code: def test_pre_transform_cache_cleared():
      # Make sure that result changes when input DataFrame changes
      def check(n):
          order_items = pd.DataFrame({"menu_item": [0] * n + [1] * n})
  
          vega_spec = order_items_spec()
          new_spec, warnings = vf.runtime.pre_transform_spec(
              vega_spec,
              inline_datasets={
                  "order_items": order_items,
              },
          )
  
          assert new_spec["data"][1] == dict(
              name="data_0",
              values=[
                  {"menu_item": 0, "__count": n},
                  {"menu_item": 1, "__count": n},
              ],
          )
  
      check(16)
      check(32)
  
imports: import pandas
  import pytest
  from pandas import Timestamp, NaT
  import pyarrow
  import vegafusion
  import json
  import polars
  from datetime import date
  import decimal
  import base64
label_desc: Use image node_id 14 for calling a global function with example usage: test_pre_transform_cache_cleared() without return types