Result for 00B0D6A970CFDEB313950037C799B45F4C53D04E

Query result

Key Value
FileName./usr/lib64/python3.8/site-packages/numba/cuda/tests/cudadrv/__pycache__/test_managed_alloc.cpython-38.opt-1.pyc
FileSize3935
MD51627572A37C879EDA2A98D1847686351
SHA-100B0D6A970CFDEB313950037C799B45F4C53D04E
SHA-25628469E2B1D59BC6D59CD1BABE6506883E7300D0ED671768CA45E55A28A9A7E70
SSDEEP96:OUQ9o7dEQwPa+zbmp2CFYOUluS1TXqDhl5LK38u20JY:OUQS9qhg2CFU0ITaDhlxK38u20JY
TLSHT1038122B47A4E4C05F863F3B7F8370228572183239AEA1D065A14A57F2F5A2D927E13CD
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