Result for CB2AF31C9EEA758F0DB66257C466849D2C8274AD

Query result

Key Value
FileName./usr/lib/python3.6/site-packages/lazyarray-0.3.2-py3.6.egg-info
FileSize2201
MD5123533EDC99992725EC849AC844AF0B7
SHA-1CB2AF31C9EEA758F0DB66257C466849D2C8274AD
SHA-256CD1AD6DD86961327046D736AEEE4ED3377E7E78EFE7EED5EC5DB1285BF2228C6
SSDEEP48:DhZr64/mFbKCxZK68ykQI/s+OpMn0c+GV0xpi0Vjk4BQI/jEu:DhZWomFmQI6O/aek3keQI/jEu
TLSHT14741948723D17BFE1F930587166852C4E59161A3B88A148838AFAC0D6F31FB0863F11C
hashlookup:parent-total4
hashlookup:trust70

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Parents (Total: 4)

The searched file hash is included in 4 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
MD5192CCD1298D6F33AEED609F7C1CD3219
PackageArchnoarch
PackageDescriptionlazyarray is a Python package that provides a lazily-evaluated numerical array class, larray, based on and compatible with NumPy arrays. Lazy evaluation means that any operations on the array (potentially including array construction) are not performed immediately, but are delayed until evaluation is specifically requested. Evaluation of only parts of the array is also possible. Use of an larray`can potentially save considerable computation time and memory in cases where: * arrays are used conditionally (i.e. there are cases in which the array is never used) * only parts of an array are used (for example in distributed computation, in which each MPI node operates on a subset of the elements of the array)
PackageMaintainerhttps://bugs.opensuse.org
PackageNamepython2-lazyarray
PackageReleaselp151.1.1
PackageVersion0.3.2
SHA-1380892B2272600420C690FC32FE7C703479991C6
SHA-2568299D3914B95D7776699212871B965DF20D53CB80A0F96BCCEC9A7E7A6208D6A
Key Value
MD5ED032EFF2A70EAE35B94B835DE503F6B
PackageArchnoarch
PackageDescription lazyarray is a Python package that provides a lazily-evaluated numerical array class, ``larray``, based on and compatible with NumPy arrays. Lazy evaluation means that any operations on the array (potentially including array construction) are not performed immediately, but are delayed until evaluation is specifically requested. Evaluation of only parts of the array is also possible. Use of an ``larray`` can potentially save considerable computation time and memory in cases where: * arrays are used conditionally (i.e. there are cases in which the array is never used) * only parts of an array are used (for example in distributed computation, in which each MPI node operates on a subset of the elements of the array) Documentation: http://lazyarray.readthedocs.org
PackageMaintainerFedora Project
PackageNamepython3-lazyarray
PackageRelease8.fc33
PackageVersion0.3.2
SHA-17C7D722BE9E67A5238C92EACABA12E8C0C0C6B7E
SHA-25684159442335CC3B75B2EB3A0ABB44E0AD399EF507E894095F61A1E0B463AB0CD
Key Value
MD599C0278C695ECE7B4BBB103E072BD691
PackageArchnoarch
PackageDescriptionlazyarray is a Python package that provides a lazily-evaluated numerical array class, larray, based on and compatible with NumPy arrays. Lazy evaluation means that any operations on the array (potentially including array construction) are not performed immediately, but are delayed until evaluation is specifically requested. Evaluation of only parts of the array is also possible. Use of an larray`can potentially save considerable computation time and memory in cases where: * arrays are used conditionally (i.e. there are cases in which the array is never used) * only parts of an array are used (for example in distributed computation, in which each MPI node operates on a subset of the elements of the array)
PackageMaintainerhttps://bugs.opensuse.org
PackageNamepython3-lazyarray
PackageReleaselp151.1.1
PackageVersion0.3.2
SHA-1753A8D8667BC9787C0434C9245A9A0D52D71AF17
SHA-256A17F93EE5EB5A004ABC3455797EDEF68FDBABC0515E03A74B3568E8644D9A8AA
Key Value
MD5EE3FFEAB29D53665A7958D1798DC35F7
PackageArchnoarch
PackageDescription lazyarray is a Python package that provides a lazily-evaluated numerical array class, ``larray``, based on and compatible with NumPy arrays. Lazy evaluation means that any operations on the array (potentially including array construction) are not performed immediately, but are delayed until evaluation is specifically requested. Evaluation of only parts of the array is also possible. Use of an ``larray`` can potentially save considerable computation time and memory in cases where: * arrays are used conditionally (i.e. there are cases in which the array is never used) * only parts of an array are used (for example in distributed computation, in which each MPI node operates on a subset of the elements of the array) Documentation: http://lazyarray.readthedocs.org
PackageMaintainerFedora Project
PackageNamepython3-lazyarray
PackageRelease6.fc32
PackageVersion0.3.2
SHA-195D71AD34017904433F69083ADFA974D50CF0299
SHA-256A43B25AC7BFFC5E4B3AE07F780A6BBF5B2B15417A87C1D42B8CFD714F733CE7A