Result for 41D3A0D357FD099DC455307B7554FF8612F62C16

Query result

Key	Value
MD5	76E53FB6C6EB054FA9B890AB33621CB1
PackageArch	aarch64
PackageDescription	PyOpenCL makes it possible to access GPUs and other massively parallel compute devices from Python. Specifically, PyOpenCL provides Pythonic access to the OpenCL parallel computation API in a manner similar to the sister project `PyCUDA`. Python 3 version.
PackageMaintainer	Fedora Project
PackageName	python3-pyopencl
PackageRelease	2.fc32
PackageVersion	2019.1.2
SHA-1	41D3A0D357FD099DC455307B7554FF8612F62C16
SHA-256	691E0F0D38745BE3B1BDC1BA05E3B92AC0670987C6A4673913307E93C6E13D99
hashlookup:children-total	111
hashlookup:trust	50

Network graph view

Children (Total: 111)

The searched file hash includes 111 children files known and seen by metalookup. A sample is included below:

Key	Value
FileName	./usr/lib64/python3.8/site-packages/pyopencl/compyte/ndarray/__pycache__/gen_reduction.cpython-38.opt-1.pyc
FileSize	52543
MD5	1705DA56A95AD3CAB238FE3C3E336988
SHA-1	00C1519EA89D49BD44FA450E67D0397F7EB55319
SHA-256	B892B9DA1F3FA51E1597FA5E04F873CAA3596EF9724D5EECB25AA1B44F6C23D3
SSDEEP	384:9gzQv5i82uUvU7P9jOjT1/L4CUoj1owhdOlbyPVtNH7vafXTtg:9gzQn2fU7P9jOjT1z4Ej1ok2boV7LafG
TLSH	T19033585C0C7B0BA6F956F874475A21152E07D20B26C8A9F1F92DD1E19F0E0D89FF239A

Key	Value
FileName	./usr/lib/python3/dist-packages/pyopencl/bitonic_sort_templates.py
FileSize	16107
MD5	EF3D88EB8C079640729FB39AB9E6429C
SHA-1	02B4316BB36BB0AE08B2240668663C805328A112
SHA-256	1867D1531AAF96B1EB7A856233563E7AD981A31974176DC3FDC2AFD304B3EBCF
SSDEEP	384:vritKB+6AgRX7jjB48BNBCBy1BFfQMr7/kcJPh/kpUNNrQwDBlhlok14p:vZ+5mX7jjBtBNBCBqBFt/hv/2Uz/DBhY
TLSH	T15172622239A90551797624DFEB9174003A5AF13FA6E8EEA0393E41451F52F2C23FE79C
tar:gname	root
tar:uname	root

Key	Value
FileName	usr/lib/python3.12/site-packages/pyopencl/cl/pyopencl-random123/threefry.cl
FileSize	54699
MD5	A191744A31FAD84FAD0CFBC92A14B486
SHA-1	036890928362E83B633F397AC7D0BF6185EB416D
SHA-256	D969901B1C7980F4AFDB650BF7F3255EFD1E32E83DD64DDB0BEE7FC90E309672
SSDEEP	384:trUCrUKr1DLaPiLeuHG75L4CB9U8KT7ocv/:tDxDLHe5L4CB9U8K/
TLSH	T11433BCB51565C4313F634B70B67EB1D2205A42FB0A600E7EB81ED6E0AF2E4F9359B5C8
tar:gname	root
tar:uname	root

Key	Value
FileName	./usr/lib64/python3.8/site-packages/pyopencl/__pycache__/bitonic_sort_templates.cpython-38.pyc
FileSize	15982
MD5	6927574A2DF3CBE345FD2214D9BC25F8
SHA-1	0373F904A1ACA209A9F684E0739E93ABF636DD6D
SHA-256	2C8EA99E3FFC1D4DAE7F1560F7B2D6AE209F535CFC201CD65E0A8051224927EA
SSDEEP	384:4ritKB+6A3X7jbH4PHAH8HA3FfQMre/kcJPf/kpUNNMQwF3lhlok14PE:4Z+53X7jbH2HAH8HA3FI/hV/2Uk/F3hL
TLSH	T1CA72322639A90151697624EFAB9174003A5BF13FA7E8EA90393E41441F52F2C23FF78D

