Result for 0046D8E0456FE2FBB2F78D30A83CA1796B6886D4

Query result

Key Value
FileName./usr/lib64/python3.8/site-packages/numba/tests/__pycache__/test_return_values.cpython-38.pyc
FileSize2497
MD5F6B93DD2F2C1C6CDC034275E0D075611
SHA-10046D8E0456FE2FBB2F78D30A83CA1796B6886D4
SHA-2566382FF20E6F08F637F0E826ABE90FBAF595F8D74C2102CD5911DBF226423C251
SSDEEP48:pTh3rM4jge78XsndJsMq3SRhTsq3u5E4yqqwcR3UCMC:pF7jguIsndzq38psq3uzyq94MC
TLSHT1DA51E1D291D348A9FFA8F1FD942DC2119761D377438962122D4C12AB2F281881BE0E29
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