Parents (Total: 38)

The searched file hash is included in 38 parent files which include package known and seen by metalookup. A sample is included below:

Key	Value
SHA-1	01D8F27093B9C23517E4DF53030A2BB39A431C30
snap-authority	canonical
snap-filename	guuqEF6cnnKFfecNJNF4fmyvQMfP5ODm_101.snap
snap-id	guuqEF6cnnKFfecNJNF4fmyvQMfP5ODm_101
snap-name	home-assistant-configurator
snap-publisher-id	Zgwwrb2vssjDtam8qFmo4ezg3koyPPyQ
snap-signkey	BWDEoaqyr25nF5SNCvEv2v7QnM9QsfCc0PBMYD_i2NGSQ32EF2d4D0hqUel3m8ul
snap-timestamp	2020-09-06T23:07:45.366233Z
source-url	https://api.snapcraft.io/api/v1/snaps/download/guuqEF6cnnKFfecNJNF4fmyvQMfP5ODm_101.snap

Key	Value
MD5	D57AF2C63B2ACA006E43677959C9B81E
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	python38-smmap
PackageRelease	34.17
PackageVersion	4.0.0
SHA-1	057EFC9971FF46798195D737A697413055041E6E
SHA-256	EC2AEFFF6888CA3FFB7DBDFE3029808FEB1F78489355A5B78F1D00BD3FECC867

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	36177082E0C6AAE3DE9FE88FAA5FB02C
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	lp152.2.2
PackageVersion	4.0.0
SHA-1	0F18B6AD5FC3BE351BC8E53BA21F7341ECA4E873
SHA-256	72FFC9CE1D3513A203803C6A3425B435A40B061228094BF754AC96E731A56141

Key	Value
MD5	9FA8491CDD64017464EF7D53A2569620
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	2.2
PackageVersion	4.0.0
SHA-1	166C1F5715DDFAF88C4FE6DE0E17FD2DE2B96BED
SHA-256	670F9B19EF7213C53BAB75A6164A964BCB8747E207F85B92A244D37F4CAA08A2

Key	Value
MD5	3922BE787A4ED4A48C9EB92F0821909F
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	2.3
PackageVersion	4.0.0
SHA-1	18184044F6B23570139F86366D1A9A89C362ABAE
SHA-256	7208B6D7A9FACEAD9FDD68CEB9CDDAB473C0BDF57649DE8111BD2C5C6B535BF6

Key	Value
MD5	31048AE5984A5FFA513B2A9B743AEC6C
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	lp152.2.2
PackageVersion	4.0.0
SHA-1	2405C7E3B6A0771FA5AC4188BA20C7245108FBFE
SHA-256	9601487C61FC3F0C16827DF667180A3E3113A0E18334B48693F6AFEA619150FB

Key	Value
MD5	324CE6D66E3E385AA6CBE34B3E78B224
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	python39-smmap
PackageRelease	34.12
PackageVersion	4.0.0
SHA-1	2656E979BD56D70F570A64703BAA8267A509EC84
SHA-256	018B7F87112D1DAB83D894E17B6887EC477B20E27F7DFE712BB4E1D6FCA99BA1

Key	Value
MD5	92D3150EAF0C05F275CB206DC52F40EF
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	282C1011F69561F52B8429222F2125688CD1A4D8
SHA-256	A52652AD28E0B1A7C7CE36FE71F053DCA8401A79AA4D0D04EB912FCD94CD7BC9

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