pytables 2.1.2-3.1ubuntu0.11.04.1 source package in Ubuntu

Changelog

pytables (2.1.2-3.1ubuntu0.11.04.1) natty-proposed; urgency=low

  * debian/rules: fix dh_shlibdeps call to fill dependencies
    correctly (LP: #863248)
    - dependency on lzo2 required to import tables
 -- Julian Taylor <email address hidden>   Tue, 28 Feb 2012 21:51:06 +0100

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Uploaded by:
Julian Taylor on 2012-03-03
Uploaded to:
Natty
Original maintainer:
Ubuntu Developers
Architectures:
any
Section:
python
Urgency:
Low Urgency

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File Size SHA-256 Checksum
pytables_2.1.2.orig.tar.gz 4.5 MiB 948d80fb66693bca67863c4a7dc879dae1d6caa4235df0030ca0cc3220cffa39
pytables_2.1.2-3.1ubuntu0.11.04.1.diff.gz 11.8 KiB 68b7a0ddb8e55ae28ffc5d633d4018042ef665c700c61be671062dba17025e28
pytables_2.1.2-3.1ubuntu0.11.04.1.dsc 1.9 KiB 7bad742420dad130a8ce252c4771fef0f276625314199d8fc28e55ed3326879f

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Binary packages built by this source

python-tables: hierarchical database for Python based on HDF5

 PyTables is a hierarchical database package designed to efficently
 manage very large amounts of data. PyTables is built on top of the
 HDF5 library and the NumPy package. It features an object-oriented
 interface that, combined with natural naming and C-code generated
 from Pyrex sources, makes it a fast, yet extremely easy to use tool
 for interactively save and retrieve large amounts of data.
 .
  - 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, Numeric and numarray objects.

python-tables-doc: hierarchical database for Python based on HDF5 - documentation

 PyTables is a hierarchical database package designed to efficently
 manage very large amounts of data. PyTables is built on top of the
 HDF5 library and the NumPy package. It features an object-oriented
 interface that, combined with natural naming and C-code generated
 from Pyrex sources, makes it a fast, yet extremely easy to use tool
 for interactively save and retrieve large amounts of data.
 .
 This package includes the manual in PDF and HTML formats.