Allow common builtins such as sum and super by default

src/pytest_prairielearn_grader/utils.py

@@ -257,6 +257,29 @@ def get_builtins(builtin_whitelist: list[str] | None) -> dict[str, Any]:
         "min",
         "max",
         "map",
+        # Not in RestrictedPython's list, but they don't give student code anything that plain Python
+        # syntax doesn't. Courses commonly use them, and without them, correct solutions fail with a
+        # NameError.
+        "all",
+        "any",
+        "ascii",
+        "bin",
+        "bytearray",
+        "classmethod",
+        "Ellipsis",
+        "filter",
+        "format",
+        "frozenset",
+        "iter",
+        "next",
+        "NotImplemented",
+        "object",
+        "property",
+        "reversed",
+        "staticmethod",
+        "sum",
+        "super",
+        "type",
     )
 
     _safe_exceptions = (

tests/scenario_root/test_default_builtins/expected_outcome.json

@@ -0,0 +1,34 @@
+{
+  "expected_data_object": {
+    "score": 1.0,
+    "tests": [
+      {
+        "max_points": 1,
+        "message": "",
+        "name": "common builtins",
+        "outcome": "passed",
+        "points": 1.0,
+        "points_frac": 1.0,
+        "test_id": "test_default_builtins.py::test_common_builtins[student_code]"
+      },
+      {
+        "max_points": 1,
+        "message": "",
+        "name": "classes",
+        "outcome": "passed",
+        "points": 1.0,
+        "points_frac": 1.0,
+        "test_id": "test_default_builtins.py::test_classes[student_code]"
+      },
+      {
+        "max_points": 1,
+        "message": "",
+        "name": "dangerous builtins stay blocked",
+        "outcome": "passed",
+        "points": 1.0,
+        "points_frac": 1.0,
+        "test_id": "test_default_builtins.py::test_open_blocked[student_code]"
+      }
+    ]
+  }
+}

tests/scenario_root/test_default_builtins/scenario.py

@@ -0,0 +1,34 @@
+"""Commonly used builtins are available to student code without a builtin_whitelist."""
+
+import pytest
+
+from pytest_prairielearn_grader.fixture import StudentFixture
+
+
+@pytest.mark.grading_data(name="common builtins", points=1)
+def test_common_builtins(sandbox: StudentFixture) -> None:
+    assert sandbox.query_function("common_builtins", [3, 1, 2]) == [
+        6,
+        True,
+        True,
+        [2, 1, 3],
+        [3, 1],
+        3,
+        [1, 2, 3],
+        "3.14",
+        "0b101",
+        "'\\xe9'",
+        "list",
+        True,
+    ]
+
+
+@pytest.mark.grading_data(name="classes", points=1)
+def test_classes(sandbox: StudentFixture) -> None:
+    assert sandbox.query_function("classes") == ["square!", 0, "circle"]
+
+
+@pytest.mark.grading_data(name="dangerous builtins stay blocked", points=1)
+def test_open_blocked(sandbox: StudentFixture) -> None:
+    response = sandbox.query_function_raw("call_open")
+    assert response["exception_name"] == "NameError"

tests/scenario_root/test_default_builtins/student_code.py

@@ -0,0 +1,46 @@
+class Shape:
+    def __init__(self, name):
+        self.name = name
+
+    @property
+    def label(self):
+        return f"{self.name}!"
+
+    @staticmethod
+    def sides():
+        return 0
+
+    @classmethod
+    def make(cls, name):
+        return cls(name)
+
+
+class Square(Shape):
+    def __init__(self):
+        super().__init__("square")
+
+
+def common_builtins(values):
+    return [
+        sum(values),
+        any(v > 2 for v in values),
+        all(v > 0 for v in values),
+        list(reversed(values)),
+        list(filter(lambda v: v % 2, values)),
+        next(iter(values)),
+        sorted(frozenset(values)),
+        format(3.14159, ".2f"),
+        bin(5),
+        ascii("é"),
+        type(values).__name__,
+        isinstance(object(), object),
+    ]
+
+
+def classes():
+    square = Square()
+    return [square.label, Square.sides(), Shape.make("circle").name]
+
+
+def call_open():
+    return open("data.txt").read()

tests/scenario_root/test_helper_modules_workspace/helper_function.py

@@ -6,4 +6,4 @@ def triple(x):
 
 
 def total(values):
-    return sum(values)
+    return vars(values)