Result for 0517B3F0ED52A4D2C638D9FCBC9053E12963F2FE

Query result

Key Value
FileName./usr/lib64/python3.10/site-packages/tables/indexesextension.cpython-310-x86_64-linux-gnu.so
FileSize165664
MD5626C8256B61EEFB7BFE38D67C1C8D8FD
SHA-10517B3F0ED52A4D2C638D9FCBC9053E12963F2FE
SHA-25660C363C5B0729D8FEFC70220634976815736770FB8A3F1BBD0CD6E5F94C77BFC
SSDEEP1536:qlWq7xhm6vqlYsjJSaAwjuozE/dCte2xjp86LYD9j2SZipx03iI/wTHDuHo:ql1ftGjg/dj4jO6LYD9jW303aDuH
TLSHT1D4F35D1BA0B114FDC1F5C878CAA746A27D767850832426FB24C4E9341F92F705B6EBE9
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
MD588BA903D237A0A6D4A470054F2D4CB96
PackageArchx86_64
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).
PackageMaintainerumeabot <umeabot>
PackageNamepython3-tables
PackageRelease4.mga9
PackageVersion3.6.1
SHA-16E701724A844AEF8A80D93654170AC231BE253AC
SHA-2566D7899904829BB31ED9D25B3F4F1F1684DB10EAB5963F43CC9722C9E33FB7C18