Result for 006B884AB76A859982FFA7D6DC8ABF1BA0DFD706

Query result

Key Value
FileName./usr/lib64/python3.9/site-packages/numba/tests/__pycache__/test_heapq.cpython-39.opt-1.pyc
FileSize12398
MD57D950A9E1BE965021E21905AC6D3934D
SHA-1006B884AB76A859982FFA7D6DC8ABF1BA0DFD706
SHA-2566E536B7B9E8D57B75D65F60D426E76C5E7ACD103BBF22ACF2933FF3F8C73D9B3
SSDEEP384:owHqGqMWqgjgsj35PqOMdqqmq2TqteGzxqeDgqwWqSLq9cqxq+wMqeqgq68KVqSG:owHqGqMWqgfj35PqOMdqqmqgqteSxqeT
TLSHT1D542B6EEA4CA6E8FFD79F1BE84560314F1B4E31B4388D5E39110D25E2FA26C41EB1099
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
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