Result for 00093ECB58F842EF8B1FC6684A03E344CC9E47AE

Query result

Key Value
FileName./usr/lib/python3.8/site-packages/numba/core/types/__pycache__/misc.cpython-38.opt-1.pyc
FileSize20252
MD5F2F438D7BE4544EADE9AA6E3A9009749
SHA-100093ECB58F842EF8B1FC6684A03E344CC9E47AE
SHA-2562FF62407BF3BF492603BC9A93881932E1E315E8ABC215C6161E8FDAB385B9839
SSDEEP384:uKNr6QVCQwrnuYD549WWbFUJCxWoCleEhfjrjkmD2u:uKNr6QVCQwrBG9WWbFdMZeEhfjrjkmKu
TLSHT1D19272C2AF4A5D5FF8A7F3B2D13A13006B658337E7585D47642A806F2E8B2D20DB5358
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
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