Result for 00517F7FDF1A7AD90E3211BC1866860F5776D74B

Query result

Key Value
FileName./usr/lib64/python3.6/site-packages/numba/cuda/tests/cudapy/__pycache__/test_inspect.cpython-36.pyc
FileSize2072
MD56D9E5F30128BF15EA64279B73FBA62AE
SHA-100517F7FDF1A7AD90E3211BC1866860F5776D74B
SHA-2562D91EAD3C8F6DA250E7267F6FE8668A3B7E4B64578B723ED6BFEA4A1C182BC80
SSDEEP48:2nJAbgQ+vYTQtt9HuAvWF3Ku3t9f/gm4Lcpc:qAb8+F3KudV/b8mc
TLSHT1F74182980203DE9EFE29F2B864AF070EC5B4C47E7F8827740A0040BD9F5928B588164F
hashlookup:parent-total5
hashlookup:trust75

Network graph view

Parents (Total: 5)

The searched file hash is included in 5 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
MD5C85A87532D4326D031C96ECEC1A57C14
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.
PackageMaintainerhttps://bugs.opensuse.org
PackageNamepython3-numba
PackageReleasebp153.1.18
PackageVersion0.37.0
SHA-19A25515A3F0F9F78CBAB1189A062D4EDAF8ABF0F
SHA-256143E8AEE9EB4B3F087C5654D3AB1A61B0A88C1C7179A82AE6187182010467DCC
Key Value
MD58B2EBD08D6BEC47EA5AA71D52D910A20
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
PackageNamepython3-numba
PackageReleaselp151.3.5
PackageVersion0.37.0
SHA-113DE3EED8C75AB82F96BFB22B8B80A4F9352A749
SHA-256A8AFFFCABC73831A59869BA2256013D3290F626F1F7E63D773E6AF5D6A224C64
Key Value
MD58890CF490A99D514072A1239BA0E8D7C
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
PackageNamepython3-numba
PackageReleaselp150.2.2
PackageVersion0.37.0
SHA-11DA817A714284E4AEE8C7BD60C215E1F2323B35D
SHA-256FEBD65A8D31D2DEA56F232976BF2C0E4EABF47DA115CF6E49479D1B8763A9044
Key Value
MD5ABB145C90E8EDF6BAF060CE729CD7596
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
PackageNamepython3-numba
PackageReleaselp152.4.9
PackageVersion0.37.0
SHA-186ACD8B62FCAD54DFD1BAE42614E4B528CB03D5B
SHA-2567BADDE4B7B257F2D769CB8FC0065C5AA5536068C0B427303E68AD5468D81EAD6
Key Value
MD53CE84EC00D5B4E3CB3FC71CD1C905B4E
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
PackageNamepython3-numba
PackageReleasebp153.1.18
PackageVersion0.37.0
SHA-1AB8B0F0F5A12AFC49DB0AB5FFAED5B73149860F8
SHA-256FB18E153322A38793B99BD59782B0694A25A8F337CEBBCB39946095C5550AD95