Result for 043BE8C2AF851506E32B3B981C4D7EACD84E5333

Query result

Key Value
FileName./usr/lib/python3.9/site-packages/xarray/tests/__pycache__/test_merge.cpython-39.opt-1.pyc
FileSize12438
MD503D250B1C4E9BB22C002CE0EB745D100
SHA-1043BE8C2AF851506E32B3B981C4D7EACD84E5333
SHA-256FB3E9E54625A2D984A373E4F67A8B2C50CC8E3CB72B15526E4EF83B285C37AF0
SSDEEP384:QWGpc8WWMbUPoZMiZrloHPwE23Zt+JQirr:gp6W8UgrZ5oHPlSt+JQiv
TLSHT18F42A5B634575D1AFF02FA7CC0BA233D2A26E31D638595632D04F87A5D842E918F29DC
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