Parents (Total: 12)

The searched file hash is included in 12 parent files which include package known and seen by metalookup. A sample is included below:

Key	Value
MD5	A0DBF63D32C9D033CEB0726A4CCA2D19
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	umeabot <umeabot>
PackageName	python3-tables
PackageRelease	4.mga9
PackageVersion	3.6.1
SHA-1	8CDF8AED4224E5E4120C6984F76CCE9AD7AF328E
SHA-256	AC735D50EDD77E30EAC94184726D9D95B4C75C118BD3EAC4A4FFFDE3817E9DD8

Key	Value
FileSize	342296
MD5	2FCE94F4BB77C9C0546F1E82B6979272
PackageDescription	hierarchical database for Python3 based on HDF5 PyTables is a package for managing hierarchical datasets and designed to efficiently cope with extremely large amounts of data. . It is built on top of the HDF5 library and the NumPy package. It features an object-oriented interface that, combined with C extensions for the performance-critical parts of the code (generated using Cython), makes it a fast, yet extremely easy to use tool for interactively save and retrieve very large amounts of data. One important feature of PyTables is that it optimizes memory and disk resources so that they take much less space (between a factor 3 to 5, and more if the data is compressible) than other solutions, like for example, relational or object oriented databases. . - Compound types (records) can be used entirely from Python (i.e. it is not necessary to use C for taking advantage of them). - The tables are both enlargeable and compressible. - I/O is buffered, so you can get very fast I/O, specially with large tables. - Very easy to select data through the use of iterators over the rows in tables. Extended slicing is supported as well. - It supports the complete set of NumPy objects. . This is the Python 3 version of the package.
PackageMaintainer	Debian Science Maintainers <debian-science-maintainers@lists.alioth.debian.org>
PackageName	python3-tables
PackageSection	python
PackageVersion	3.6.1-5
SHA-1	40E7996FE4B444345174A99EDD476D771194DD8A
SHA-256	2A5252E6DDBEE11192957E64E21EA156A0D6CDC2AE988F33330F4A25F8E3D0A9

Key	Value
MD5	E9461CB18FFFE98010AEC190EACBF995
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	python3-tables
PackageRelease	lp153.5.1
PackageVersion	3.6.1
SHA-1	4C4F1E5CE9B2CFFC560FEB902B2F20FAD8F57632
SHA-256	6CBA36CC430D3A70FDE50E2A0490E0958A27704D5C9A1BF8B9BFE88B20B75760

Key	Value
MD5	15F0F79DB800C765DA3F27C8912E9EE8
PackageArch	aarch64
PackageDescription	PyTables is a package for managing hierarchical datasets and designed to efficiently and easily cope with extremely large amounts of data.
PackageMaintainer	Fedora Project
PackageName	python3-tables
PackageRelease	2.fc34
PackageVersion	3.6.1
SHA-1	5CD0189C8A4EF16D29AB831ABCA1E852BB37E29F
SHA-256	B25D28212A54A6DA773ACBC3507E61488FD9EE504A3967C53CD97EBAD1DEE7A5

Key	Value
FileSize	333208
MD5	6E75946C4169859023EB2DD7A92129B7
PackageDescription	hierarchical database for Python3 based on HDF5 PyTables is a package for managing hierarchical datasets and designed to efficiently cope with extremely large amounts of data. . It is built on top of the HDF5 library and the NumPy package. It features an object-oriented interface that, combined with C extensions for the performance-critical parts of the code (generated using Cython), makes it a fast, yet extremely easy to use tool for interactively save and retrieve very large amounts of data. One important feature of PyTables is that it optimizes memory and disk resources so that they take much less space (between a factor 3 to 5, and more if the data is compressible) than other solutions, like for example, relational or object oriented databases. . - Compound types (records) can be used entirely from Python (i.e. it is not necessary to use C for taking advantage of them). - The tables are both enlargeable and compressible. - I/O is buffered, so you can get very fast I/O, specially with large tables. - Very easy to select data through the use of iterators over the rows in tables. Extended slicing is supported as well. - It supports the complete set of NumPy objects. . This is the Python 3 version of the package.
PackageMaintainer	Ubuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageName	python3-tables
PackageSection	python
PackageVersion	3.6.1-3
SHA-1	A28E0AB1E9B95390BB606132A467E737A4050D5D
SHA-256	6397C2420D916F0679420F4606BBFC32F9859506F0A7912A5019380255D79B8F

