Parents (Total: 13)

The searched file hash is included in 13 parent files which include package known and seen by metalookup. A sample is included below:

Key	Value
MD5	80017033CE70A448B4170A719C795F63
PackageArch	armv7hl
PackageDescription	PyTables is a package for managing hierarchical datasets and designed to efficently cope with extremely large amounts of data. PyTables is built on top of the HDF5 library and the NumPy package and features an object-oriented interface that, combined with C-code generated from Pyrex sources, makes of it a fast, yet extremely easy to use tool for interactively save and retrieve large amounts of data.
PackageName	python310-tables
PackageRelease	19.1
PackageVersion	3.7.0
SHA-1	72F92D8717061E054A0DF9F4FC4818FAFFAD82A0
SHA-256	BDE3E68C59FA16361AFB00381F340E4B4BF02661F69E404E1C8085AE9001F3F5

Key	Value
MD5	4642E0C720C75D267ABC3B8CDA5AEFB1
PackageArch	armv7hl
PackageDescription	PyTables is a package for managing hierarchical datasets and designed to efficently cope with extremely large amounts of data. PyTables is built on top of the HDF5 library and the NumPy package and features an object-oriented interface that, combined with C-code generated from Pyrex sources, makes of it a fast, yet extremely easy to use tool for interactively save and retrieve large amounts of data.
PackageName	python39-tables
PackageRelease	19.1
PackageVersion	3.7.0
SHA-1	D6B1202EA51ADD627D9E23F5483ABBE446896CF6
SHA-256	85E9DF745364075A542C911BB0DA7923DC97BB12E397784ECDF75B8E441C7584

Key	Value
MD5	94271992B0A49546B72F07AD0741194D
PackageArch	armv7hl
PackageDescription	PyTables is a Python 3 package for managing hierarchical datasets designed to efficiently and easily cope with extremely large amounts of data. It is built on top of the HDF5 library and the NumPy package (numarray and Numeric are also supported). PyTables features an object-oriented interface and performance-critical extensions coded in C (generated using Pyrex) that make it a fast yet extremely easy-to-use tool for interactively processing and searching through very large amounts of data. PyTables also optimizes memory and disk resources so that data occupies much less space than with other solutions such as relational or object-oriented databases (especially when compression is used).
PackageMaintainer	neoclust <neoclust>
PackageName	python3-tables
PackageRelease	1.mga9
PackageVersion	3.7.0
SHA-1	FC8B064172799D28DD12EF3C1BFE8EF0F35919F5
SHA-256	3CBADBA3E551754A9F106E1F2E77F609CE4F42835E3D9D677CA6CC18027C49CB

Key	Value
MD5	469BA2DA942B6AB78CB705F3F7D1BAC0
PackageArch	aarch64
PackageDescription	PyTables is a Python 3 package for managing hierarchical datasets designed to efficiently and easily cope with extremely large amounts of data. It is built on top of the HDF5 library and the NumPy package (numarray and Numeric are also supported). PyTables features an object-oriented interface and performance-critical extensions coded in C (generated using Pyrex) that make it a fast yet extremely easy-to-use tool for interactively processing and searching through very large amounts of data. PyTables also optimizes memory and disk resources so that data occupies much less space than with other solutions such as relational or object-oriented databases (especially when compression is used).
PackageMaintainer	neoclust <neoclust>
PackageName	python3-tables
PackageRelease	1.mga9
PackageVersion	3.7.0
SHA-1	8B4E8FE0D62B1914E90B0EB706DB818C4D25FFEE
SHA-256	2E709179F16BC5E82AF4802DEAC8C9BA05FEE517D653EFE90F25C91E145813D5

Key	Value
MD5	2E10F6332E5E5DFAE4A61DA604F8AECB
PackageArch	i586
PackageDescription	PyTables is a package for managing hierarchical datasets and designed to efficently cope with extremely large amounts of data. PyTables is built on top of the HDF5 library and the NumPy package and features an object-oriented interface that, combined with C-code generated from Pyrex sources, makes of it a fast, yet extremely easy to use tool for interactively save and retrieve large amounts of data.
PackageName	python39-tables
PackageRelease	19.1
PackageVersion	3.7.0
SHA-1	D478C202C39308B2C2DFA7EA47BFB648865C68F1
SHA-256	3E9253E4F54D77A76BB0549B94AC6E40A9925327178D3BF21E2B1DA2640929C5

Key	Value
MD5	DB946D4371F87FDC0C02162DBAF93763
PackageArch	x86_64
PackageDescription	PyTables is a package for managing hierarchical datasets and designed to efficently cope with extremely large amounts of data. PyTables is built on top of the HDF5 library and the NumPy package and features an object-oriented interface that, combined with C-code generated from Pyrex sources, makes of it a fast, yet extremely easy to use tool for interactively save and retrieve large amounts of data.
PackageName	python310-tables
PackageRelease	19.1
PackageVersion	3.7.0
SHA-1	FD7DCDE376A19E635EF99AE217E683E83AE99C91
SHA-256	2110EB55EBDC8C192B43E5CD4CF6D30DA685DD0BE056DB57F0587DD0DC75FFFC

