Result for 0130EF3A3CA1E9ED452F74A8FF97751462FD77B3

Query result

Key Value
FileName./usr/lib/python3.8/site-packages/numba/cuda/__pycache__/codegen.cpython-38.pyc
FileSize2970
MD59009FC81B09A98A7BDAA2B272546266E
SHA-10130EF3A3CA1E9ED452F74A8FF97751462FD77B3
SHA-256BA86D3618B2CF4C4BA6A0A7FF2EE30BCBB5BB336DFE2800C0F12F293FDF7E640
SSDEEP48:zVkryO0DNWyRycSWuFSE/kfHyudQlaLm+7VD3cXrM22KrSONXVp97qzmhGN:GJ05YWeSZSuels7VD3c7M22KrVFp97cB
TLSHT1785101C08B4454DBFCADF2F5F0F812085BF047BE5B4A78861A2885AF0D4A2C16DB928C
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