Result for 0109CC2F1D3C02E72F18137EA2ACCC0A6232BD28

Query result

Key Value
FileName./usr/share/doc/python-dask-doc/html/_sources/generated/dask.array.stats.ttest_1samp.rst.txt
FileSize130
MD5AAEB9F30E752F4D7FFEC16D83E6F2F89
SHA-10109CC2F1D3C02E72F18137EA2ACCC0A6232BD28
SHA-256FF4806789CA75780E41B5ABAE5845262C5714A756044EA0EB843A3B0D0EEBD70
SSDEEP3:EEFEXxWERQBh6BW+XxWERoTCEKKbKjmW6ZV:r+jwOjoeEpbwmWsV
TLSHT14EC01216723B252748EF1540433130EC4D667458780E52A208378F8443AC77C84FFE8C
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