code: def test_group_by_binary_agg_with_literal() -> None:
      df = pl.DataFrame(
          {"id": ["a", "a", "b", "b"], "value": [1, 2, 3, 4]}
      )
  
      out = df.group_by("id", maintain_order=True).agg(
          pl.col("value") + pl.Series([1, 3])
      )
      assert out.to_dict(as_series=False) == {
          "id": ["a", "b"],
          "value": [[2, 5], [4, 7]],
      }
  
      out = df.group_by("id", maintain_order=True).agg(
          pl.col("value") + pl.lit(1)
      )
      assert out.to_dict(as_series=False) == {
          "id": ["a", "b"],
          "value": [[2, 3], [4, 5]],
      }
  
      out = df.group_by("id", maintain_order=True).agg(
          pl.lit(1) + pl.lit(2)
      )
      assert out.to_dict(as_series=False) == {
          "id": ["a", "b"],
          "literal": [3, 3],
      }
  
      out = df.group_by("id", maintain_order=True).agg(
          pl.lit(1) + pl.Series([2, 3])
      )
      assert out.to_dict(as_series=False) == {
          "id": ["a", "b"],
          "literal": [[3, 4], [3, 4]],
      }
  
      out = df.group_by("id", maintain_order=True).agg(
          value=pl.lit(pl.Series([1, 2])) + pl.lit(pl.Series([3, 4]))
      )
      assert out.to_dict(as_series=False) == {
          "id": ["a", "b"],
          "value": [[4, 6], [4, 6]],
      }
  
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 23 for calling a global function with example usage: test_group_by_binary_agg_with_literal() without return types