Result for 02FEEDAA7CFDEEAC90DECCDAA77C9CA583A39B25

Query result

Key Value
FileName./usr/lib/python3.9/site-packages/xarray/core/__pycache__/merge.cpython-39.pyc
FileSize26212
MD51C6D11B78D233135D149346210D5D84E
SHA-102FEEDAA7CFDEEAC90DECCDAA77C9CA583A39B25
SHA-256212013FC04678A1AE4C2AFD5C9CC0967E987F7984A3ACADB55D24475357FEA80
SSDEEP384:GiiwN7wNgKB05b3ka4OrVD0DP6WwFzzbWJg42gYcWixbbeuOSz+CU:GBwSNNiV3kafIP6WwJkbeuM
TLSHT15FC21A4225806E3AF9D6F0FA421E5449EF95929B33497D10B0CEC6381F4656CE13DAEF
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