Parents (Total: 6)

The searched file hash is included in 6 parent files which include package known and seen by metalookup. A sample is included below:

Key	Value
MD5	0C04AAD870FEEEBA60F7EA420C70FAD0
PackageArch	x86_64
PackageDescription	Numba 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.
PackageName	python3-numba
PackageRelease	44.1
PackageVersion	0.48.0
SHA-1	87894AE6B9EA7EE72CE95B6EB6E6703AAEE29C8F
SHA-256	2DEEBFEFFF7FBAFE10AEFF8EADCEACBB82DFB587D57431F955E6B1E933FADD5B

Key	Value
MD5	E49D476075169CA9191664F30E6DE118
PackageArch	x86_64
PackageDescription	Numba 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.
PackageName	python3-numba
PackageRelease	lp151.3.2
PackageVersion	0.48.0
SHA-1	43BA13C1802B5F852050F73BA2BF7507F1C60861
SHA-256	37B5272CCDF09310FB607B14CAD201FFC8D59F83831E6B6903A42A0667F62DF3

Key	Value
MD5	B764D08CFAEE3AF4221DF7215859120B
PackageArch	x86_64
PackageDescription	Numba 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.
PackageName	python3-numba
PackageRelease	3.3
PackageVersion	0.48.0
SHA-1	9EE3AC165B646510E966FBAF13E4F1739D692098
SHA-256	D1B9933DC5C1E5226EECEEAE67919520C41E0CB57825907771AF1433D9450C71

Key	Value
MD5	4F9BA253BD558CE651F3B0BF44AB8DCE
PackageArch	x86_64
PackageDescription	Numba 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.
PackageName	python3-numba
PackageRelease	3.1
PackageVersion	0.48.0
SHA-1	749F0CEFC80840C6EE96E714BB6C39D75609DE1E
SHA-256	9F4AA8A68BB749FAC735F0483B35A176D3E69E0C9180CDA79377F0A6042DECCF

Key	Value
MD5	EA13BEB974A81C11071BEA94F10826E2
PackageArch	i586
PackageDescription	Numba 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.
PackageName	python3-numba
PackageRelease	3.3
PackageVersion	0.48.0
SHA-1	65F50BE666F241E42BC26F21CA19FDA3478A9465
SHA-256	3F26FD34FD71B7894A69C0455E85F6DC5DCD14C7787577277A24D0F58EA2172C

Key	Value
MD5	6D796110A14D6E4A5AFE6175DBCC55EA
PackageArch	x86_64
PackageDescription	Numba 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.
PackageName	python3-numba
PackageRelease	3.2
PackageVersion	0.48.0
SHA-1	A5FDFF39BAB7CF7DB86796362A1ACC13B9DF4D30
SHA-256	7442F86AF7FB69835299E496D253404CEBDF1562C1440DB8459A2A11306C171A