Make it easier with dask

As people have worked with writing parallel Python code over time, the painful parts have been identified and people have written packages to try and make these a bit more comfortable to work with. One of these packages that has been gaining in popularity is dask. The real power of dask is its flexibility. It can use many different parallelisation backends, and it also gives methods and objects that build on those used for scientific computations. For example, these new objects can mimic numpy arrays, or pandas data frames. Because of all of this additional functionality, you can select what you want support for when you install dask. For example, if you want everything, you can install it with this command: The back end parallelisation method used by dask is…

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The Python Book (Digital) - 1 Issue, The Python Book 4th Edition

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