Result for 0021484429771B6D992975A757C1D203B100BD08

Query result

Key Value
FileName./usr/share/doc/python-dask-doc/html/generated/dask.array.stats.moment.html
FileSize24106
MD528F9A5857770B4C3F8AE447063E330BE
SHA-10021484429771B6D992975A757C1D203B100BD08
SHA-2566C0441087614A6879B5D6B401ECE086114C992D6F701BDA61BF44F790C932915
SSDEEP384:0hhpbFsQd55J0cGNCXbfWYfN+8Pofefxf3bk3xnyQKyL/ySbejKRHvSeAc:NnNNV8Pxbk3xnyQKyL/ySb3PFAc
TLSHT171B2413258DA183B02A742C81E6A373C35D3953FC65E1D12B1FD26698B96F60B90F71E
hashlookup:parent-total1
hashlookup:trust55

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Parents (Total: 1)

The searched file hash is included in 1 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
FileSize3954064
MD567966D93F75F40AC0C112212E38995D3
PackageDescriptionMinimal task scheduling abstraction documentation Dask is a flexible parallel computing library for analytics, containing two components. . 1. Dynamic task scheduling optimized for computation. This is similar to Airflow, Luigi, Celery, or Make, but optimized for interactive computational workloads. 2. "Big Data" collections like parallel arrays, dataframes, and lists that extend common interfaces like NumPy, Pandas, or Python iterators to larger-than-memory or distributed environments. These parallel collections run on top of the dynamic task schedulers. . This contains the documentation
PackageMaintainerDebian Python Team <team+python@tracker.debian.org>
PackageNamepython-dask-doc
PackageSectiondoc
PackageVersion2021.09.1+dfsg-1
SHA-19C38AE7F2AEEBDC309F97B637B6C2EA30EA47A27
SHA-256A39722FADE2BA7B26F36745B88713368BBC45E285D2292E132153A106A7EE4BB