Result for 00C7B7037FC5741D14B39703ECE66A1F186D8382

Query result

Key Value
FileName./usr/lib/python3.8/site-packages/numba/tests/__pycache__/test_typeconv.cpython-38.pyc
FileSize6144
MD5C4C4BA768118B0798EF022DADAF8A917
SHA-100C7B7037FC5741D14B39703ECE66A1F186D8382
SHA-256B13A401B198809255897AC1510E548A641DEA8B04D4C440186E63483363BE384
SSDEEP96:MCPr10k3/L/B0yyG4xOFWmUhUE7xTjubuUh+wwTVjukbO0mhAGbn9JETSfmZIeGf:McukC9xf7wZUbO0mhAIf9mUSQ
TLSHT18FC1616C9643AEADF9B3F379946F0418F178930E531401A22650F758AF303ED2AB9BD4
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