Parents (Total: 5)

The searched file hash is included in 5 parent files which include package known and seen by metalookup. A sample is included below:

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
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
FileSize	333056
MD5	2B2226589988FD60B5B2E686C067086F
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	3.6.1-2build1
SHA-1	0D3518EA19BB9AD4BBCF1CD496729422749D08ED
SHA-256	046787334FDEFAD19E5D857A7501023981480C1449F8E780A2EED97AB017C7F2

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
FileSize	333060
MD5	889E28061C30DABBD05BEA250DB059A1
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	3.6.1-2build2
SHA-1	C488DB7160667C5FD095F7B3F66009EAA35060E9
SHA-256	A57DDFA86E002A59E7A9769048F63E02436901392D308193C83A69DBB437FAA6