Andrew Collette holds a Ph.D. in physics from UCLA, and works as a laboratory research scientist at the University of Colorado. He has worked with the Python-NumPy-HDF5 stack at two multimillion-dollar research facilities; the first being the Large Plasma Device at UCLA (entirely standardized on HDF5), and the second being the hypervelocity dust accelerator at the Colorado Center for Lunar Dust and Atmospheric Studies, University of Colorado at Boulder. Additionally, Dr. Collette is a leading developer of the HDF5 for Python (h5py) project.
Most people working on complex software systems have had That Moment, when you throw up your hands and say “If only we could start from scratch!” Generally, it’s not possible. But every now and then, the chance comes along to build a … read more
Webcast: Managing Large Datasets with Python and HDF5 January 28, 2014
Are you using Python to process large numerical datasets? Over the past few years, the Hierarchical Data Format (HDF5) has emerged as the mechanism of choice for processing, archiving and sharing scientific datasets ranging from gigabytes to terabytes...