Key	Value
MD5	36010726F2A74A57F242ED9F08E0AE85
PackageArch	armv7hl
PackageDescription	PyTables is a package for managing hierarchical datasets and designed to efficiently and easily cope with extremely large amounts of data.
PackageMaintainer	Fedora Project
PackageName	python3-tables
PackageRelease	2.fc34
PackageVersion	3.6.1
SHA-1	EF3F5345BBC793949C0577585DC2040DDD08CA83
SHA-256	005140716D55DBC08DBFB4950210FAA98BF64EEB97E0813188A88966C5D18437

Key	Value
MD5	4BE71675913ADABB2FF9070381528FDD
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	umeabot <umeabot>
PackageName	python3-tables
PackageRelease	4.mga9
PackageVersion	3.6.1
SHA-1	ACB50FEE5D29A7425D538A19B63EFDAB992B8433
SHA-256	AA90587DBC1E1636BBB4F39190A916D992AAA4FF88F4D04E6E34A5AF22ECE3F3

Key	Value
MD5	B40D53495C26EF6787093906413059BB
PackageArch	x86_64
PackageDescription	PyTables is a package for managing hierarchical datasets and designed to efficiently and easily cope with extremely large amounts of data.
PackageMaintainer	Fedora Project
PackageName	python3-tables
PackageRelease	2.fc34
PackageVersion	3.6.1
SHA-1	8DD79CA5BD9FCC0DF03BABF791051B2AD35B936E
SHA-256	9CC079FCD60A6B02EF7E25843E677DC98D7F0748333872C4A0C05FFA361EDC7F

Key	Value
MD5	5ABEA1172699A4AFA085B0E3DB080407
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	python3-tables
PackageRelease	lp154.5.1
PackageVersion	3.6.1
SHA-1	DC35185E81252F70AC9478158E901DD49196EC5A
SHA-256	EC7EF03EDCFBB4E2C7842B3F2F12CE66D9BCB24FC45A0ECC77148830F14C9077

Key	Value
FileSize	342180
MD5	146BEAE504C21365382A82BC07C371B6
PackageDescription	hierarchical database for Python3 based on HDF5 PyTables is a package for managing hierarchical datasets and designed to efficiently cope with extremely large amounts of data. . It is built on top of the HDF5 library and the NumPy package. It features an object-oriented interface that, combined with C extensions for the performance-critical parts of the code (generated using Cython), makes it a fast, yet extremely easy to use tool for interactively save and retrieve very large amounts of data. One important feature of PyTables is that it optimizes memory and disk resources so that they take much less space (between a factor 3 to 5, and more if the data is compressible) than other solutions, like for example, relational or object oriented databases. . - Compound types (records) can be used entirely from Python (i.e. it is not necessary to use C for taking advantage of them). - The tables are both enlargeable and compressible. - I/O is buffered, so you can get very fast I/O, specially with large tables. - Very easy to select data through the use of iterators over the rows in tables. Extended slicing is supported as well. - It supports the complete set of NumPy objects. . This is the Python 3 version of the package.
PackageMaintainer	Debian Science Maintainers <debian-science-maintainers@lists.alioth.debian.org>
PackageName	python3-tables
PackageSection	python
PackageVersion	3.6.1-3
SHA-1	468337C9CC136E51DB0B1C40235FF489441D325D
SHA-256	C582F06BEC3317B014C40D407B45CD24CDB17C6247EE38C05AEE35DC23E8F674

Key	Value
MD5	151FF3A1C51A2A8B6A0227B3DFC74FA7
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	umeabot <umeabot>
PackageName	python3-tables
PackageRelease	4.mga9
PackageVersion	3.6.1
SHA-1	105B39AC32E6FFA617693034F3874940EC0995B3
SHA-256	9614726E99FF1946623377A8F087117D590807CDF24B0AF14BC77AD70A87C243

Key	Value
MD5	88BA903D237A0A6D4A470054F2D4CB96
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	umeabot <umeabot>
PackageName	python3-tables
PackageRelease	4.mga9
PackageVersion	3.6.1
SHA-1	6E701724A844AEF8A80D93654170AC231BE253AC
SHA-256	6D7899904829BB31ED9D25B3F4F1F1684DB10EAB5963F43CC9722C9E33FB7C18