Result for 0006BEBA7782D075E52A5AD0A00339256BC1C0AC

Query result

Key Value
FileName./usr/share/doc/python-dask-doc/html/generated/dask.array.Array.conj.html
FileSize23097
MD5310F4AB2D3B3DC066FA758BFE3A289E4
SHA-10006BEBA7782D075E52A5AD0A00339256BC1C0AC
SHA-2561D059327CC1AB4F5D0657BD7EF6933A260BD0BCF69676B39507D70624D0FAE63
SSDEEP384:0pvxrFMQd55J0cGNCXbfWYfi4Pofefxf/bpdllc:1nNNuPJbpdllc
TLSHT190A2CE320889187B129352CC5E763B7CB5975A3FC21D2E5370BE2E294B52F61D62A31E
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