Result for 00A1FD3DBD62FAA33B5E204576C540A1CD0EBE3C

Query result

Key Value
FileName./usr/lib64/python3.8/site-packages/numba/core/__pycache__/postproc.cpython-38.pyc
FileSize7298
MD51F8BB39F0D81D545716210688643EE7A
SHA-100A1FD3DBD62FAA33B5E204576C540A1CD0EBE3C
SHA-25632365F25B0469E59696FA630060FFAC3C787CC1036A097F44504B6DBF22E983B
SSDEEP96:lEp83xbzrvZEdc137Q3m7QUFGm3TuON0c+s5AmjzUfb6RWn02bwqvZxLNGzJEFeP:lJ3NTVQW7p+TPmXo6sn0uFK1Fco
TLSHT1F8E1D99947A1BE7BFCE1F3BA945E01425A3483775369E525788C87CF8F0B2A10D707A8
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
MD54389388F8F16A2ED893C64CF0A9F9E7B
PackageArchs390x
PackageDescriptionNumba is a NumPy-aware optimizing compiler for Python. It uses the LLVM compiler infrastructure to compile Python syntax to machine code. It is aware of NumPy arrays as typed memory regions and so can speed-up code using NumPy arrays. Other, less well-typed code will be translated to Python C-API calls, effectively removing the "interpreter", but not removing the dynamic indirection. Numba is also not a tracing JIT. It *compiles* your code before it gets run, either using run-time type information or type information you provide in the decorator. Numba is a mechanism for producing machine code from Python syntax and typed data structures such as those that exist in NumPy.
PackageNamepython38-numba
PackageRelease51.27
PackageVersion0.53.0
SHA-1606EFE2580C6310573F9A60717B59D306C17F467
SHA-25675F8D31F4D17AC99B88215F53A3BDBD39B6C74E650B79ACE1FF5B71DFBF61FE3