Parents (Total: 11)

The searched file hash is included in 11 parent files which include package known and seen by metalookup. A sample is included below:

Key	Value
MD5	6767B97DA0071297650D9B9A797D6C1E
PackageArch	noarch
PackageDescription	When reading from many possibly large files in a fashion similar to random access, it is usually the fastest and most efficient to use memory maps. Although memory maps have many advantages, they represent a very limited system resource as every map uses one file descriptor, whose amount is limited per process. On 32 bit systems, the amount of memory you can have mapped at a time is naturally limited to theoretical 4GB of memory, which may not be enough for some applications. The documentation can be found here: http://packages.python.org/smmap
PackageName	python36-smmap
PackageRelease	34.13
PackageVersion	4.0.0
SHA-1	4CF48F2F93A4BA78C87ABAAD6038DB8E3105596F
SHA-256	E51C479D90FC8368933EFFD2D4CD59100E46791E1785FE77310FC1C8C3B442FC

Key	Value
MD5	DABA664BCC8CF1C63A5700AF5AD8EF34
PackageArch	noarch
PackageDescription	When reading from many possibly large files in a fashion similar to random access, it is usually the fastest and most efficient to use memory maps. Although memory maps have many advantages, they represent a very limited system resource as every map uses one file descriptor, whose amount is limited per process. On 32 bit systems, the amount of memory you can have mapped at a time is naturally limited to theoretical 4GB of memory, which may not be enough for some applications. The documentation can be found here: http://packages.python.org/smmap
PackageName	python3-smmap
PackageRelease	lp152.34.2
PackageVersion	4.0.0
SHA-1	DB739A10A9F35C966673C69EE6BCD72099F85C06
SHA-256	E56E8D863D7F9DB8A935BDB4CADC58EFD8C62E05ADBBD16F95255BAE46ADC1E7

Key	Value
MD5	CF6FC6D108FA42B35659F24214939D8F
PackageArch	noarch
PackageDescription	When reading from many possibly large files in a fashion similar to random access, it is usually the fastest and most efficient to use memory maps. Although memory maps have many advantages, they represent a very limited system resource as every map uses one file descriptor, whose amount is limited per process. On 32 bit systems, the amount of memory you can have mapped at a time is naturally limited to theoretical 4GB of memory, which may not be enough for some applications. The documentation can be found here: http://packages.python.org/smmap
PackageName	python3-smmap
PackageRelease	34.3
PackageVersion	4.0.0
SHA-1	E2537AA840911DC6C2EF4A9756365DFFFDA33A6F
SHA-256	3821054ACE662A7D665961E7E712F0A38CD583BE4C51841595BFC5FF6DFC613B

Key	Value
MD5	563F5516CF7605431EF3F010B806F782
PackageArch	noarch
PackageDescription	When reading from many possibly large files in a fashion similar to random access, it is usually the fastest and most efficient to use memory maps. Although memory maps have many advantages, they represent a very limited system resource as every map uses one file descriptor, whose amount is limited per process. On 32 bit systems, the amount of memory you can have mapped at a time is naturally limited to theoretical 4GB of memory, which may not be enough for some applications. The documentation can be found here: http://packages.python.org/smmap
PackageName	python3-smmap
PackageRelease	lp151.2.1
PackageVersion	3.0.5
SHA-1	358F74ED64CC87A0DA1D51A4DE8187198E150E22
SHA-256	42FF8C60A292D9A4BE989C80AF616D0B273C29CAD0286FF7CC1687FB107EE4D5

Key	Value
MD5	F28685E2B040E9BA320DB2F3DEF6ADB2
PackageArch	noarch
PackageDescription	When reading from many possibly large files in a fashion similar to random access, it is usually the fastest and most efficient to use memory maps. Although memory maps have many advantages, they represent a very limited system resource as every map uses one file descriptor, whose amount is limited per process. On 32 bit systems, the amount of memory you can have mapped at a time is naturally limited to theoretical 4GB of memory, which may not be enough for some applications. The documentation can be found here: http://packages.python.org/smmap
PackageName	python36-smmap
PackageRelease	1.2
PackageVersion	3.0.5
SHA-1	92A8E7008D60A0A56290A13CFB17CC39134EC0A5
SHA-256	DA06CB96F01CA41A06465E5A6580097FA3C882BFF7016CF47DECB5E7098CD9AB

