Result for 01B8522C667EE64EE1BE12F8AA491AF511399A7F

Query result

Key Value
FileName./usr/lib/python3.8/site-packages/numba/tests/doc_examples/__pycache__/test_literally_usage.cpython-38.opt-1.pyc
FileSize2112
MD541B80A07F19161D09183FAB24710D9BE
SHA-101B8522C667EE64EE1BE12F8AA491AF511399A7F
SHA-256D21AD1EF11FB32E9382C99E6A9887B168EF37F50616C5DB0C7B7CD859704EEE3
SSDEEP48:leGDmrQt7nkEkExqiYyEBeyjxEz8EMh/zC/NwUEqMEHy:sGDmrwg93iYyGey168hhLZU3M8y
TLSHT1EA41CCDA06460C3EF4BCF3BBB5D61124EF734163B6062702712C65EEEC0728624A2778
hashlookup:parent-total3
hashlookup:trust65

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Parents (Total: 3)

The searched file hash is included in 3 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
MD55D2E84100ECF4FB9E2AE48FB17450A4C
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.
PackageNamepython38-numba
PackageRelease54.3
PackageVersion0.55.0
SHA-1C7452AD002F685D37EF92E82E49758BDEC0D783A
SHA-2569D07AF4742C09184FD303A7D4D2A7EB32D907EFBAC196A25BAB13B0E02B6259F
Key Value
MD58AC15F04554BE845A3321089D6313399
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.
PackageMaintainerhttps://bugs.opensuse.org
PackageNamepython38-numba
PackageRelease1.1
PackageVersion0.54.1
SHA-102084C3E85C4C817D8A80A69A7AEEF3F21FBB66C
SHA-256EDDD5607A00BB1A9B537D795AE58ABF5B7D6F1A415388FAF68AE65BF76CE0904
Key Value
MD51002CF0734BEC63A81716ADDB16F7A4C
PackageArcharmv7hl
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.
PackageNamepython38-numba
PackageRelease54.2
PackageVersion0.55.0
SHA-1920E492626E6F5D17306C009D43BFA50F6D0299C
SHA-2568A608921A44F2D7091F0C15B2E6E212BD2DD9FAC758713EA454880099A6DDD16