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Dask is a flexible library for parallel computing in Python. Dask is composed of two parts: - Dynamic task scheduling optimized for computation. This is similar to Airflow, Luigi, Celery, or Make, but optimized for interactive computational workloads. - "Big Data" collections like parallel arrays, dataframes, and lists that extend common interfaces like NumPy, Pandas, or Python iterators to larger-than-memory or distributed environments. These parallel collections run on top of dynamic task schedulers. WWW: https://dask.org/ WWW: https://github.com/dask/dask
13 lines
575 B
Plaintext
13 lines
575 B
Plaintext
Dask is a flexible library for parallel computing in Python.
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Dask is composed of two parts:
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- Dynamic task scheduling optimized for computation. This is similar to Airflow,
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Luigi, Celery, or Make, but optimized for interactive computational workloads.
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- "Big Data" collections like parallel arrays, dataframes, and lists that extend
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common interfaces like NumPy, Pandas, or Python iterators to
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larger-than-memory or distributed environments. These parallel collections run
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on top of dynamic task schedulers.
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WWW: https://dask.org/
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WWW: https://github.com/dask/dask
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