Result for 010F229B1F0E36D6DDB3A34EB80B3BDE4B609B6E

Query result

Key Value
FileName./usr/lib/python3.10/site-packages/tables/__pycache__/filters.cpython-310.pyc
FileSize12127
MD5E57FEF4DCCC21DBD6861E20D9A64B553
SHA-1010F229B1F0E36D6DDB3A34EB80B3BDE4B609B6E
SHA-256D28C15F08555532448497D546C3B46021AAB73FFF76BC92D7A9C87825D7B352A
SSDEEP192:sEcum1cFz+hgznf2Y4X0cfj2fdDF2hgslcZVpH7Z6QrcGh0qY5xCFdP:s71mSknf1sfj2BoKslKpHTnh0qqxM
TLSHT10E42F7222A806733FD65F1B0FF7E8695533081BB63551222304D861A3F4353CCAE6ADD
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
MD594271992B0A49546B72F07AD0741194D
PackageArcharmv7hl
PackageDescriptionPyTables is a Python 3 package for managing hierarchical datasets designed to efficiently and easily cope with extremely large amounts of data. It is built on top of the HDF5 library and the NumPy package (numarray and Numeric are also supported). PyTables features an object-oriented interface and performance-critical extensions coded in C (generated using Pyrex) that make it a fast yet extremely easy-to-use tool for interactively processing and searching through very large amounts of data. PyTables also optimizes memory and disk resources so that data occupies much less space than with other solutions such as relational or object-oriented databases (especially when compression is used).
PackageMaintainerneoclust <neoclust>
PackageNamepython3-tables
PackageRelease1.mga9
PackageVersion3.7.0
SHA-1FC8B064172799D28DD12EF3C1BFE8EF0F35919F5
SHA-2563CBADBA3E551754A9F106E1F2E77F609CE4F42835E3D9D677CA6CC18027C49CB