Result for 01378DAA14DEE14AF295E6AAF2E888B708DD914B

Query result

Key Value
FileName./usr/lib64/python3.9/site-packages/numba/cuda/__pycache__/api.cpython-39.opt-1.pyc
FileSize15172
MD550CCEF200F5FB266D93494270E1E00B8
SHA-101378DAA14DEE14AF295E6AAF2E888B708DD914B
SHA-2563576C16FE720F937AB00B3A70DD5ECE4145C0C2E4B103FFB6EA89E3CC6F5A45F
SSDEEP384:C9huGpbMwlREpdQsf+2LVF3WC1BQ0FraToTu2p9NB3EdFp6:GHMwlR2Qsf+2LVF3WC1SOraToTLpEdb6
TLSHT1B3623B41DE1AAA79F467F8F9483C4C2447A3C23B77188041744D986E0FD66EAAAF13DD
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
MD54DD5EB932768829652572CC647EF0BF7
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.
PackageNamepython39-numba
PackageRelease54.3
PackageVersion0.55.0
SHA-1FF47E3AC66EF868467ACBFFE1A32A777F506589A
SHA-256592BD62CD26A0AD1B9A3A3F844378A23E9B7784C41C02282A52396D578A69AAB