These materials provide a brief hands-on introduction to the parallel computing system, Dask. They are intended to be delivered over a 90 minute session and cover the following topics.
- Parallelize existing code with dask.delayed
- Set up the dask.distributed system on your local laptop
- Use Dask.dataframe on time series data
These topics are far from comprehensive, but have been chosen to give a flavor for what can be done with Dask.
These materials are presented as Jupyter notebooks, which should be available within this directory. They depend on the following libraries
conda install -c conda-forge dask distributed jupyter bokeh feather-format
pip install pandas_datareader
Artificial data is automatically generated as part of the notebooks.