Result for 006BB0E7618C550A61945587CD5CAB4162245FEE

Query result

Key Value
FileName./usr/lib64/python3.9/site-packages/numba/core/typeconv/_typeconv.cpython-39-s390x-linux-gnu.so
FileSize23224
MD58D0C5447563C35DB07345C2D8E7BDCB2
SHA-1006BB0E7618C550A61945587CD5CAB4162245FEE
SHA-25662C3106B6824826EDDE9D170C3D6D9890DD3933B4A07B9535EB9FB6CBFAB3482
SSDEEP384:BTvsABqdJCZXifQtMAjd2tmVi6VpMTkJLGP+8:BTv8d2SfJAjd2Qi6VpMTiLl8
TLSHT122A2D7537B548EAAD4A83F3715DAC374E3322A1262494B0EFB1CD7352C633608F26E50
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
MD59C84078D61357FE6993503AF5D441A31
PackageArchs390x
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.
PackageNamepython39-numba
PackageRelease51.27
PackageVersion0.53.0
SHA-1C8761BA63F3A16CF11A7FD4319E398F7F3124C24
SHA-25679E756AB2DBC796DB97DD8C02CB0684335F6643DB276C771846B35921F0B31F0