Result for 024E10318A73F7C7D3C15CFA4B9AF412EB36B8CC

Query result

Key Value
FileName./usr/share/doc/python-dask-doc/html/generated/dask.array.conj.html
FileSize45772
MD54879C80EFC5CD5FEB8FFA3CD8598E79E
SHA-1024E10318A73F7C7D3C15CFA4B9AF412EB36B8CC
SHA-25633618CF798A3B14A39FCB75C0E144A0833989DBC60C6D4B409303DD61BD098D7
SSDEEP384:0MacZFTQd55J0cGNCXbfWYfDM6vMy4Pofefxfvb7dnwtIoRZZyc:hnNNEM62PBb7dnwtpZZyc
TLSHT154236D32088E147B02A652C81E7A3B6C75976F3FC25D2A1374BF3E250756F61D62A31E
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