Result for 066475E9445987B73BB15573F4DC2ADD27E8EF8C

Query result

Key Value
FileName./usr/lib/python3.9/site-packages/xarray/core/__pycache__/arithmetic.cpython-39.pyc
FileSize2679
MD5DA3CB817C519C29BA5798A2EB27EF71C
SHA-1066475E9445987B73BB15573F4DC2ADD27E8EF8C
SHA-256C56E9267EB966C027459EC8CDBEF1E1B0B2CCCB4004DDDF91B1457F707A372C4
SSDEEP48:QWThlV/wUvq6pAy08hzp2NBqKFvLhzPofejJSw62VvAK1h5gWDN4c:T/ayAy0Q3KFvBPofQdvL1vJ
TLSHT13051D62C504986FCF25BD0BCD0AB0156EE4742BA1B40138B7D53BF005D1A154E73A7A9
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
MD5D96107ED10E9FA051B6F22C852FF5FEF
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.fc34
PackageVersion0.17.0
SHA-121F00B9C11FE48CDFAF56940E8B1C165E5A04CC7
SHA-256F012CDBC21B445DF218451281316B64FCB894587D1A54D9E264894DDFBF8FD28