{"name":"py311-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":2896}],"variants":[],"dependencies":[{"type":"build","ports":["py311-build","py311-installer","py311-setuptools","py311-wheel","py311-versioneer","clang-18"]},{"type":"lib","ports":["py311-toolz","python311","py311-partd","py311-cloudpickle","py311-packaging","py311-fsspec","py311-importlib-metadata","py311-click","py311-yaml"]}],"depends_on":[{"type":"lib","ports":["py311-distributed"]},{"type":"run","ports":["py311-reproject"]}]}