If anyone would be willing to test this out, it may be a worthwhile upgrade. My reading of the release notes is that there are no backwards-incompatible changes.
---------- Forwarded message ---------- From: Andrew Collette email@example.com Date: Thu, Oct 4, 2012 at 8:20 AM Subject: ANN: HDF5 for Python (h5py) 2.1.0-final To: SciPy Users List firstname.lastname@example.org, email@example.com, firstname.lastname@example.org, email@example.com
Announcing HDF5 for Python (h5py) 2.1.0 =======================================
We are proud to announce the availability of HDF5 for Python (h5py) 2.1.0! This release has been a long time coming. Thanks to everyone who contributed code and filed bug reports!
What's new in h5py 2.1 -----------------------
* The HDF5 Dimension Scales API is now available, along with high-level integration with Dataset objects. Thanks to D. Dale for implementing this.
* Unicode scalar strings can now be stored in attributes.
* Dataset objects now expose a .size property giving the total number of elements.
* Many performance improvements and bug fixes
About the project -----------------------
HDF5 for Python (h5py) is a general-purpose Python interface to the Hierarchical Data Format library, version 5. HDF5 is a mature scientific software library originally developed at NCSA, designed for the fast, flexible storage of enormous amounts of data.
From a Python programmer's perspective, HDF5 provides a robust way to
store data, organized by name in a tree-like fashion. You can create datasets (arrays on disk) hundreds of gigabytes in size, and perform random-access I/O on desired sections. Datasets are organized in a filesystem-like hierarchy using containers called "groups", and accessed using the traditional POSIX /path/to/resource syntax.
Downloads, FAQ and bug tracker are available at Google Code:
* Google code site: http://h5py.googlecode.com
Documentation is available at Alfven.org:
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