text: import dask
  import dask.dataframe as dd
  import pandas as pd
  
  dsk = {
      ("x", 0): pd.DataFrame({"a": [1, 2, 3], "b": [4, 5, 6]}, index=[0, 1, 3]),
      ("x", 1): pd.DataFrame({"a": [4, 5, 6], "b": [3, 2, 1]}, index=[5, 6, 8]),
      ("x", 2): pd.DataFrame({"a": [7, 8, 9], "b": [0, 0, 0]}, index=[9, 9, 9]),
  }
  dfs = list(dsk.values())
  
  
  def test_fuse_ave_width():
      df = pd.DataFrame({"x": range(10)})
      df = dd.from_pandas(df, npartitions=5)
  
      s = (df.x + 1) + (df.x + 2)
  
      with dask.config.set({"optimization.fuse.ave-width": 4}):
          a = s.__dask_optimize__(s.dask, s.__dask_keys__())
  
      b = s.__dask_optimize__(s.dask, s.__dask_keys__())
  
      assert len(a) <= 15
      assert len(b) <= 15
  
  
  def test_optimize_blockwise():
      from dask.array.optimization import optimize_blockwise
  
      df = pd.DataFrame({"x": range(10), "y": range(10)})
      ddf = dd.from_pandas(df, npartitions=2)
  
      for i in range(10):
          ddf["x"] = ddf.x + 1 + ddf.y
  
      graph = optimize_blockwise(ddf.dask)
  
      assert len(graph) <= 4
  