{"name":"py-dask","portdir":"python/py-dask","version":"2025.9.1","license":"BSD","platforms":"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":2892}],"variants":[],"dependencies":[{"type":"build","ports":["clang-18"]},{"type":"lib","ports":["py313-dask"]}],"depends_on":[]}