Result for 005F0C49265588612E909C74FAC617414150A0AA

Query result

Key Value
FileName./usr/lib64/python3.8/site-packages/numba/cuda/tests/cudapy/__pycache__/test_macro.cpython-38.pyc
FileSize3995
MD50ACD75DDBF01A1BEDD5023BD3C6CFCA5
SHA-1005F0C49265588612E909C74FAC617414150A0AA
SHA-25642D4406DBB8B68D68ABFD806E3ED7C1514D531A776A8E6F6415F9D2FA9154799
SSDEEP48:3p+eKqAbrZy5bNaYlNpvv2SRqYvJoIALL+gcoJtsUevv2/:1pAbrSNaYbZe2hvJobcqT/
TLSHT1BE8142A06942DE5AFC99F2BC847F020DA738D773A35F794B452C929E1C89BC51A26480
hashlookup:parent-total1
hashlookup:trust55

Network graph view

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
MD5B764D08CFAEE3AF4221DF7215859120B
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
PackageRelease3.3
PackageVersion0.48.0
SHA-19EE3AC165B646510E966FBAF13E4F1739D692098
SHA-256D1B9933DC5C1E5226EECEEAE67919520C41E0CB57825907771AF1433D9450C71