Sometimes problems don’t fit into one of the collections like
dask.dataframe. In these cases, users can parallelize custom algorithms
using the simpler
dask.delayed interface. This allows one to create graphs
directly with a light annotation of normal python code.
>>> x = dask.delayed(inc)(1) >>> y = dask.delayed(inc)(2) >>> z = dask.delayed(add)(x, y) >>> z.compute() 7 >>> z.vizualize()