Result for 012B076D3FD08BD1DA862D684AEAABFF147C8CCD

Query result

Key Value
FileName./usr/lib/python3.10/site-packages/tables/tests/__pycache__/test_all.cpython-310.pyc
FileSize1420
MD5A945643C7FD8BADCC78E6547918C4C6B
SHA-1012B076D3FD08BD1DA862D684AEAABFF147C8CCD
SHA-2566A00EE0B7E5AB5999DADEB47F5A97F8477F89E37EDD179B20959AC86F8538DB6
SSDEEP24:KuRAtRHH5GN0s95zqz4XTFTWLlIAMgF0KqJnyJwzvgXVPzwoUvV8iEIVC5Z4Z:KuRAtRn5GN33xWRIAMZzY9ko0dC5S
TLSHT1D12186CC2A1BCEB3E065E7BAE92621117335E2B447489226624EDF454F8A1CD06E4B4D
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