Result for 96AAE1E64E425E67B7F296476DE307D339D26575

Query result

Key Value
FileName./usr/lib/python2.7/dist-packages/tables/tableextension.s390x-linux-gnu_d.so
FileSize425704
MD5BC6AE8882ABE3931A4C0D29601572EF0
SHA-196AAE1E64E425E67B7F296476DE307D339D26575
SHA-2565B4F80D2DB618D1E4430E0FF865D9059942AEDB8281EB6057B96ADE671F0159E
SSDEEP6144:erdmh7+SrrcRL8msgtTz0phE+yZhtg1NP7FVKH2r9swPJAnkScHn:eaKLhtShE+ytgDPxrew2
TLSHT18594648691109391C5B87633DEDF67B1E22720343BC9A59C8BDECF661CB1B96831522F
hashlookup:parent-total1
hashlookup:trust55

Network graph view

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
FileSize463836
MD5254C3E4D0A984C1B84E02B395810D8CF
PackageDescriptionhierarchical database for Python based on HDF5 (debug extension) PyTables is a hierarchical database package designed to efficiently manage very large amounts of data. PyTables is built on top of the HDF5 library and the NumPy package. It features an object-oriented interface that, combined with natural naming and C-code generated from Pyrex sources, makes it a fast, yet extremely easy to use tool for interactively save and retrieve large amounts of data. . - Compound types (records) can be used entirely from Python (i.e. it is not necessary to use C for taking advantage of them). - The tables are both enlargeable and compressible. - I/O is buffered, so you can get very fast I/O, specially with large tables. - Very easy to select data through the use of iterators over the rows in tables. Extended slicing is supported as well. - It supports the complete set of NumPy, Numeric and numarray objects. . This package contains the extension built for the Python 2 debug interpreter.
PackageMaintainerDebian Science Maintainers <debian-science-maintainers@lists.alioth.debian.org>
PackageNamepython-tables-dbg
PackageSectiondebug
PackageVersion3.3.0-5
SHA-1227532B16AC3EA5D1FC26712DC48583C936FAF47
SHA-25606453DC74ADBBE4039B5EACE2E92B1A825A74651D176CF9C1603AEC2DA81D0DE