Result for 0028CA476263822F9953AA56045D239B7F18CBAC

Query result

Key Value
FileName./usr/lib/python3.9/site-packages/numba/tests/__pycache__/test_iteration.cpython-39.pyc
FileSize9729
MD54AFC21D2B434511001169230C400513D
SHA-10028CA476263822F9953AA56045D239B7F18CBAC
SHA-2564A217DD02EAB24AFA9326F7B0C30781022C161BBF5FBA7AFED9EA2503E31F10D
SSDEEP96:TYin/P+FAd3y7gkIPKlHsHUI9dH9hl+9/CV9X7A9MlWWLoHhD56bV922FV9wdnyl:TYukAdGd8TbQ56S2FbWxaciRORA
TLSHT10B123FEC9E4F995AFE26F1B9D03202217636C36253958DA340156EAF9D4E3C02FE64E4
hashlookup:parent-total3
hashlookup:trust65

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Parents (Total: 3)

The searched file hash is included in 3 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
MD571D66A3498F552992E6CD538925A2BAA
PackageArcharmv7hl
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
PackageRelease54.2
PackageVersion0.55.0
SHA-147AC50676A3920262B3D67238A2C84D9F153C9E4
SHA-256DF6781B2E29D9D300FE3E09E0F449980B0235DCD1A2BE147D0064F93F0271AA6
Key Value
MD5F153423B8725959B6601D2C7B3469B30
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.
PackageMaintainerhttps://bugs.opensuse.org
PackageNamepython39-numba
PackageRelease1.1
PackageVersion0.54.1
SHA-1A007C017DC97F5610EB470F1014B2A9529AA0ED7
SHA-256708D9C76533CE88D2767AE84B0003F2499D54F28842009266CDE226B6EB34459
Key Value
MD585B3AF7742FB14EE3CAB412F7DA54F0E
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.
PackageNamepython39-numba
PackageRelease54.3
PackageVersion0.55.0
SHA-1DB7B2AA59BD4F7F1B597D1375994E26C17E839D1
SHA-256AC006DB424B7DBCCE939FAA47C428201C398CF2264D0E4BDE6A0C56FA6EFEF89