Result for 010655FC624EF1DEB6CE4FAD7874A1EFDB8D1A50

Query result

Key Value
FileName./usr/lib64/python3.8/site-packages/numba/runtime/__pycache__/nrtdynmod.cpython-38.opt-1.pyc
FileSize5831
MD5E275F56B5DBF7CE18EE6A845DCBAC329
SHA-1010655FC624EF1DEB6CE4FAD7874A1EFDB8D1A50
SHA-256150929A5AC6E6EB26F71B1FCFEDE65EFDC432B81ED6E4A671D2111B2C1CA654D
SSDEEP96:n9GDe4W/byRezS3G4qmRu1JJdugkdUPEoUJBjMIh9UOAR5I3QRwmzAmLCSnuUBpf:n9fbIqS3GpmRutcgmUTWBjJ9URR5BRF1
TLSHT1BFC1C758B803ABA5FD89F1FA900F10B8D651E27F030415127C4CA5DD9F276EA94EA7C9
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