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<div class="section" id="what-s-new-in-pytables-0-9">
<h1>What’s new in PyTables 0.9<a class="headerlink" href="#what-s-new-in-pytables-0-9" title="Permalink to this headline">¶</a></h1>
<p>On this release you will find a series of quite
exciting new features, being the most important the indexing
capabilities, in-kernel selections, support for complex datatypes and
the possibility to modify values in both tables <em>and</em> arrays (yeah,
finally :).</p>
<div class="section" id="new-features">
<h2>New features:<a class="headerlink" href="#new-features" title="Permalink to this headline">¶</a></h2>
<ul class="simple">
<li>Indexing of columns in tables. That allow to make data selections on
tables up to 500 times faster than standard selections (for
ex. doing a selection along an indexed column of 100 milion of rows
takes less than 1 second on a modern CPU). Perhaps the most
interesting thing about the indexing algorithm implemented by
PyTables is that the time taken to index grows <em>lineraly</em> with the
length of the data, so, making the indexation process to be
<em>scalable</em> (quite differently to many relational databases). This
means that it can index, in a relatively quick way, arbitrarily
large table columns (for ex. indexing a column of 100 milion of rows
takes just 100 seconds, i.e. at a rate of 1 Mrow/sec). See more
detailed info about that in <a class="reference external" href="http://www.pytables.org/docs/SciPy04.pdf">http://www.pytables.org/docs/SciPy04.pdf</a>.</li>
<li>In-kernel selections. This feature allow to make data selections on
tables up to 5 times faster than standard selections (i.e. pre-0.9
selections), without a need to create an index. As a hint of how
fast these selections can be, they are up to 10 times faster than a
traditional relational database. Again, see
<a class="reference external" href="http://www.pytables.org/docs/SciPy04.pdf">http://www.pytables.org/docs/SciPy04.pdf</a> for some experiments on that
matter.</li>
<li>Support of complex datatypes for all the data objects (i.e. Table,
Array, EArray and VLArray). With that, the complete set of datatypes
of Numeric and numarray packages are supported. Thanks to Tom Hedley
for providing the patches for Array, EArray and VLArray objects, as
well as updating the User’s Manual and adding unit tests for the new
functionality.</li>
<li>Modification of values. You can modifiy Table, Array, EArray and
VLArray values. See Table.modifyRows, Table.modifyColumns() and the
newly introduced __setitem__() method for Table, Array, EArray and
VLArray entities in the Library Reference of User’s Manual.</li>
<li>A new sub-package called “nodes” is there. On it, there will be
included different modules to make more easy working with different
entities (like images, files, ...). The first module that has been
added to this sub-package is “FileNode”, whose mission is to enable
the creation of a database of nodes which can be used like regular
opened files in Python. In other words, you can store a set of
files in a PyTables database, and read and write it as you would do
with any other file in Python. Thanks to Ivan Vilata i Balaguer for
contributing this.</li>
</ul>
</div>
<div class="section" id="improvements">
<h2>Improvements:<a class="headerlink" href="#improvements" title="Permalink to this headline">¶</a></h2>
<ul class="simple">
<li>New __len__(self) methods added in Arrays, Tables and Columns. This,
in combination with __getitem__(self,key) allows to better emulate
sequences.</li>
<li>Better capabilities to import generic HDF5 files. In particular,
Table objects (in the HDF5_HL naming schema) with “holes” in their
compound type definition are supported. That allows to read certain
files produced by NASA (thanks to Stephen Walton for reporting this).</li>
<li>Much improved test units. More than 2000 different tests has been
implemented which accounts for more than 13000 loc (this represents
twice of the PyTables library code itself (!)).</li>
</ul>
</div>
<div class="section" id="backward-incompatible-api-changes">
<h2>Backward-incompatible API changes:<a class="headerlink" href="#backward-incompatible-api-changes" title="Permalink to this headline">¶</a></h2>
<ul class="simple">
<li>The __call__ special method has been removed from objects File,
Group, Table, Array, EArray and VLArray. Now, you should use
walkNodes() in File and Group and iterrows in Table, Array, EArray
and VLArray to get the same functionality. This would provide better
compatibility with IPython as well.</li>
</ul>
<p>‘nctoh5’, a new importing utility:</p>
<ul class="simple">
<li>Jeff Whitaker has contributed a script to easily convert NetCDF
files into HDF5 files using Scientific Python and PyTables. It has
been included and documented as a new utility.</li>
</ul>
</div>
<div class="section" id="bug-fixes">
<h2>Bug fixes:<a class="headerlink" href="#bug-fixes" title="Permalink to this headline">¶</a></h2>
<ul class="simple">
<li>A call to File.flush() now invoke a call to H5Fflush() so to
effectively flushing all the file contents to disk. Thanks to Shack
Toms for reporting this and providing a patch.</li>
<li>SF #1054683: Security hole in utils.checkNameValidity(). Reported in
2004-10-26 by ivilata</li>
<li>SF #1049297: Suggestion: new method File.delAttrNode(). Reported in
2004-10-18 by ivilata</li>
<li>SF #1049285: Leak in AttributeSet.__delattr__(). Reported in
2004-10-18 by ivilata</li>
<li>SF #1014298: Wrong method call in examples/tutorial1-2.py. Reported
in 2004-08-23 by ivilata</li>
<li>SF #1013202: Cryptic error appending to EArray on RO file. Reported
in 2004-08-21 by ivilata</li>
<li>SF #991715: Table.read(field=”var1”, flavor=”List”) fails. Reported
in 2004-07-15 by falted</li>
<li>SF #988547: Wrong file type assumption in File.__new__. Reported in
2004-07-10 by ivilata</li>
</ul>
<p>Bon profit!,</p>
<p>– Francesc Altet
<a class="reference external" href="mailto:falted%40pytables.org">falted<span>@</span>pytables<span>.</span>org</a></p>
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<h3><a href="../index.html">Table Of Contents</a></h3>
<ul>
<li><a class="reference internal" href="#">What’s new in PyTables 0.9</a><ul>
<li><a class="reference internal" href="#new-features">New features:</a></li>
<li><a class="reference internal" href="#improvements">Improvements:</a></li>
<li><a class="reference internal" href="#backward-incompatible-api-changes">Backward-incompatible API changes:</a></li>
<li><a class="reference internal" href="#bug-fixes">Bug fixes:</a></li>
</ul>
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