Result for FA8B45A987AC06501D19C2CE4B4786FB35EFF33C

Query result

Key Value
FileName./usr/lib/python3.8/site-packages/__pycache__/lazyarray.cpython-38.opt-1.pyc
FileSize17698
MD5A11472898BC0E4EB0D6BB7E5CE82E9DA
SHA-1FA8B45A987AC06501D19C2CE4B4786FB35EFF33C
SHA-256E709F804C8C975D2D571870F212F10A4913D357045DB7B8354901F5D127283B7
SSDEEP384:fdM7FzMuOqQ89ljQ0VfFszHC+tK2gJj+2joD:fdM7FzMuOq99lEesziV2gJy2sD
TLSHT10082F9D556800F7EFD16F7FEC04A1A50AA60A177138E9253F00F89AA2F4D9E81A719DC
hashlookup:parent-total1
hashlookup:trust55

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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
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