Result for 00995FB50AF9C57BBD299DB577F299565367B9F4

Query result

Key Value
FileName./usr/lib64/python3.6/site-packages/numba/__pycache__/dataflow.cpython-36.pyc
FileSize29633
MD501362F3A497920CB0A4E32F741B1B436
SHA-100995FB50AF9C57BBD299DB577F299565367B9F4
SHA-256012EBA153D02B9C279D22E227A21B74EF2F330EE05EE838F4BA925970ECE47AE
SSDEEP384:HbHIvINgm9zqXVnRE6o/vVutcV1AQpOb3D9nQuP89OeCW1gAFL:HbovkzqXBRE6oHTW3P89HCW1gAV
TLSHT13FD28592B2429CCDFD32F3F84AAD4151572C8A3F3BCDB0526629E1DA2F411D42E3559E
hashlookup:parent-total1
hashlookup:trust55

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Parents (Total: 1)

The searched file hash is included in 1 parent files which include package known and seen by metalookup. A sample is included below:

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