Result for 3D227B375A8CE100084DDB7B273D7F978219706C

Query result

Key Value
FileName./usr/lib/python3.8/site-packages/xarray/__init__.py
FileSize2357
MD553E89EB6A3746476DBEBD9C7B894D32E
SHA-13D227B375A8CE100084DDB7B273D7F978219706C
SHA-25602B63C749EFF4233DB2D569DE7E5D4D522195C2D492FAF0B81AAED1543D0A0B3
SSDEEP48:rThWDf5aUy9M67/a/1RsWk0HtIEMvuxCiLzb6h/7Q/1eCzQoCyW:rThIaUy9M67CtxMvuZLzGhkFzhCyW
TLSHT11141CFADE13ABE7906DA919804D946155732B3331F403416738683AE1FDE50FE5B709F
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
MD5D68FF1A377928F17C9DA6B0FB037A2A0
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.fc32
PackageVersion0.15.1
SHA-18028092FB3FB86551114838ED07B6FCE80628EFA
SHA-25610C0C632BCDB558AE8954C8969691C6F294F8E26E02F0AF93F6EDB6D2ABB74A6