Result for 01DA3630B21FD41A45113B266B2FEA07B38D2922

Query result

Key Value
FileName./usr/share/doc/python-dask-doc/html/generated/dask.array.linalg.lu.html
FileSize19606
MD536F8B2B8FAF084A94A7BFE8684D29AAC
SHA-101DA3630B21FD41A45113B266B2FEA07B38D2922
SHA-2566BDB5FB814265DD7DF89B400A1F680109764916803FAB5FE2C0AE8732FCB02EB
SSDEEP384:0yWkpFDQd55J0cGNCXbfWYfNwPofefxf3bKAxMwo1sc:nnNNDPpbKAxMwksc
TLSHT1A692FE3308C918BB125342CC5E6A37387597963FC65E2D12B1FD2A194B92F61EA1F31E
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