Result for 03BED01C62A4BF735B8816F53016A592427996AF

Query result

Key Value
FileName./usr/lib64/python2.7/site-packages/tables/tests/test_earray.pyo
FileSize89698
MD5155CC79A2162E16B16F37DB1A665318D
SHA-103BED01C62A4BF735B8816F53016A592427996AF
SHA-256978F2940E3E7B8DB391A20CFC4FC54C56AD7105426E808D1F34DB454E444D729
SSDEEP1536:9NK5aLJEK1rZJi5pEy4D4a0Imk0vQU0ZJ/V7e3Ure1VbVyt/NyuP/Ne+P/NuXy46:9NK5aLJEK1rZJi5pJ4D4a0ImXvQU0ZJt
TLSHT17593F281B3A39A9FC2D04671A2F03746DEB2F067A641676216FDD43929C4379C86E3C9
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
MD53C11C6B8E4BB93BB00C0D1AA2A6A3432
PackageArchx86_64
PackageDescriptionPyTables is a Python 2 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).
PackageMaintainerdaviddavid <daviddavid>
PackageNamepython2-tables
PackageRelease4.mga7
PackageVersion3.4.4
SHA-1FD9940156DFADCA2F868C50A2229C49F5CF20B34
SHA-2561C120086218CBFEB56B82DD14BB6E67B0242B34E5FC78A0D91FB2C06CFD5F06E