Result for 0139DF54EEB720EA186CEB4D984E476F2B9B7E08

Query result

Key Value
FileName./usr/lib/python3.8/site-packages/numba/tests/__pycache__/error_usecases.cpython-38.pyc
FileSize316
MD530273D638067F17A2E0F098AE64AB564
SHA-10139DF54EEB720EA186CEB4D984E476F2B9B7E08
SHA-25681123FABF7B9749160B32E3809D856145D216F3ED690CBEBB147545CA3A749B5
SSDEEP6:XmeKlgY+A6Xj+sOqkJwFA9YvLorBjRgBCdkv0MWlCr/R:KgY+A6TDBkJwawgoEA0blCr/R
TLSHT1BCE02B80CA821C96F9BCF7749121013D2CA2A8F6EB1DC0531F18A3962D041611432E44
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
MD5EA13BEB974A81C11071BEA94F10826E2
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.
PackageNamepython3-numba
PackageRelease3.3
PackageVersion0.48.0
SHA-165F50BE666F241E42BC26F21CA19FDA3478A9465
SHA-2563F26FD34FD71B7894A69C0455E85F6DC5DCD14C7787577277A24D0F58EA2172C