Key	Value
FileName	./usr/lib64/python3.8/site-packages/pyopencl/__pycache__/tools.cpython-38.pyc
FileSize	29842
MD5	7C9F60DE9E7D7894B051537723DF9483
SHA-1	0A822D8F7BF6BB5775E9669AA388C5E034143C73
SHA-256	9007A581487598D0D97415C503A4E89DAE04CE7A15DEBFEDDEA83288E9A84971
SSDEEP	768:c7YhQxUtpw+AJoOY6K0zug2/6wdhQ8Y6ZmyGK5Pf:c7YBAJoOlKEug2C2h5Pf
TLSH	T12BD2C5A2B195A94BFBA1F2B8844932107326B337570DA143370CB26B3FC96C89D7579C

Key	Value
FileName	./usr/share/doc/python-pyopencl-doc/examples/print-binary.py
FileSize	248
MD5	89D093F25E1585106B8A6BDE1E3F1BC3
SHA-1	0E517933C4946DD4D200E3E2F32D9ECD164B17F2
SHA-256	5450F9391A244F22B20FDA65C46905C135227B050F167D48614F4DA0D41D3F68
SSDEEP	6:J0p+KMABKzA+wycGhm6W4nMisHtehMLn7tvrQ7OHB99n:9KjKzBwycY8iyKMLnlQIz
TLSH	T1E7D09712E00EB9B1B3C6308C4322A6B2C7B038753FA0652C332007FA9A823101CB5228

Key	Value
FileName	./usr/share/doc/python-pyopencl-doc/examples/demo-struct-reduce.py
FileSize	1856
MD5	AC3B169C8FA1618D55BB19BDA2A4D495
SHA-1	1521A985192CD4273EC3EF8FBF48B37A2F54675A
SHA-256	BB31586DDE93AD5811F504D5865DBA0A9DCE785032C94F16C5AB316752C03C2C
SSDEEP	48:Pv1CRXoZzyeMBzU8RZVA+OCLO/K0vOEqO/SgvONObO8OTlEBeLo+I+SWM5Itqb6q:Ho+ZzyeMBzUAZV0BeLZSitS/
TLSH	T10231C3D65C033A2A53DB743C8B99A19DDF123A97890864C0B79C53B4BF41324B1753B4

Key	Value
FileName	./usr/lib64/python3.8/site-packages/pyopencl/compyte/ndarray/__pycache__/test_gpu_elemwise.cpython-38.opt-1.pyc
FileSize	8090
MD5	8765CAE5919C4E1752A73B279800AA2E
SHA-1	154872E78465C3AD8AD1C334795F61164779B2CA
SHA-256	0D3CB2D3D3C7D49C56EFCD458A096CD04F962F1824AA4305D4468B740F74973E
SSDEEP	192:8/7c0jeWAfvBadIkWKDNakmp8Xi6Ks5yvo6ZxyqI:8zWvBadIkWKDUkmp2IvBvLI
TLSH	T1ECF1639434810D37F9AEF6F89749432D96DEC6956F8EEA1BF40691065F823800D60BEC

Key	Value
FileName	./usr/share/doc/python-pyopencl-doc/examples/transpose.py
FileSize	6110
MD5	468BAACB94EC9E984EDC506A1C2A9505
SHA-1	16D1A8EB6230C7892D7D2319F24CEF9A19725139
SHA-256	59DA83BFD96C9FF304E7D57599A2526D96AF21FF0B3D35D2503A378849861847
SSDEEP	96:WJKJXksWl6aDwyDAmrsaJUfkePaDLoqEBK0YjtwwC+5jebv7AlHvf1QQ9v5aGiot:WK5ksJCsaOM0aoqEfmtwKp+zAN1Qyv5v
TLSH	T1F4C152E7842A58A55712F8BD89C3D112733D9B03C5486C68BFBCA4102F9DE1D42B75F5

Key	Value
FileName	./usr/lib64/python3.8/site-packages/pyopencl/compyte/ndarray/__pycache__/test_gpu_ndarray.cpython-38.pyc
FileSize	12121
MD5	559FFC563A8DF96EF725565BC5965466
SHA-1	1DC3BD40AB297FB9FB01BC13176BF1CDDB90DB49
SHA-256	DD3BDAFD82C6A08A1C537379241411A0D297F3F93C8C4C217303EF33EC3C5624
SSDEEP	192:vh4VFWahwp8Mf/48CxPf5uEXrxgajIkBm7EO5Pz26To7:yVFWa6fRobaajIkBmI+Pa6Q
TLSH	T19D42E8E7BC04AA5FFE9DF5F4600C426846E5E2B8FBC752A60805D1EF1D402D91F20A5E