Result for 06AB4256EC3D66394687DCE19E39452B41FD149C

Query result

Key Value
FileName./usr/lib/python3.9/site-packages/xarray/tests/__pycache__/test_backends_file_manager.cpython-39.opt-1.pyc
FileSize5587
MD52A9D515E017C3CFFFF68A5D953D106B3
SHA-106AB4256EC3D66394687DCE19E39452B41FD149C
SHA-2566695D36F666CA009C5F62DCB7D29A67DF7EEC977E9E6EBF8857526999EEB5F63
SSDEEP96:msQ2BdxZoRQ2RHNhnq1VAq1dq+71nEFpquBnqqgQ+Aewq4RtSbq5dzq+ujqqDCdX:ZndxZ8Q2RHNBqDAq1dq+71nEFpqonqqh
TLSHT1B2B198E7726B5D9AFE7DF2FD50DB0721911EC22B57C891025810B84B6F833D908E68C8
hashlookup:parent-total1
hashlookup:trust55

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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