Result for 01A1E64662D3CCF469FE6D31FFB00CCDA1E3E1EC

Query result

Key Value
FileName./usr/lib64/python3.6/site-packages/numba/cuda/tests/cudapy/test_montecarlo.py
FileSize604
MD595FFF7307734BA6B9910E652518FE6A8
SHA-101A1E64662D3CCF469FE6D31FFB00CCDA1E3E1EC
SHA-256B351B56084EB60557C4D15A9FB1C1871F1FCB17E8DBCBB0997872F5BA3DC21AD
SSDEEP12:eTBSDFwBx0Eig7CDeLNo/7Fm72H8H8H8KCF85Geh09+wq/ArfGh2aM7g:Jof7nG/7U24S5Geh09E/8+oaMc
TLSHT151F08B3FD1033507B74746D89D574192A698C4131F054C7DBC7D02476F94622A4E6C4B
hashlookup:parent-total7
hashlookup:trust85

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Parents (Total: 7)

The searched file hash is included in 7 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
FileSize1379476
MD5915B2E54E004DDE06942EF6F7D067D2D
PackageDescriptionnative machine code compiler for Python 3 Numba compiles native machine code instructions from Python programs at runtime using the LLVM compiler infrastructure. It could be easily employed by decorating individual computation intensive functions in the Python code. Numba could significantly speed up the performance of computations, and optionally supports compilation to run on GPU processors through Nvidia's CUDA platform. It integrates well with the Python scientific software stack, and especially recognizes Numpy arrays. . This package contains the modules for Python 3.
PackageMaintainerUbuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageNamepython3-numba
PackageSectionpython
PackageVersion0.50.1-2
SHA-1C9CF1B41DEB4D63E43CF2B197F9DDBA7B18335A2
SHA-256C28697D2523B677F5D21FA838E2478374DF3A230EA9B71EDCC622516B411A037
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