Result for 00653D4D5AADC699D2D4E561E7EB2BE9980EAEB4

Query result

Key Value
FileName./usr/lib64/python3.6/site-packages/numba/tests/doc_examples/__pycache__/test_typed_list_usage.cpython-36.opt-1.pyc
FileSize1994
MD5AB39E33065CEE6B585C910F5656C414E
SHA-100653D4D5AADC699D2D4E561E7EB2BE9980EAEB4
SHA-2569F04459B5A6BA7ABA49FC1532F69B91FFA95DCF9D77893983A943A43B4774CA1
SSDEEP24:yBCGOtM0fobA43ZaCZATtIjUn95BRn90hSoQesCMGg+huJnMH8TcmIil4MjrQnsH:y4Gh/A4QXTYishSKNHg+47T0S1f3dHF
TLSHT14041288F98495ABCF6D8F1F6B0A7112E5F3AD3BA6A4F71870704445A1E01AC048C4AAC
hashlookup:parent-total6
hashlookup:trust80

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Parents (Total: 6)

The searched file hash is included in 6 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
MD52B336D729458BD475DD8AFEC0D414070
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
PackageReleasebp154.1.67
PackageVersion0.51.2
SHA-112DCFC7A140F1AAC5D63DA7C13CAD074AD62B6F5
SHA-2562858190886CE9A2F94C029058CC1AD7905734BFC3B6F751DB7D55EAF075EADF6
Key Value
MD5106DA372AC7B4660DB5949F3A0A7CBD4
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
PackageReleasebp156.3.5
PackageVersion0.51.2
SHA-106436226CB42BA444A00149614CA79BA8515CBEA
SHA-256EBEBA588F8FFFB79AE2000DF00B071B68927E985F24523212A319D0D782C9A1D
Key Value
MD5BD75A01B719E679E2F83DAA32B50E2A7
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
PackageReleasebp155.2.21
PackageVersion0.51.2
SHA-137B3A4FC48EF5F95B447B59342D92A8F2990988E
SHA-256270EF3D7AC9AA2D2FCB6AA6915C5D7AC5E8A6E611DF478A6192C54F23E7E3AAD
Key Value
MD5A1A77B5B328FAFCFDD3FBEBEB52E297D
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
PackageReleasebp156.3.5
PackageVersion0.51.2
SHA-14037D3E1397065BD0C1B7EF25E1821878007ABF9
SHA-256044B3E142F45800414B33B845C0E16C86FC244F7B5B2BFB4957E482847567CB4
Key Value
MD5E6FD969E4DC09C3661AE01FD53D74990
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
PackageReleasebp154.1.67
PackageVersion0.51.2
SHA-1C74146211C3285BDFDDEFECE3F05920A728C47A6
SHA-2566147AC8A7D719637014C25D87DCB5AF7580AA36E5ED5C001A587A3A77773C3FD
Key Value
MD5ADB462D0D6AD70D7EE88A25A5BB5C063
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
PackageReleasebp155.2.21
PackageVersion0.51.2
SHA-1B87D53CDC76F3CD12B06B15D925F1B617E3EDBF6
SHA-256D26D89CBD85C2918F022F5575FC00A5E15391E795E7139ACAB018C7D8B44D8DD