                 # frequency/name just warn
                 if key in ["freq", "index_name"]:
                     ws = attribute_conflict_doc % (key, existing_value, value)
-                    warnings.warn(ws, AttributeConflictWarning, stacklevel=6)
+                    warnings.warn(
+                        ws, AttributeConflictWarning, stacklevel=find_stack_level()
+                    )
 
                     # reset
                     idx[key] = None
@@ -3080,7 +3083,7 @@ def write_array(
                 pass
             else:
                 ws = performance_doc % (inferred_type, key, items)
-                warnings.warn(ws, PerformanceWarning, stacklevel=7)
+                warnings.warn(ws, PerformanceWarning, stacklevel=find_stack_level())
 
             vlarr = self._handle.create_vlarray(self.group, key, _tables().ObjectAtom())
             vlarr.append(value)

pandas/io/sql.py

@@ -28,6 +28,7 @@
 from pandas._typing import DtypeArg
 from pandas.compat._optional import import_optional_dependency
 from pandas.errors import AbstractMethodError
+from pandas.util._exceptions import find_stack_level
 
 from pandas.core.dtypes.common import (
     is_datetime64tz_dtype,
@@ -1159,7 +1160,7 @@ def _sqlalchemy_type(self, col):
                 "the 'timedelta' type is not supported, and will be "
                 "written as integer values (ns frequency) to the database.",
                 UserWarning,
-                stacklevel=8,
+                stacklevel=find_stack_level(),
             )
             return BigInteger
         elif col_type == "floating":
@@ -1886,7 +1887,7 @@ def _create_table_setup(self):
         pat = re.compile(r"\s+")
         column_names = [col_name for col_name, _, _ in column_names_and_types]
         if any(map(pat.search, column_names)):
-            warnings.warn(_SAFE_NAMES_WARNING, stacklevel=6)
+            warnings.warn(_SAFE_NAMES_WARNING, stacklevel=find_stack_level())
 
         escape = _get_valid_sqlite_name
 
@@ -1948,7 +1949,7 @@ def _sql_type_name(self, col):
                 "the 'timedelta' type is not supported, and will be "
                 "written as integer values (ns frequency) to the database.",
                 UserWarning,
-                stacklevel=8,
+                stacklevel=find_stack_level(),
             )
             col_type = "integer"
 

pandas/plotting/_matplotlib/tools.py

@@ -13,6 +13,8 @@
 import matplotlib.ticker as ticker
 import numpy as np
 
+from pandas.util._exceptions import find_stack_level
+
 from pandas.core.dtypes.common import is_list_like
 from pandas.core.dtypes.generic import (
     ABCDataFrame,
@@ -233,7 +235,7 @@ def create_subplots(
                     "When passing multiple axes, sharex and sharey "
                     "are ignored. These settings must be specified when creating axes.",
                     UserWarning,
-                    stacklevel=4,
+                    stacklevel=find_stack_level(),
                 )
             if ax.size == naxes:
                 fig = ax.flat[0].get_figure()
@@ -256,7 +258,7 @@ def create_subplots(
                 "To output multiple subplots, the figure containing "
                 "the passed axes is being cleared.",
                 UserWarning,
-                stacklevel=4,
+                stacklevel=find_stack_level(),
             )
             fig.clear()
 

pandas/tseries/frequencies.py

@@ -29,6 +29,7 @@
 from pandas._libs.tslibs.parsing import get_rule_month
 from pandas._typing import npt
 from pandas.util._decorators import cache_readonly
+from pandas.util._exceptions import find_stack_level
 
 from pandas.core.dtypes.common import (
     is_datetime64_dtype,
@@ -116,7 +117,7 @@ def get_offset(name: str) -> DateOffset:
         "get_offset is deprecated and will be removed in a future version, "
         "use to_offset instead.",
         FutureWarning,
-        stacklevel=2,
+        stacklevel=find_stack_level(),
     )
     return _get_offset(name)
 

pandas/util/_validators.py

@@ -12,6 +12,8 @@
 
 import numpy as np
 
+from pandas.util._exceptions import find_stack_level
+
 from pandas.core.dtypes.common import (
     is_bool,
     is_integer,
@@ -339,7 +341,7 @@ def validate_axis_style_args(data, args, kwargs, arg_name, method_name):
             "positional arguments for 'index' or 'columns' will raise "
             "a 'TypeError'."
         )
-        warnings.warn(msg, FutureWarning, stacklevel=4)
+        warnings.warn(msg, FutureWarning, stacklevel=find_stack_level())
         out[data._get_axis_name(0)] = args[0]
         out[data._get_axis_name(1)] = args[1]
     else:

pandas/util/testing.py

@@ -1,5 +1,7 @@
 import warnings
 
+from pandas.util._exceptions import find_stack_level
+
 from pandas._testing import *  # noqa
 
 warnings.warn(
@@ -8,5 +10,5 @@
         "public API at pandas.testing instead."
     ),
     FutureWarning,
-    stacklevel=2,
+    stacklevel=find_stack_level(),
 )