code: def test_group_by_args() -> None:
      df = pl.DataFrame(
          {
              "a": ["a", "b", "a", "b", "b", "c"],
              "b": [1, 2, 3, 4, 5, 6],
              "c": [6, 5, 4, 3, 2, 1],
          }
      )
  
      # Single column name
      assert df.group_by("a").agg("b").columns == ["a", "b"]
      # Column names as list
      expected = ["a", "b", "c"]
      assert df.group_by(["a", "b"]).agg("c").columns == expected
      # Column names as positional arguments
      assert df.group_by("a", "b").agg("c").columns == expected
      # With keyword argument
      assert (
          df.group_by("a", "b", maintain_order=True).agg("c").columns
          == expected
      )
      # Multiple aggregations as list
      assert df.group_by("a").agg(["b", "c"]).columns == expected
      # Multiple aggregations as positional arguments
      assert df.group_by("a").agg("b", "c").columns == expected
      # Multiple aggregations as keyword arguments
      assert df.group_by("a").agg(q="b", r="c").columns == [
          "a",
          "q",
          "r",
      ]
  
imports: from __future__ import annotations
  from collections import OrderedDict
  from datetime import datetime, timedelta
  from typing import Any
  import pytest
  import polars
  from polars.testing import assert_frame_equal, assert_series_equal
label_desc: Use image node_id 5 for calling a global function with example usage: test_group_by_args() without return types