Result for 0123C698A0308A8D95F434BAEDA4ECC00458BB4B

Query result

Key Value
FileName./usr/lib/python3.8/site-packages/numba/tests/__pycache__/test_config.cpython-38.pyc
FileSize3037
MD5F5B4D7D733C6B6BC9A223AE470CABE54
SHA-10123C698A0308A8D95F434BAEDA4ECC00458BB4B
SHA-256BEE378E33A3170F3D50B990E0DA25581DE60D5BFFBE0D7C60507F0EC9D238DB0
SSDEEP48:oxi4TPX5YgrRKIuNS4CVUO9hHzH3JPyOijUB3/omasoQUR1/MxlOQjZi:oxnCOKXS4OUopDzB3Am/orPMfZNi
TLSHT1B151C4C70549AC2BFA61FEB9C32E4222AD328BEB515BB4177D0CF52D0F141C892E3885
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