Result for 00194819D9B68F4C0CA8967F91B16E4DE15CA086

Query result

Key Value
FileName./usr/lib/python3.8/site-packages/numba/tests/__pycache__/test_remove_dead.cpython-38.opt-1.pyc
FileSize11620
MD5F3DB54DC4B7FFF2CFE8F819E085B08CE
SHA-100194819D9B68F4C0CA8967F91B16E4DE15CA086
SHA-25674ED01ED385C46EA43C40EC7CF8FA20817EEA2A80292EBE23DF49EEEBDDD20F8
SSDEEP192:v6b9Vq72+pxryNj/se//CGN6t7y+B5XjRwlnGkjuv26RY3D:v6b9Vq7TrreXCGNy2+vje/nWY3D
TLSHT18E32B9CD80671D4FFEB2F2BE64DE41015D72D23347A741272593A26B1F08BD929B038A
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
MD5EA13BEB974A81C11071BEA94F10826E2
PackageArchi586
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.
PackageNamepython3-numba
PackageRelease3.3
PackageVersion0.48.0
SHA-165F50BE666F241E42BC26F21CA19FDA3478A9465
SHA-2563F26FD34FD71B7894A69C0455E85F6DC5DCD14C7787577277A24D0F58EA2172C