code: def dask_pipeline(
      df, schema, canvas, glyph, summary, *, antialias=False, cuda=False
  ):
      dsk, name = glyph_dispatch(
          glyph,
          df,
          schema,
          canvas,
          summary,
          antialias=antialias,
          cuda=cuda,
      )
  
      # Get user configured scheduler (if any), or fall back to default
      # scheduler for dask DataFrame
      scheduler = dask.base.get_scheduler() or df.__dask_scheduler__
  
      if isinstance(dsk, da.Array):
          return da.compute(dsk, scheduler=scheduler)[0]
  
      keys = df.__dask_keys__()
      optimize = df.__dask_optimize__
      graph = df.__dask_graph__()
  
      dsk.update(optimize(graph, keys))
      return scheduler(dsk, name)
  
file_path: datashader/datashader/data_libraries/dask.py
imports: from __future__ import annotations
  import numpy
  import pandas
  import dask
  import dask.array
  import dask.dataframe
  from dask.base import tokenize, compute
  from datashader.core import bypixel
  from datashader.utils import apply
  from datashader.compiler import compile_components
  from datashader.glyphs import Glyph, LineAxis0
  from datashader.utils import Dispatcher
label_desc: Use image node_id 1 for calling a global function with example usage: dask_pipeline(df, schema, canvas, glyph, summary) and returns: scheduler, da