============== Other Material ============== Videos ====== These are the videos of a series dedicated to introduce the main features of PyTables in a visual and easy to grasp manner. More videos will be made available with the time: * `HDF5 is for Lovers, SciPy 2012 Tutorial `_: a beginner's introduction to PyTables and HDF5. Presentations ============= Here are the slides of some presentations about PyTables that you may find useful: * HDF5 is for Lovers, SciPy 2012 Tutorial, July 2012, Austin, TX, USA, `slides (pdf) `_, `video `_, `exercises `_, `solutions `_, and `repository `_. * `An on-disk binary data container `_. Talk given at the `Austin Python Meetup `_, Austin, TX, USA (May 2012). * `Large Data Analysis with Python `_. Seminar given at the `German Neuroinformatics Node `_, Munich, Germany (November 2010). * `Starving CPUs (and coping with that in PyTables) `_. Seminar given at `FOM Institute for Plasma Physics Rijnhuizen `_, The Netherlands (September 2009). * `On The Data Access Issue (or Why Modern CPUs Are Starving) `_. Keynote presented at `EuroSciPy 2009 `_ conference in Leipzig, Germany (July 2009). * `An Overview of Future Improvements to OPSI `_. Informal talk given at the `THG headquarters `_ in Urbana-Champaign, Illinois, USA (October 2007). * `Finding Needles in a Huge DataStack `_. Talk given at the **EuroPython 2006 Conference**, held at CERN, Genève, Switzerland (July 2006). * `Presentation given at the "HDF Workshop 2005" `_, held at San Francisco, USA (December 2005). * `I `_ and `II `_ **Workshop in Free Software and Scientific Computing** given at the Universitat Jaume I, Castelló, Spain (October 2004). In Catalan. * `Presentation given at the "SciPy Workshop 2004" `_, held at Caltech, Pasadena, USA (September 2004). * `Slides `_ of presentation given at **EuroPython Conference** in Charleroi, Belgium (June 2003). * `Presentation for the "iParty5" `_ held at Castelló, Spain (May 2003). In Spanish. * `Talk `_ on PyTables given at the **PyCon 2003 Convention** held at Washington, USA (March 203). Reports ======= * White Paper on `OPSI indexes `_, explaining the powerful new indexing engine in PyTables Pro. * `Performance study `_ on how the new object tree cache introduced in PyTables 1.2 can accelerate the opening of files with a large number of objects, while being quite less memory hungry. * `Paper version `_ of the presentation at PyCon2003. Other sources for examples ========================== The examples presented above show just a little amount of the full capabilities of PyTables. Please check out the documentation and the :file:`examples/` directory in the source package for more examples.