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Update scikit-learn imports for version 1.8. #262

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Update scikit-learn imports for version 1.8. #262

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6 changes: 3 additions & 3 deletions pyproject.toml
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Original file line number Diff line number Diff line change
Expand Up @@ -7,9 +7,9 @@ name = "tabpfn-extensions"
version = "0.2.2"
dependencies = [
"torch>=2.1,<3",
"pandas>=1.4.0,<3",
"scikit-learn>=1.6.0,<1.7",
"scipy>=1.11.1,<2",
"pandas>=1.4.0",
"scikit-learn>=1.6.0",
"scipy>=1.11.1",
"tabpfn>=6.0.5,<8",
"tabpfn-common-utils[telemetry-interactive]>=0.2.0",
]
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15 changes: 13 additions & 2 deletions src/tabpfn_extensions/misc/sklearn_compat.py
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Expand Up @@ -245,7 +245,7 @@ def _raise_for_params(params, owner, method):
f" details. Extra parameters passed are: {set(params)}",
)

def _is_pandas_df(X):
def is_pandas_df(X):
"""Return True if the X is a pandas dataframe."""
try:
pd = sys.modules["pandas"]
Expand All @@ -260,7 +260,6 @@ def _is_pandas_df(X):
)
from sklearn.utils.validation import (
_is_fitted, # noqa: F401
_is_pandas_df, # noqa: F401
)


Expand Down Expand Up @@ -861,3 +860,15 @@ def parametrize_with_checks(
check_X_y, # noqa: F401
validate_data, # noqa: F401
)


########################################################################################
# Upgrading for scikit-learn 1.8
########################################################################################


if sklearn_version < parse_version("1.8"):
if sklearn_version >= parse_version("1.4"):
from sklearn.utils.validation import _is_pandas_df as is_pandas_df
else:
from sklearn.utils._dataframe import is_pandas_df # noqa: F401
Comment on lines +870 to +874
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@gemini-code-assist gemini-code-assist Bot Apr 10, 2026

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medium

The nested if structure can be simplified to a more readable if/elif block. Additionally, the import on line 872 is missing a # noqa: F401 comment, which is required by the project's linting rules (Ruff) for unused imports intended for export, as seen elsewhere in this file.

Suggested change
if sklearn_version < parse_version("1.8"):
if sklearn_version >= parse_version("1.4"):
from sklearn.utils.validation import _is_pandas_df as is_pandas_df
else:
from sklearn.utils._dataframe import is_pandas_df # noqa: F401
if sklearn_version >= parse_version("1.8"):
from sklearn.utils._dataframe import is_pandas_df # noqa: F401
elif sklearn_version >= parse_version("1.4"):
from sklearn.utils.validation import _is_pandas_df as is_pandas_df # noqa: F401

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