Ubuntu
pytables package

pytables 3.7.0-3 source package in Ubuntu

Changelog

pytables (3.7.0-3) unstable; urgency=medium

  * Fix documentation build (Closes: #1009459).

 -- Antonio Valentino <email address hidden>  Thu, 14 Apr 2022 06:39:28 +0000

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Uploaded by:
Debian Science Team
Uploaded to:
Sid
Original maintainer:
Debian Science Team
Architectures:
any all
Section:
python
Urgency:
Medium Urgency

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File Size SHA-256 Checksum
pytables_3.7.0-3.dsc 2.7 KiB 7f392b1a7bb3d2236cb5850eb34c1ff85cd984432a76ebc130bffc606e3ddc18
pytables_3.7.0.orig.tar.gz 3.4 MiB 41065fc11b958dde09bd5b9c069d88e40ca07ad10687dd597835fcc8199e81ea
pytables_3.7.0-3.debian.tar.xz 18.3 KiB c1228141f1792e717f1d7a46eea194e927bde8891f7da123a45709be4be165c2

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Binary packages built by this source

python-tables-data: No summary available for python-tables-data in ubuntu kinetic.

No description available for python-tables-data in ubuntu kinetic.

python-tables-doc: No summary available for python-tables-doc in ubuntu kinetic.

No description available for python-tables-doc in ubuntu kinetic.

python3-tables: 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.

python3-tables-lib: hierarchical database for Python3 based on HDF5 (extension)

 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 package contains the extension built for the Python 3 interpreter.

python3-tables-lib-dbgsym: debug symbols for python3-tables-lib