{"name":"py36-dask","portdir":"python/py-dask","version":"2021.12.0","license":"BSD","platforms":"darwin","epoch":0,"replaced_by":null,"homepage":"https://github.com/dask/dask/","description":"Minimal task scheduling abstraction.","long_description":"Dask provides multi-core execution on larger-than-memory datasets using blocked algorithms and task scheduling. It maps high-level NumPy, Pandas, and list operations on large datasets on to many operations on small in-memory datasets. It then executes these graphs in parallel on a single machine. Dask lets us use traditional NumPy, Pandas, and list programming while operating on inconveniently large data in a small amount of space.","active":false,"categories":["devel","python"],"maintainers":[{"name":"stromnov","github":"stromnov","ports_count":2896}],"variants":[],"dependencies":[{"type":"build","ports":["clang-9.0","py36-setuptools"]},{"type":"lib","ports":["py36-fsspec","py36-packaging","python36","py36-toolz","py36-yaml","py36-partd","py36-cloudpickle"]}],"depends_on":[{"type":"lib","ports":["py36-pyfftw","py36-distributed"]}]}