Key	Value
MD5	7496F4EE4DC943D43C55AAB605A376E2
PackageArch	i586
PackageDescription	PyTables is a package for managing hierarchical datasets and designed to efficently cope with extremely large amounts of data. PyTables is built on top of the HDF5 library and the NumPy package and features an object-oriented interface that, combined with C-code generated from Pyrex sources, makes of it a fast, yet extremely easy to use tool for interactively save and retrieve large amounts of data.
PackageName	python310-tables
PackageRelease	19.1
PackageVersion	3.7.0
SHA-1	1EF3B9ADAAA627EA36C39692FF67F95623167CBF
SHA-256	A6634E11251292A10CAD9D1A670E46B1F7705A2BFB74C80C843B835F79AB279C

Key	Value
MD5	9E65A7E425EA5B2EA644CC941589B36E
PackageArch	i586
PackageDescription	PyTables is a Python 3 package for managing hierarchical datasets designed to efficiently and easily cope with extremely large amounts of data. It is built on top of the HDF5 library and the NumPy package (numarray and Numeric are also supported). PyTables features an object-oriented interface and performance-critical extensions coded in C (generated using Pyrex) that make it a fast yet extremely easy-to-use tool for interactively processing and searching through very large amounts of data. PyTables also optimizes memory and disk resources so that data occupies much less space than with other solutions such as relational or object-oriented databases (especially when compression is used).
PackageMaintainer	neoclust <neoclust>
PackageName	python3-tables
PackageRelease	1.mga9
PackageVersion	3.7.0
SHA-1	A9358EA92C760EFD97F289CD9C539BD43105EF94
SHA-256	AE978244F890C930897BBEA6503860B91BFB74859910BEAD3EAE9CBBEF4870B4

Key	Value
MD5	AB7B34D5024AD081AC5FC507D624B8C9
PackageArch	x86_64
PackageDescription	PyTables is a package for managing hierarchical datasets and designed to efficently cope with extremely large amounts of data. PyTables is built on top of the HDF5 library and the NumPy package and features an object-oriented interface that, combined with C-code generated from Pyrex sources, makes of it a fast, yet extremely easy to use tool for interactively save and retrieve large amounts of data.
PackageName	python38-tables
PackageRelease	19.1
PackageVersion	3.7.0
SHA-1	0C74B2021084218CA8BA3362877D58B5FFF979C0
SHA-256	079C0DC3DFB2A2E4BE99F435CC7D4033A3253E8B96E5DB38D872EEF5319B9B99

Key	Value
MD5	73206ECFEAE06A7D46E7FAAB26C6DF49
PackageArch	x86_64
PackageDescription	PyTables is a package for managing hierarchical datasets and designed to efficently cope with extremely large amounts of data. PyTables is built on top of the HDF5 library and the NumPy package and features an object-oriented interface that, combined with C-code generated from Pyrex sources, makes of it a fast, yet extremely easy to use tool for interactively save and retrieve large amounts of data.
PackageName	python39-tables
PackageRelease	19.1
PackageVersion	3.7.0
SHA-1	5DFC91EA440C1018B6396BC3FE96170E2299B81B
SHA-256	A50D5E176F0E203147DF9073A17035CB75FAB88E58647934D75AACC4202D28F3

Key	Value
MD5	A0203C81DF5FEFB421CB62DDFD0EF415
PackageArch	i586
PackageDescription	PyTables is a package for managing hierarchical datasets and designed to efficently cope with extremely large amounts of data. PyTables is built on top of the HDF5 library and the NumPy package and features an object-oriented interface that, combined with C-code generated from Pyrex sources, makes of it a fast, yet extremely easy to use tool for interactively save and retrieve large amounts of data.
PackageName	python38-tables
PackageRelease	19.1
PackageVersion	3.7.0
SHA-1	D93B647FBE5650DE44A0B5B7BFC74C62878C0E13
SHA-256	64141769F8EC61828980A3691C6A03A151466D99B4EEC223EFA91DABEDD1A36A

Key	Value
MD5	B526966DF455CFB075548F8CD20AC233
PackageArch	x86_64
PackageDescription	PyTables is a Python 3 package for managing hierarchical datasets designed to efficiently and easily cope with extremely large amounts of data. It is built on top of the HDF5 library and the NumPy package (numarray and Numeric are also supported). PyTables features an object-oriented interface and performance-critical extensions coded in C (generated using Pyrex) that make it a fast yet extremely easy-to-use tool for interactively processing and searching through very large amounts of data. PyTables also optimizes memory and disk resources so that data occupies much less space than with other solutions such as relational or object-oriented databases (especially when compression is used).
PackageMaintainer	neoclust <neoclust>
PackageName	python3-tables
PackageRelease	1.mga9
PackageVersion	3.7.0
SHA-1	9973423C3CB1CE0F5ABE7558C0639516FA896D66
SHA-256	53F1D43D71702BA4F92989D18CD774F50AE0BE2EC7F1A0C996D34E56F2E4BC63

Key	Value
MD5	2A193B60AC43562A91B7502A3139825B
PackageArch	armv7hl
PackageDescription	PyTables is a package for managing hierarchical datasets and designed to efficently cope with extremely large amounts of data. PyTables is built on top of the HDF5 library and the NumPy package and features an object-oriented interface that, combined with C-code generated from Pyrex sources, makes of it a fast, yet extremely easy to use tool for interactively save and retrieve large amounts of data.
PackageName	python38-tables
PackageRelease	19.1
PackageVersion	3.7.0
SHA-1	E98A9911DEC1E261007AC7F157A8B4842924956D
SHA-256	A413187E642CD4AECE31055967F2A02F5301063E60C16AD090AA9A89556DC463