Parallelizing Scientific Python with Dask | SciPy 2018 Tutorial | James Crist, Martin Durant

[@harryh2185]

Let's hope for an updated Tutorial in 2020 🙏

[@fee79]

Thank you for asking! We will be giving this Tutorial again at SciPy 2020. 😊

[@mystisification]

Any chance to have an overview of optimization where dask & numba are used together or would it collide in some way? thanks

[@kannansingaravelu]

I am getting a ValueError: Length mismatch: Expected axis has 15 elements, new values have 16 elements when I run df.compute() where df has 15 columns. It works for some datasets and not for some despite the format remaining the same. Any idea on how to sort this out?

[@gianlucastrada548]

why don't we do a complet project? why only nootebook? It is a mistake...

[@nivedhitha_ezhilarasan]

conda install python-graphviz will help us visualize. hope it is helpful.

[@ekbastu]

Very apt

[@matthewson8917]

conda install graphviz or conda install -c conda-forge graphviz in case you don't have graphviz installed

[@matthewson8917]

Thanks for the video! It helped me a lot.

[@atzenigor]

If you are on windows graphviz can be a problem. You can solve it with this line of code in your notebook. import os os.environ["PATH"] += os.pathsep + os.environ['CONDA_PREFIX'] + '\\Library\\bin\\graphviz' Maybe it would be helpful!

[@eliasbassani1426]

The link to the materials seems to be broken, can you provide a working one? Thanks for uploading this!

[@eliasbassani1426]

For anyone interested, you can find the materials at github.com/martindurant/dask-tutorial-scipy-2018

[@enthought]

The link has been updated! Thank you for letting us know about the issue.

[@eliasbassani1426]

@@enthought You are welcome! :) Thanks again for the awesome contents!

[@MrCraber]

Dask should be used by every python user

[@ninonazghaidze7687]