Result for 01CEC36EFC5A7D66A9D1724A4FFA67AB9937A151

Query result

Key Value
FileName./usr/share/doc/python-dask-doc/html/_sources/generated/dask.array.core.PerformanceWarning.rst.txt
FileSize147
MD5F6AA084D4D3CE0E810ED87420706CDA1
SHA-101CEC36EFC5A7D66A9D1724A4FFA67AB9937A151
SHA-256B9D372E12DF5AA6B9B3976AEB25DE46BC65D7DA13C7C7B0B329F96241006060B
SSDEEP3:EEFEXxde1QKYay0vYYY1Y6BW+XxdiCEKsqQfHAay0n:r+vqQMyfrtvpENHpy0
TLSHT18EC01200F324442761A901D6027460CE5C3B2BE8B4443547CCBF9E5C004E33081FFF28
hashlookup:parent-total3
hashlookup:trust65

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Parents (Total: 3)

The searched file hash is included in 3 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
FileSize3964340
MD5870AF1465DB0E84ED8B879B3411947CF
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-2
SHA-1827B35900A1D0A2736A0ACDABE77B5FCEC4ABAB2
SHA-2562CDF1DB821BDF373D8AF9D4C6E962696974AF9893708D9CBC31DB5FAA8DF6370
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
Key Value
FileSize9678540
MD551916ABB5151B40836CC495B2297C5F7
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
PackageVersion2022.12.1+dfsg-2
SHA-1CE9AD860D74774AA01A349FEF116DB92C09698DA
SHA-25681FC4CC36BFC939ED9FF28C2423D921909CFBEF1AF69055131B79AB69A33B615