Parents (Total: 27)

The searched file hash is included in 27 parent files which include package known and seen by metalookup. A sample is included below:

Key	Value
MD5	106DA372AC7B4660DB5949F3A0A7CBD4
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.
PackageMaintainer	https://bugs.opensuse.org
PackageName	python3-numba
PackageRelease	bp156.3.5
PackageVersion	0.51.2
SHA-1	06436226CB42BA444A00149614CA79BA8515CBEA
SHA-256	EBEBA588F8FFFB79AE2000DF00B071B68927E985F24523212A319D0D782C9A1D

Key	Value
FileSize	1514992
MD5	B1285EA3CDBBF12F55FFB3096B8AD0D4
PackageDescription	native machine code compiler for Python 3 Numba compiles native machine code instructions from Python programs at runtime using the LLVM compiler infrastructure. It could be easily employed by decorating individual computation intensive functions in the Python code. Numba could significantly speed up the performance of computations, and optionally supports compilation to run on GPU processors through Nvidia's CUDA platform. It integrates well with the Python scientific software stack, and especially recognizes Numpy arrays. . This package contains the modules for Python 3.
PackageMaintainer	Debian Science Maintainers <debian-science-maintainers@lists.alioth.debian.org>
PackageName	python3-numba
PackageSection	python
PackageVersion	0.52.0-4
SHA-1	08F898DE47538FFC7B8D77EAA605E24A9C9D6A20
SHA-256	E8E4700868F11496000B64F613716A43D0FAEF07C6C2F6845CA0DD4AD4E69722

Key	Value
FileSize	1518892
MD5	00BB154353C3A44456E7C37357DC0CF6
PackageDescription	native machine code compiler for Python 3 Numba compiles native machine code instructions from Python programs at runtime using the LLVM compiler infrastructure. It could be easily employed by decorating individual computation intensive functions in the Python code. Numba could significantly speed up the performance of computations, and optionally supports compilation to run on GPU processors through Nvidia's CUDA platform. It integrates well with the Python scientific software stack, and especially recognizes Numpy arrays. . This package contains the modules for Python 3.
PackageMaintainer	Debian Science Maintainers <debian-science-maintainers@lists.alioth.debian.org>
PackageName	python3-numba
PackageSection	python
PackageVersion	0.52.0-4
SHA-1	0E1B56774FA5E83D6319316258C88D07091A65F4
SHA-256	2896127B26DB22BD361AB9A88E8F1C06E83D0CD3701EA75872DC17EA196F684D

Key	Value
MD5	2B336D729458BD475DD8AFEC0D414070
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.
PackageMaintainer	https://bugs.opensuse.org
PackageName	python3-numba
PackageRelease	bp154.1.67
PackageVersion	0.51.2
SHA-1	12DCFC7A140F1AAC5D63DA7C13CAD074AD62B6F5
SHA-256	2858190886CE9A2F94C029058CC1AD7905734BFC3B6F751DB7D55EAF075EADF6

Key	Value
MD5	DCBFC246B43931DC15CE79952EBB4407
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	51.3
PackageVersion	0.53.0
SHA-1	17B952067229CC3FCD88CAD669A603E60B4395B5
SHA-256	5A264DDF0E77D82DBFAF36A40B2AA9C28F93C0E130A8317FDBD533F827F8A0D0

Key	Value
FileSize	1502420
MD5	506A38845B05B88B72C41FD3FE3DF053
PackageDescription	native machine code compiler for Python 3 Numba compiles native machine code instructions from Python programs at runtime using the LLVM compiler infrastructure. It could be easily employed by decorating individual computation intensive functions in the Python code. Numba could significantly speed up the performance of computations, and optionally supports compilation to run on GPU processors through Nvidia's CUDA platform. It integrates well with the Python scientific software stack, and especially recognizes Numpy arrays. . This package contains the modules for Python 3.
PackageMaintainer	Debian Science Maintainers <debian-science-maintainers@lists.alioth.debian.org>
PackageName	python3-numba
PackageSection	python
PackageVersion	0.52.0-4
SHA-1	181B729A4536B0B3000AD410D60110E415C4067F
SHA-256	E2BFBFC0BBC939A6EC3CAD13FB918F291CA16596436F70D8E88AB654186E076C

Key	Value
MD5	3B34138441C4DC8B67C553D0BB6C15F3
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	lp153.51.2
PackageVersion	0.53.0
SHA-1	1AF6D5089D4B71988629C4F977698EA631443119
SHA-256	C0DECFA83E87374DCBB381B5171E68F6759B8FEC440A7EC57DB81703EA3E12FF

Key	Value
MD5	D70EA79722238EADFB872F44B6A1E9C0
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	lp153.2.5
PackageVersion	0.53.0
SHA-1	3253B014B47FF0689926E07A511304DAB46336AD
SHA-256	747FF92B10647E7F5786C24596CA96587EEA8E13055C27E5748A8C8ABCA29107

Key	Value
MD5	BD75A01B719E679E2F83DAA32B50E2A7
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.
PackageMaintainer	https://bugs.opensuse.org
PackageName	python3-numba
PackageRelease	bp155.2.21
PackageVersion	0.51.2
SHA-1	37B3A4FC48EF5F95B447B59342D92A8F2990988E
SHA-256	270EF3D7AC9AA2D2FCB6AA6915C5D7AC5E8A6E611DF478A6192C54F23E7E3AAD

Key	Value
MD5	A1A77B5B328FAFCFDD3FBEBEB52E297D
PackageArch	s390x
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.
PackageMaintainer	https://bugs.opensuse.org
PackageName	python3-numba
PackageRelease	bp156.3.5
PackageVersion	0.51.2
SHA-1	4037D3E1397065BD0C1B7EF25E1821878007ABF9
SHA-256	044B3E142F45800414B33B845C0E16C86FC244F7B5B2BFB4957E482847567CB4