code: def test_map_partitions_df_input():
      """
      Check that map_partitions can handle a delayed
      partition of a dataframe input
      """
      pd = pytest.importorskip("pandas")
      dd = pytest.importorskip("dask.dataframe")
  
      def f(d, a):
          assert isinstance(d, pd.DataFrame)
          assert isinstance(a, pd.DataFrame)
          return d
  
      def main():
          item_df = dd.from_pandas(
              pd.DataFrame({"a": range(10)}), npartitions=1
          )
          ddf = item_df.to_delayed()[0].persist()
          merged_df = dd.from_pandas(
              pd.DataFrame({"b": range(10)}), npartitions=1
          )
  
          # Notice, we include a shuffle in order to trigger a complex culling
          merged_df = merged_df.shuffle(on="b", shuffle_method="tasks")
  
          merged_df.map_partitions(
              f, ddf, meta=merged_df, enforce_metadata=False
          ).compute()
  
      with distributed.LocalCluster(
          scheduler_port=0,
          # Explicitly disabling dashboard to prevent related warnings being
          # elevated to errors until `bokeh=3` is fully supported.
          # See https://github.com/dask/dask/issues/9686 and
          # https://github.com/dask/distributed/issues/7173 for details.
          dashboard_address=":0",
          scheduler_kwargs={"dashboard": False},
          asynchronous=False,
          n_workers=1,
          nthreads=1,
          processes=False,
      ) as cluster:
          with distributed.Client(cluster, asynchronous=False):
              main()
  
imports: from __future__ import annotations
  import pytest
  import asyncio
  import os
  import sys
  from functools import partial
  from operator import add
  from distributed import Client, SchedulerPlugin, WorkerPlugin
  from distributed.utils_test import cleanup
  from distributed.utils_test import client
  from distributed.utils_test import cluster, cluster_fixture, gen_cluster, loop, loop_in_thread, popen, varying
  import dask
  import dask.bag
  from dask import compute, delayed, persist
  from dask.base import compute_as_if_collection, get_scheduler
  from dask.blockwise import Blockwise
  from dask.delayed import Delayed
  from dask.distributed import futures_of, wait
  from dask.layers import ShuffleLayer, SimpleShuffleLayer
  from dask.utils import get_named_args, get_scheduler_lock, tmpdir, tmpfile
  from dask.utils_test import inc
label_desc: Use image node_id 23 for calling a global function with example usage: test_map_partitions_df_input() and returns: d