fkromer/awesome-dask

awesome-dask

Advanced parallelism for analytics.

Packages

• Dask
  • Dask (pypi)
  • Dask (docs)
  • Dask (source code)
• Dask.distributed
  • Dask.distributed (docs)
  • Dask.distributed (source code)
• daskperiment
  • daskperiment (pypi)
  • daskperiment (docs)
  • daskperiment (source code)
• dask-cloudprovider
  • dask-cloudprovider (pypi)
  • dask-cloudprovider (docs)
  • dask-cloudprovider (source code)
• dask-gateway
  • dask-gateway (pypi)
  • dask-gateway (docs)
  • dask-gateway (source code)
• dask-image
  • dask-image (docs)
  • dask-image (source code)
• dask-jobqueue
  • dask-jobqueue (docs)
  • dask-jobqueue (source code)
• dask-labextension
  • dask-labextension (pypi)
• dask-memusage
  • dask-memusage (source code)
• dask-ml
  • dask-ml (pypi)
  • dask-ml (docs)
  • dask-ml (source code)
• dask-kubernetes
  • dask-kubernetes (pypi)
  • dask-kubernetes (docs)
  • dask-kubernetes (source code)
• dask-rasterio
  • dask-rasterio (pypi)
  • dask-rasterio (source code)
• dask-tensorflow
  • dask-tensorflow (pypi)

Docker images

• daskdev images (DockerHub)

Cheat sheets

• Official Cheatsheet

Examples and Tutorials

• Dask Examples
• Live Dask Examples on Binder
• Dask Tutorial
• Parallelizing Scientific Python with Dask - SciPy 2018 Tutorial (3:20 h video) - Tutorial recording.

Documentation

• API
• Array
  • Design
  • Best Practices
• Bag
  • Common uses
  • Known Limitations
• DataFrame
  • Design
  • Best Practices
  • Common uses and anti-uses
• Delayed
  • Best Practices

Blog posts

• Ultimate guide to handle Big Datasets for Machine Learning using Dask (in Python) (August 9, 2018)

Presentations

• Official Youtube Channel
  • Dask Introduction
  • Dask Setup: Introduction
  • Dask Array: Introduction
  • Dask Bag: Introduction
  • Dask DataFrame: Introduction
  • Dask Delayed: Introduction
  • Dask Futures: Introduction
• dask-image: A Library for Distributed Image Processing (SciPy 2019)
• Better and Faster Hyper Parameter Optimization with Dask (SciPy 2019)
• Real Time Processing and Dask (AnacondaCon 2018)
• Scalable Machine Learning with Dask (AnacondaCon 2018)
• Adapting from Spark to Dask: what to expect (PyCon 2018)
• Parallelizing Pandas, NumPy, and Scikit Learn with Dask (PyMunich 2017)
• Dask A Pythonic Distributed Data Science Framework (PyCon 2017)
• Dask Parallel and Distributed Computing (SciPy 2016)