Introduction Overview Prepare Links Tutorial Structure Exercise: Print Hello, world! You can run this notebook in a live session or view it on Github . Introduction Wel...

DataFrame Examples Design Dask DataFrame copies the Pandas API Common Uses and Anti-Uses Scope Execution DataFrame A Dask DataFrame is a large parallel DataFrame composed...

IceCube: Detecting Cosmic Rays Who am I? What problem am I trying to solve? How Dask Helps us Pain points of using Dask Technology that we use around Dask IceCube: Detecti...

Asynchronous Operation Basic Operation Python 2 Compatibility Example Python 3 with Tornado or Asyncio Python 2/3 with Tornado Use Cases Asynchronous Operation Dask can r...

Best Practices Start Small Use The Dashboard Avoid Very Large Partitions Avoid Very Large Graphs Learn Techniques For Customization Stop Using Dask When No Longer Needed Pers...

API Datasets Utilities API Dask APIs generally follow from upstream APIs: Arrays follows NumPy DataFrames follows Pandas Bag follows map/filter/groupby/reduce common in ...

Configuration Access Configuration Specify Configuration YAML files Environment Variables Defaults Directly within Python Updating Configuration Manipulating configuration di...

GPUs Custom Computations High Level Collections DataFrames Arrays Scikit-Learn Setup Restricting Work Specifying GPUs per Machine Work in Progress GPUs Dask works with...

Joblib Joblib Many Scikit-Learn algorithms are written for parallel execution usingJoblib , which natively providesthread-based and process-based parallelism. Joblib is what ba...

Citations Papers about parts of Dask Citations Dask is developed by many people from many institutions. Some of thesedevelopers are academics who depend on academic citations ...