Package: python3-tables-dbg
Source: pytables
Version: 3.6.1-2build1
Architecture: amd64
Maintainer: Ubuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
Original-Maintainer: Debian Science Maintainers <debian-science-maintainers@lists.alioth.debian.org>
Installed-Size: 12679
Depends: python3-dbg (<< 3.9), python3-dbg (>= 3.8~), python3-numpy (>= 1:1.16.0~rc1), python3-numpy-abi9, libblosc1 (>= 1.17.1+ds1), libbz2-1.0, libc6 (>= 2.14), libhdf5-103, liblzo2-2 (>= 2.02), python3-numpy-dbg, python3-numexpr-dbg, python3-tables (= 3.6.1-2build1), python3-tables-lib (= 3.6.1-2build1)
Suggests: python3-netcdf4, python-tables-doc
Section: debug
Priority: optional
Homepage: https://www.pytables.org
Description: hierarchical database for Python 3 based on HDF5 (debug 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 debug interpreter.
Build-Ids: 06e8d0148ad9ea69cdff1b1ec94b6a8d7ea6dbdb 2a200fac1ffe3a96672486b56e5a1dc78e858ce2 396c40c062872988df10f651fa950da4e7a20525 483517a36a0069a26ebd0b378f8082a3b99eceb5 9757f5937c03484871137d4c906f7ff188ddc7a5 a3c072dd68608d82ded37c7511086650b1fea1eb bd9a03d77a04bbd8c153a869f47ed18063ca3ac8 df9810b5eca21d829b4921ccddc8aebac754c59e
