Result for 0148FD97EF5605930D7BCE634CEF739576765DA3

Query result

Key Value
FileName./usr/lib/python3.8/site-packages/numba/tests/__pycache__/test_fancy_indexing.cpython-38.pyc
FileSize7805
MD5724D8F9F34751540179381D20F7C7680
SHA-10148FD97EF5605930D7BCE634CEF739576765DA3
SHA-256867EAADEFD0230E07A781C09267432DF4F27B67E2AB45D19EE2636A290A9F3DA
SSDEEP96:UtJVvwnFUsHsfAYklubOMbjTyPJOOUlvnwN41C8El6sSWQo9Wy0Ixhyg4FnGn7A1:UROLYvbIley1xhygtn7YFiR35c
TLSHT1D6F1A5EA6D02AD7FFC54F2B8002F07469138972ED748D6136418A26F6FF92850DF9768
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
MD55D2E84100ECF4FB9E2AE48FB17450A4C
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.
PackageNamepython38-numba
PackageRelease54.3
PackageVersion0.55.0
SHA-1C7452AD002F685D37EF92E82E49758BDEC0D783A
SHA-2569D07AF4742C09184FD303A7D4D2A7EB32D907EFBAC196A25BAB13B0E02B6259F
Key Value
MD58AC15F04554BE845A3321089D6313399
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
PackageNamepython38-numba
PackageRelease1.1
PackageVersion0.54.1
SHA-102084C3E85C4C817D8A80A69A7AEEF3F21FBB66C
SHA-256EDDD5607A00BB1A9B537D795AE58ABF5B7D6F1A415388FAF68AE65BF76CE0904
Key Value
MD51002CF0734BEC63A81716ADDB16F7A4C
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.
PackageNamepython38-numba
PackageRelease54.2
PackageVersion0.55.0
SHA-1920E492626E6F5D17306C009D43BFA50F6D0299C
SHA-2568A608921A44F2D7091F0C15B2E6E212BD2DD9FAC758713EA454880099A6DDD16