1Bibliography
2============
3
4.. _HDFG1:
5
6:ref:`[HDFG1] <HDFG1>`
7    The HDF Group. What is HDF5?. Concise description about HDF5 capabilities
8    and its differences from earlier versions (HDF4).
9    `<http://www.hdfgroup.org/HDF5/whatishdf5.html>`_.
10
11.. _HDFG2:
12
13:ref:`[HDFG2] <HDFG2>`
14    The HDF Group. Introduction to HDF5. Introduction to the HDF5 data model
15    and programming model. `<http://www.hdfgroup.org/HDF5/doc/H5.intro.html>`_.
16
17.. _HDFG3:
18
19:ref:`[HDFG3] <HDFG3>`
20    The HDF Group. The HDF5 table programming model. Examples on using HDF5
21    tables with the C API. `<http://www.hdfgroup.org/HDF5/Tutor/h5table.html>`_.
22
23.. _MERTZ:
24
25:ref:`[MERTZ] <MERTZ>`
26    David Mertz. Objectify. On the 'Pythonic' treatment of XML documents as
27    objects(II). Article describing XML Objectify, a Python module that
28    allows working with XML documents as Python objects.
29    Some of the ideas presented here are used in PyTables.
30    `<http://gnosis.cx/publish/programming/xml_matters_2.html>`_.
31
32.. _CYTHON:
33
34:ref:`[CYTHON] <CYTHON>`
35    Stefan Behnel, Robert Bradshaw, Dag Sverre Seljebotn, and Greg Ewing.
36    Cython. A language that makes writing C extensions for the Python
37    language as easy as Python itself. `<http://www.cython.org>`_.
38
39.. _NUMPY:
40
41:ref:`[NUMPY] <NUMPY>`
42    Travis Oliphant and et al. NumPy. Scientific Computing with Numerical
43    Python. The latest and most powerful re-implementation of Numeric to
44    date.
45    It implements all the features that can be found in Numeric and numarray,
46    plus a bunch of new others. In general, it is more efficient as well.
47    `<http://www.numpy.org>`_.
48
49.. _NUMEXPR:
50
51:ref:`[NUMEXPR] <NUMEXPR>`
52    David Cooke, Francesc Alted, and et al. Numexpr. Fast evaluation of array
53    expressions by using a vector-based virtual machine.
54    It is an enhaced computing kernel that is generally faster (between 1x
55    and 10x, depending on the kind of operations) than NumPy at evaluating
56    complex array expressions. `<http://code.google.com/p/numexpr>`_.
57
58.. _ZLIB:
59
60:ref:`[ZLIB] <ZLIB>`
61    JeanLoup Gailly and Mark Adler. zlib. A Massively Spiffy Yet Delicately
62    Unobtrusive Compression Library. A standard library for compression
63    purposes. `<http://www.gzip.org/zlib/>`_.
64
65.. _LZO:
66
67:ref:`[LZO] <LZO>`
68    Markus F Oberhumer. LZO. A data compression library which is suitable for
69    data de-/compression in real-time. It offers pretty fast compression and
70    decompression with reasonable compression ratio.
71    `<http://www.oberhumer.com/opensource/>`_.
72
73.. _BZIP2:
74
75:ref:`[BZIP2] <BZIP2>`
76    Julian Seward. bzip2. A high performance lossless compressor.
77    It offers very high compression ratios within reasonable times.
78    `<http://www.bzip.org/>`_.
79
80.. _BLOSC:
81
82:ref:`[BLOSC] <BLOSC>`
83    Francesc Alted. Blosc. A blocking, shuffling and loss-less compression
84    library.  A compressor designed to transmit data from memory to CPU
85    (and back) faster than a plain memcpy().
86    `<http://www.blosc.org/>`_.
87
88.. _GNUWIN32:
89
90:ref:`[GNUWIN32] <GNUWIN32>`
91    Alexis Wilke, Jerry S., Kees Zeelenberg, and Mathias Michaelis.
92    GnuWin32. GNU (and other) tools ported to Win32.
93    GnuWin32 provides native Win32-versions of GNU tools, or tools with a
94    similar open source licence.
95    `<http://gnuwin32.sourceforge.net/>`_.
96
97.. _PSYCO:
98
99:ref:`[PSYCO] <PSYCO>`
100    Armin Rigo. Psyco. A Python specializing compiler.
101    Run existing Python software faster, with no change in your source.
102    `<http://psyco.sourceforge.net>`_.
103
104.. _SCIPY1:
105
106:ref:`[SCIPY1] <SCIPY1>`
107    Konrad Hinsen. Scientific Python. Collection of Python modules useful for
108    scientific computing.
109    `<http://dirac.cnrs-orleans.fr/ScientificPython>`_.
110
111.. _SCIPY2:
112
113:ref:`[SCIPY2] <SCIPY2>`
114    Eric Jones, Travis Oliphant, Pearu Peterson, and et al. SciPy.
115    Scientific tools for Python. SciPy supplements the popular Numeric module,
116    gathering a variety of high level science and engineering modules
117    together as a single package.
118    `<http://www.scipy.org>`_.
119
120.. _OPTIM:
121
122:ref:`[OPTIM] <OPTIM>`
123    Francesc Alted and Ivan Vilata. Optimization of file openings in PyTables.
124    This document explores the savings of the opening process in terms of
125    both CPU time and memory, due to the adoption of a LRU cache for the
126    nodes in the object tree.
127    `<http://www.pytables.org/docs/NewObjectTreeCache.pdf>`_.
128
129.. _OPSI:
130
131:ref:`[OPSI] <OPSI>`
132    Francesc Alted and Ivan Vilata. OPSI: The indexing system of PyTables 2
133    Professional Edition. Exhaustive description and benchmarks about the
134    indexing engine that comes with PyTables Pro.
135    `<http://www.pytables.org/docs/OPSI-indexes.pdf>`_.
136
137.. _VITABLES:
138
139:ref:`[VITABLES] <VITABLES>`
140    Vicent Mas. ViTables. A GUI for PyTables/HDF5 files.
141    It is a graphical tool for browsing and editing files in both PyTables
142    and HDF5 formats.
143    `<http://vitables.org>`_.
144
145.. _GIT:
146
147:ref:`[GIT] <GIT>`
148    Git is a free and open source, distributed version control system designed
149    to handle everything from small to very large projects with speed and
150    efficiency `<http://git-scm.com>`_.
151
152.. _SPHINX:
153
154:ref:`[SPHINX] <SPHINX>`
155    Sphinx is a tool that makes it easy to create intelligent and beautiful
156    documentation, written by Georg Brandl and licensed under the BSD license
157    `<http://sphinx-doc.org>`_.
158
159.. |Kuepper| unicode:: K U+00FC pper .. Kuepper
160
161.. todo:: remove the above substitution. It is no more needed with sphinx
162          1.0.8
163