Result for 00070A0226F340A3D7237D9FCB33873DAE0BEADC

Query result

Key Value
FileName./usr/share/doc/python-dask-doc/html/generated/dask.bag.Bag.html
FileSize38250
MD55A9BFE96DB35CBA0716BEBAC81EBB74F
SHA-100070A0226F340A3D7237D9FCB33873DAE0BEADC
SHA-256C3E9CFC864B3AB92FB8566D09F14E36B1DB9880B434683A9543A54337BE7029F
SSDEEP768:znNNHbotQsWomFthTt4QsWgKqn5p/xTkBgYwc:znDstQsWomnhTt4QsWgKqn5p/xTkBgYb
TLSHT15F03EF6244F6143703E351C966BA3B3970E7152ED15B0821F2FD33A98BA9F61B50BB1E
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