fix: local TabPFN import drift and declare SciPy explicitly

pyproject.toml

@@ -31,6 +31,7 @@ dependencies = [
   "pydantic-settings>=2.4.0,<3",
   "rdkit>=2024.9.1",
   "scikit-learn>=1.9.0,<1.10",
+  "scipy>=1.11.1,<2",
   "colorama>=0.4.6,<0.5",
   "boruta>=0.4.3,<0.5",
   "quantile-forest>=1.4.2,<2"
@@ -71,7 +72,7 @@ clustering = [
 
 ### TabPFN
 tabpfn = [
-  "tabpfn==8.0.8",
+  "tabpfn==8.2.0",
   "torch>=2.3.0,<3",
 ]
 

src/mother/errors.py

@@ -9,8 +9,9 @@ def __init__(self, extras_type: str, nested_error: Exception):
         message: str = (
             f"\n\n📦 {nested_error}\n\n"
             + f"{Style.DIM}# Have you tried running the following?{Style.RESET_ALL}\n"
-            + f"$ {style}pip install 'mother[{extras_type}]'{Style.RESET_ALL} or\n"
-            + f"$ {style}uv add 'mother[{extras_type}]'{Style.RESET_ALL}"
+            + f"$ {style}pip install 'mother-ml[{extras_type}]'{Style.RESET_ALL} or\n"
+            + f"$ {style}uv add mother-ml --extra {extras_type}{Style.RESET_ALL} or\n"
+            + f"$ {style}uv sync --extra {extras_type}{Style.RESET_ALL}"
         )
         super().__init__(message)
 

src/mother/ml/models/m_tabpfn.py

@@ -46,7 +46,6 @@
 
 import numpy as np
 import pandas as pd
-import torch
 from optuna.trial import Trial
 from six import iteritems
 from sklearn.base import BaseEstimator, TransformerMixin, clone
@@ -60,9 +59,16 @@
 )
 from sklearn.utils import check_array
 from sklearn.utils.validation import check_is_fitted
-from tabpfn import TabPFNClassifier, TabPFNRegressor
-from tabpfn.constants import ModelVersion
-from tabpfn.regressor import FullOutputDict
+
+from mother.errors import ExtrasDependencyImportError
+
+try:
+    import torch
+    from tabpfn import TabPFNClassifier, TabPFNRegressor
+    from tabpfn.constants import ModelVersion
+    from tabpfn.regressor import FullOutputDict
+except ImportError as import_error:
+    raise ExtrasDependencyImportError("tabpfn", import_error) from import_error
 
 from mother.ml.core import AbstractMotherPipeline
 from mother.ml.models import utils

test/unit/test_errors.py

@@ -1,3 +1,9 @@
+import builtins
+import importlib
+import sys
+
+import pytest
+
 from mother.errors import ConfigurationError, ExtrasDependencyImportError
 
 
@@ -7,12 +13,41 @@ def test_extras_dependency_import_error():
 
     assert isinstance(error, ExtrasDependencyImportError)
     assert str(nested_error) in str(error)
-    assert "pip install 'mother[example]'" in str(error)
-    assert "uv add 'mother[example]'" in str(error)
+    assert "pip install 'mother-ml[example]'" in str(error)
+    assert "uv add mother-ml --extra example" in str(error)
+    assert "uv sync --extra example" in str(error)
 
 
 def test_configuration_error():
     error = ConfigurationError("Configuration is invalid")
 
     assert isinstance(error, ConfigurationError)
     assert str(error) == "Configuration is invalid"
+
+
+@pytest.mark.parametrize(
+    ("module_name", "import_error"),
+    [
+        ("torch", ModuleNotFoundError("No module named 'torch'")),
+        ("tabpfn", ImportError("tabpfn is incompatible with scikit-learn")),
+    ],
+    ids=["missing-torch", "tabpfn-import-error"],
+)
+def test_tabpfn_optional_dependency_imports_raise_extras_error(monkeypatch, module_name, import_error):
+    target_module = "mother.ml.models.m_tabpfn"
+    sys.modules.pop(target_module, None)
+
+    original_import = builtins.__import__
+
+    def guarded_import(name, globals=None, locals=None, fromlist=(), level=0):
+        if name == module_name:
+            raise import_error
+        return original_import(name, globals, locals, fromlist, level)
+
+    monkeypatch.setattr(builtins, "__import__", guarded_import)
+
+    with pytest.raises(ExtrasDependencyImportError) as exc_info:
+        importlib.import_module(target_module)
+
+    assert str(import_error) in str(exc_info.value)
+    assert "mother-ml[tabpfn]" in str(exc_info.value)