Result for 010806F2F2F9236D4F72711277AF19426C6321C6

Query result

Key Value
FileName./usr/lib64/python3.8/site-packages/numba/runtime/__pycache__/nrt.cpython-38.opt-1.pyc
FileSize4160
MD5B520797486C258553E8E49EFEA612B84
SHA-1010806F2F2F9236D4F72711277AF19426C6321C6
SHA-2561D842DA05BD703B56A08D936F8ACF317735ACDA2B6D9C839423D81421AF27B28
SSDEEP96:wYSe4DjLuKr8nSKi/x1fl8Nh/BLLuT4l7UQCxBu:MiKr8n0/xRa/BLLuT4xqBu
TLSHT1A681B7893A46AF5AF8D5F375A43A22B88331C17B8B6CF0057F0E410F2F4529C05A8789
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
MD5B764D08CFAEE3AF4221DF7215859120B
PackageArchx86_64
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-19EE3AC165B646510E966FBAF13E4F1739D692098
SHA-256D1B9933DC5C1E5226EECEEAE67919520C41E0CB57825907771AF1433D9450C71