chore: import upstream snapshot with attribution

tests/resources/example_virtualenv_no_python_env/entrypoint.py

@@ -0,0 +1,33 @@
+import argparse
+import os
+import sys
+
+import numpy as np
+import sklearn
+from sklearn.pipeline import make_pipeline
+from sklearn.preprocessing import StandardScaler
+from sklearn.svm import SVC
+
+import mlflow
+
+parser = argparse.ArgumentParser()
+parser.add_argument(
+    "--test",
+    action="store_true",
+    help="If specified, check this script is running in a virtual environment created by mlflow "
+    "and python and sickit-learn versions are correct.",
+)
+args = parser.parse_args()
+if args.test:
+    assert "VIRTUAL_ENV" in os.environ
+    assert ".".join(map(str, sys.version_info[:3])) == "3.10.20", sys.version_info
+    assert sklearn.__version__ == "1.4.2", sklearn.__version__
+
+X = np.array([[-1, -1], [-2, -1], [1, 1], [2, 1]])
+y = np.array([1, 1, 2, 2])
+
+clf = make_pipeline(StandardScaler(), SVC(gamma="auto"))
+clf.fit(X, y)
+
+with mlflow.start_run():
+    mlflow.sklearn.log_model(clf, name="model")