Python and HDF5 (2013)
Chapter 10. Next Steps
Now that you have a firm introduction to HDF5, it’s up to you to put that knowledge to use! Here are some resources to help you on your way.
Asking for Help
The Python community is very open, and this extends to users of h5py, NumPy, and SciPy. Don’t be afraid to ask for help on the h5py (firstname.lastname@example.org), NumPy (email@example.com), or SciPy (firstname.lastname@example.org) mailing lists. Stack Overflow is also a great place to ask specific technical questions if you’re getting started with the NumPy world.
You can find technical documentation for h5py, including API reference material, at www.h5py.org. The HDF Group’s website also has an extensive reference manual and user guide (from a C programmer’s perspective).
If you’re working on an “application” of HDF5, like EOS5, get in touch with that community for more information on how files are structured. For general questions on HDF5 (as opposed to h5py or Python), you can post to the HDF Group’s public forum at email@example.com. The HDF Group can also be reached directly for bug reports, technical questions, and so on at firstname.lastname@example.org.
Finally, if you’re craving more information on using Python for scientific coding, Python for Data Analysis (McKinney, 2012) is a great place to start. Tutorials and reference materials are also available on the SciPy website for those seeking a quick introduction to analysis in Python, or just looking for the fft function.
As you continue to use HDF5, you may occasionally have a bug to report or a feature request. Both the h5py and PyTables projects are on GitHub and welcome user bug reports and features. Using the git revision control system and GitHub’s “pull requests” feature, you can even contribute code directly to the projects. Read more about how to contribute at www.h5py.org.