Result for 015B15BC52BE43BB7FD07E9F82B10303FB9EEE41

Query result

Key Value
FileName./usr/lib64/python3.8/site-packages/numba/tests/__pycache__/serialize_usecases.cpython-38.opt-1.pyc
FileSize3709
MD5481A60E75B38D581756248A24F015A10
SHA-1015B15BC52BE43BB7FD07E9F82B10303FB9EEE41
SHA-256EDB7CD624A5721191DAEAB0D889B2AB8A9E6D14784873E031D7FDE829A945FB1
SSDEEP48:mR9UurPaEaPS6hAL9q4d9g0wCbg9HM9Yt0sa6w+mO+pKf+svJhpDnl2qjZSqQG:M9hrhal47RguSt0simus7jVwqEqQG
TLSHT1FF71FFD05DC24E5BFAA1F3B401EB86113370D253335E929FBA0CA9BF1F456860969E49
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
MD55A90D3C00EC378B410B78D1FF0464097
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.
PackageMaintainerhttps://bugs.opensuse.org
PackageNamepython38-numba
PackageRelease1.1
PackageVersion0.54.1
SHA-1A0C3FD5C6CBAB490C4A32015EA2DF316566DCCCC
SHA-256E3B854BB85C41775F7F33961743B07BCC261DA17D1B5EC811A6907A1C0BBDE04
Key Value
MD508EF5CE34C3A1FB1A24EE647B3471425
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.
PackageNamepython38-numba
PackageRelease54.3
PackageVersion0.55.0
SHA-19DE1E589BA0989870F006F83C3108F7EB870CFAB
SHA-2567D83943CA45A8592B34F38576DC2F6A4E8F9B919EBA71F8661593E9C969B8D6E
Key Value
MD54389388F8F16A2ED893C64CF0A9F9E7B
PackageArchs390x
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.
PackageNamepython38-numba
PackageRelease51.27
PackageVersion0.53.0
SHA-1606EFE2580C6310573F9A60717B59D306C17F467
SHA-25675F8D31F4D17AC99B88215F53A3BDBD39B6C74E650B79ACE1FF5B71DFBF61FE3