Result for 0136B6E3B263B9FC62D18D81EBA4254320B12F50

Query result

Key Value
FileName./usr/share/doc/python-dask-doc/html/generated/dask.dataframe.DataFrame.bfill.html
FileSize35411
MD5C2B7CB5982D5B9CEB417C640B8D29BD1
SHA-10136B6E3B263B9FC62D18D81EBA4254320B12F50
SHA-256531C3AAD87AB00409A76C6753DCFC0A8C5FEB93C5A0312163E944CF28DDB9E24
SSDEEP384:UKssZFrQd55J0cGNCXbfWYfJP8zQBfefxfHbt0xyFkyFIc:xnNNwPMfbt0xyFkyFIc
TLSHT133F2692F2889063E039B968C9F2D7B1CA047773EED994A5574B8725D2772FB0B10932D
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
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