{"name":"py39-dask","portdir":"python/py-dask","version":"2024.8.0","license":"BSD","platforms":"{darwin any}","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":["py39-setuptools","py39-wheel","py39-build","py39-installer","py39-versioneer","clang-18"]},{"type":"lib","ports":["py39-toolz","python39","py39-partd","py39-yaml","py39-click","py39-cloudpickle","py39-fsspec","py39-importlib-metadata","py39-packaging"]}],"depends_on":[{"type":"lib","ports":["py39-distributed"]},{"type":"run","ports":["py39-reproject"]},{"type":"test","ports":["py39-sparse"]}]}