Key	Value
MD5	26E906529ED1F5B7DD05D6689F9B2FC7
PackageArch	noarch
PackageDescription	When reading from many possibly large files in a fashion similar to random access, it is usually the fastest and most efficient to use memory maps. Although memory maps have many advantages, they represent a very limited system resource as every map uses one file descriptor, whose amount is limited per process. On 32 bit systems, the amount of memory you can have mapped at a time is naturally limited to theoretical 4GB of memory, which may not be enough for some applications. The documentation can be found here: http://packages.python.org/smmap
PackageName	python3-smmap
PackageRelease	33.3
PackageVersion	3.0.5
SHA-1	B0F6D7429E56EC998A67DF61DA0D9866A759EFDE
SHA-256	7E611EAFFB729291C76AA0143F1D110F24E54FBBF9B98ED89D38332F916F853B

Key	Value
MD5	CA03BE4CA0850C1DEFBE6356928A88A0
PackageArch	noarch
PackageDescription	When reading from many possibly large files in a fashion similar to random access, it is usually the fastest and most efficient to use memory maps. Although memory maps have many advantages, they represent a very limited system resource as every map uses one file descriptor, whose amount is limited per process. On 32 bit systems, the amount of memory you can have mapped at a time is naturally limited to theoretical 4GB of memory, which may not be enough for some applications. The documentation can be found here: http://packages.python.org/smmap
PackageName	python36-smmap
PackageRelease	34.12
PackageVersion	4.0.0
SHA-1	2CBAABB27861D7BF53919F7915CA264BC224306C
SHA-256	06A36B86E86A55ED68B0D7DB2B9148024937A9DCD3FC9645D78047291D1FAB6B

Key	Value
MD5	21FA62F9049FA834951CA082AA085603
PackageArch	noarch
PackageDescription	When reading from many possibly large files in a fashion similar to random access, it is usually the fastest and most efficient to use memory maps. Although memory maps have many advantages, they represent a very limited system resource as every map uses one file descriptor, whose amount is limited per process. On 32 bit systems, the amount of memory you can have mapped at a time is naturally limited to theoretical 4GB of memory, which may not be enough for some applications. The documentation can be found here: http://packages.python.org/smmap
PackageName	python3-smmap
PackageRelease	lp151.32.1
PackageVersion	3.0.4
SHA-1	C0148A9C2F9B74C4BBC2BA8B5ED0D93457662991
SHA-256	67B668796DB272ED99A663109AABD2CC8EB4F639F88BA429405B525E0B054AA7

Key	Value
MD5	034E4B9231B41614EAA50B8273E4092D
PackageArch	noarch
PackageDescription	When reading from many possibly large files in a fashion similar to random access, it is usually the fastest and most efficient to use memory maps. Although memory maps have many advantages, they represent a very limited system resource as every map uses one file descriptor, whose amount is limited per process. On 32 bit systems, the amount of memory you can have mapped at a time is naturally limited to theoretical 4GB of memory, which may not be enough for some applications. The documentation can be found here: http://packages.python.org/smmap
PackageName	python3-smmap
PackageRelease	lp153.34.3
PackageVersion	4.0.0
SHA-1	0853580031AE6B8299203CDA49225180D2D94793
SHA-256	71F0BC4129BF202E53D76F91273538FEA9C4559A05FB74AE8CF35200D97FAA6F

Key	Value
MD5	633E49628825D678CFFF0BAFC2990FB5
PackageArch	noarch
PackageDescription	When reading from many possibly large files in a fashion similar to random access, it is usually the fastest and most efficient to use memory maps. Although memory maps have many advantages, they represent a very limited system resource as every map uses one file descriptor, whose amount is limited per process. On 32 bit systems, the amount of memory you can have mapped at a time is naturally limited to theoretical 4GB of memory, which may not be enough for some applications. The documentation can be found here: http://packages.python.org/smmap
PackageMaintainer	https://bugs.opensuse.org
PackageName	python3-smmap
PackageRelease	bp154.1.49
PackageVersion	3.0.2
SHA-1	EFE2861D5538485CA5E6E6DFEFEC3826F5D80AC7
SHA-256	1AC3FADBAB590B94F96281D86619924FC99A9CFB21A9040CFB847C76125F83C6

Key	Value
MD5	FB6EB199BA1A89D1AD19F60D527835D8
PackageArch	noarch
PackageDescription	When reading from many possibly large files in a fashion similar to random access, it is usually the fastest and most efficient to use memory maps. Although memory maps have many advantages, they represent a very limited system resource as every map uses one file descriptor, whose amount is limited per process. On 32 bit systems, the amount of memory you can have mapped at a time is naturally limited to theoretical 4GB of memory, which may not be enough for some applications. The documentation can be found here: http://packages.python.org/smmap
PackageMaintainer	https://bugs.opensuse.org
PackageName	python3-smmap
PackageRelease	bp155.2.13
PackageVersion	3.0.2
SHA-1	62B98D8C5C7D45FCAD152674114336FC030E8194
SHA-256	A0AE96A6E2E7720FB3CE16305593EC4E5292A7824199BB0713C4351FCC9DD600