Result for 1F7368D0F5D3A967A53CBF49D245DB8DE1D2EFA4

Query result

Key Value
FileName./usr/share/doc/python3-gdal/examples/validate_cloud_optimized_geotiff.py.gz
FileSize2983
MD50DF0630A3A8BA083D8A952E2FAB6054A
SHA-11F7368D0F5D3A967A53CBF49D245DB8DE1D2EFA4
SHA-2568846CB94990B9B2F0BB8672536A360685BDE7AE89E8147DBD4E729236825B06D
SSDEEP48:X3sELN0VyjuCkWXvA3IzgocgDhIK6GhDiSjP8HuUA1NyACDUhSRbA4At8ESe809W:HsWNrjDXvA3IzgR6hrP8OU2NhCDUARrn
TLSHT12B515C7320E2A06324B7CEB8F39049625A77E6622D95C680F0A1F1344E59D3889E5F6F
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
FileSize526972
MD5B4E9C1D74366C268B898C02D7B5BA1B2
PackageDescriptionPython 3 bindings to the Geospatial Data Abstraction Library GDAL is a translator library for raster geospatial data formats. As a library, it presents a single abstract data model to the calling application for all supported formats. The related OGR library (which lives within the GDAL source tree) provides a similar capability for simple features vector data. . GDAL supports 40+ popular data formats, including commonly used ones (GeoTIFF, JPEG, PNG and more) as well as the ones used in GIS and remote sensing software packages (ERDAS Imagine, ESRI Arc/Info, ENVI, PCI Geomatics). Also supported many remote sensing and scientific data distribution formats such as HDF, EOS FAST, NOAA L1B, NetCDF, FITS. . OGR library supports popular vector formats like ESRI Shapefile, TIGER data, S57, MapInfo File, DGN, GML and more. . This package contains Python 3 bindings for the GDAL/OGR library.
PackageMaintainerUbuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageNamepython3-gdal
PackageSectionpython
PackageVersion3.0.4+dfsg-1build3
SHA-1FC36DC0732717D32FCB3B3EC29A2E5FFD251DCEF
SHA-25674A087A9E98BEE4FD78B8837080776AC54F0848FECA5A4A9BBB50A8682D34731