Support doc link for the sklearn module. (#10287)

tests/ci_build/conda_env/linux_cpu_test.yml

@@ -14,7 +14,7 @@ dependencies:
 - pylint
 - numpy
 - scipy
-- scikit-learn
+- scikit-learn>=1.4.1
 - pandas
 - matplotlib
 - dask

tests/ci_build/conda_env/macos_cpu_test.yml

@@ -11,7 +11,7 @@ dependencies:
 - numpy
 - scipy
 - llvm-openmp
-- scikit-learn
+- scikit-learn>=1.4.1
 - pandas
 - matplotlib
 - dask

tests/ci_build/conda_env/win64_cpu_test.yml

@@ -6,7 +6,7 @@ dependencies:
 - wheel
 - numpy
 - scipy
-- scikit-learn
+- scikit-learn>=1.4.1
 - pandas
 - matplotlib
 - dask

tests/python/test_basic.py

@@ -9,6 +9,7 @@ import pytest
 
 import xgboost as xgb
 from xgboost import testing as tm
+from xgboost.core import _parse_version
 
 dpath = "demo/data/"
 rng = np.random.RandomState(1994)
@@ -315,3 +316,14 @@ class TestBasicPathLike:
         """An invalid model_file path should raise XGBoostError."""
         with pytest.raises(xgb.core.XGBoostError):
             xgb.Booster(model_file=Path("invalidpath"))
+
+
+def test_parse_ver() -> None:
+    (major, minor, patch), post = _parse_version("2.1.0")
+    assert post == ""
+    (major, minor, patch), post = _parse_version("2.1.0-dev")
+    assert post == "dev"
+    (major, minor, patch), post = _parse_version("2.1.0rc1")
+    assert post == "rc1"
+    (major, minor, patch), post = _parse_version("2.1.0.post1")
+    assert post == "post1"

tests/python/test_with_sklearn.py

@@ -1484,3 +1484,16 @@ def test_tags() -> None:
 
     tags = xgb.XGBRanker()._more_tags()
     assert "multioutput" not in tags
+
+
+def test_doc_link() -> None:
+    for est in [
+        xgb.XGBRegressor(),
+        xgb.XGBClassifier(),
+        xgb.XGBRanker(),
+        xgb.XGBRFRegressor(),
+        xgb.XGBRFClassifier(),
+    ]:
+        name = est.__class__.__name__
+        link = est._get_doc_link()
+        assert f"xgboost.{name}" in link

tests/test_distributed/test_with_dask/test_with_dask.py

@@ -35,6 +35,7 @@ from hypothesis import HealthCheck, assume, given, note, settings
 from sklearn.datasets import make_classification, make_regression
 
 import xgboost as xgb
+from xgboost import dask as dxgb
 from xgboost import testing as tm
 from xgboost.data import _is_cudf_df
 from xgboost.testing.params import hist_cache_strategy, hist_parameter_strategy
@@ -2324,3 +2325,16 @@ async def test_worker_restarted(c, s, a, b):
             d_train,
             evals=[(d_train, "train")],
         )
+
+
+def test_doc_link() -> None:
+    for est in [
+        dxgb.DaskXGBRegressor(),
+        dxgb.DaskXGBClassifier(),
+        dxgb.DaskXGBRanker(),
+        dxgb.DaskXGBRFRegressor(),
+        dxgb.DaskXGBRFClassifier(),
+    ]:
+        name = est.__class__.__name__
+        link = est._get_doc_link()
+        assert f"xgboost.dask.{name}" in link