Result for 027AC52C2B8C5C8163FDCFD38F4AD7BC743EED0D

Query result

Key Value
FileName./usr/lib/python3.9/site-packages/xarray/core/__pycache__/missing.cpython-39.pyc
FileSize21036
MD5C9757229BC75A794DE7414C20D4ED90E
SHA-1027AC52C2B8C5C8163FDCFD38F4AD7BC743EED0D
SHA-2567D0ACF74FE6090A5C8F5E93014A4CE91A5E51E84BE5B2DA2946C4C500F6F0251
SSDEEP384:Zj7VxySf9mcmiXR6AcumZdP8/HgXKoDVaEDXG7gw8b8PqYbW3:Z7jRMcrh6lZFVbni7J8gI
TLSHT164922AC4E4060D56FCBDF3F66D0D4646AB2080AB6382956BB44DA0762FC7184DBBD7B8
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