Result for 030A428D11C577F263E954BDB0FF2D74CD3A9930

Query result

Key Value
FileName./usr/lib/python3.9/site-packages/xarray/tests/__pycache__/test_nputils.cpython-39.opt-1.pyc
FileSize2021
MD55D19EAD6D2DDCA2B53EA458C0AE26E49
SHA-1030A428D11C577F263E954BDB0FF2D74CD3A9930
SHA-256D2A61F285E2A80420E9F24C98ADC7007793B02681C5B93D825056C2E90B415D7
SSDEEP48:QfrUG6JTyPoKe0ShC6ZS1EowtwXgIylqgK6RNQN5:rG22TGs6Zt+Yq76R8
TLSHT1FF41208C74071EAFF618F1B8401F17313668D2D97F29E146F7085A3A8D662460F14D8D
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
MD5604395DDDFE74D7B8686B995AE664507
PackageArchnoarch
PackageDescriptionXarray (formerly xray) is an open source project and Python package that makes working with labelled multi-dimensional arrays simple, efficient, and fun! Xarray introduces labels in the form of dimensions, coordinates and attributes on top of raw NumPy-like arrays, which allows for a more intuitive, more concise, and less error-prone developer experience. The package includes a large and growing library of domain-agnostic functions for advanced analytics and visualization with these data structures. Xarray was inspired by and borrows heavily from pandas, the popular data analysis package focused on labelled tabular data. It is particularly tailored to working with netCDF files, which were the source of xarray's data model, and integrates tightly with dask for parallel computing.
PackageMaintainerFedora Project
PackageNamepython3-xarray
PackageRelease1.fc33
PackageVersion0.16.1
SHA-145DFB3D025A03D0F07BAA0B0B2BD1732F9161B72
SHA-2566F5C919419803326689417C03B49F01015DD59640A97EE58F793D87961055AC1