{"name":"py310-dask","portdir":"python/py-dask","version":"2025.9.1","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":true,"categories":["devel","python"],"maintainers":[{"name":"stromnov","github":"stromnov","ports_count":2891}],"variants":[],"dependencies":[{"type":"build","ports":["py310-setuptools","py310-wheel","py310-build","py310-installer","py310-versioneer","clang-18"]},{"type":"lib","ports":["py310-cloudpickle","python310","py310-partd","py310-fsspec","py310-click","py310-packaging","py310-importlib-metadata","py310-yaml","py310-toolz"]}],"depends_on":[{"type":"lib","ports":["py310-distributed"]},{"type":"run","ports":["py310-reproject"]}]}