Result for 003AA7F7177EF7538FE8331B89494D8CE5C04152

Query result

Key Value
FileName./usr/lib64/python3.6/site-packages/numba/cuda/tests/cudapy/__pycache__/test_complex.cpython-36.pyc
FileSize11285
MD5135480EC08219A5033CA02B66575EAFC
SHA-1003AA7F7177EF7538FE8331B89494D8CE5C04152
SHA-25679BEFDD2B25556F15B2FD7F9FA28922AB847891D4E252324D2BB0B4864D9A0C4
SSDEEP192:Ea30u6YGBtisbnGpfYMGNrYewAANOLl6G3zETKgVSf4:E9Y6dGpfYjNOA/U2gYf4
TLSHT10A3230CF66021E57FDE5F3F8512A52411735C276BB8E93B70D6C928E0E043980DA6BD8
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
MD50C04AAD870FEEEBA60F7EA420C70FAD0
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.
PackageNamepython3-numba
PackageRelease44.1
PackageVersion0.48.0
SHA-187894AE6B9EA7EE72CE95B6EB6E6703AAEE29C8F
SHA-2562DEEBFEFFF7FBAFE10AEFF8EADCEACBB82DFB587D57431F955E6B1E933FADD5B