The soft-links and hard-links are compelling, but I recommend not upgrading as I believe this again introduces API incompatibilities with yt.
---------- Forwarded message ---------- From: Andrew Collette email@example.com Date: Tue, Feb 23, 2010 at 1:45 PM Subject: HDF5 for Python (h5py) 1.3.0 beta To: firstname.lastname@example.org
HDF5 for Python (h5py) 1.3.0 BETA =================================
I'm pleased to announce that HDF5 for Python 1.3 is now available! This is a significant release introducing a number of new features, including support for soft/external links as well as object and region references.
I encourage all interested HDF5/NumPy/Python users to give the beta a try and to do your best to break it. :) Download, documentation and contact links are below.
What is h5py? -------------
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 accesed using the tradional POSIX /path/to/resource syntax.
In addition to providing interoperability with existing HDF5 datasets and platforms, h5py is a convienient way to store and retrieve arbitrary NumPy data and metadata.
HDF5 datasets and groups are presented as "array-like" and "dictionary-like" objects in order to make best use of existing experience. For example, dataset I/O is done with NumPy-style slicing, and group access is via indexing with string keys. Standard Python exceptions (KeyError, etc) are raised in response to underlying HDF5 errors.
New features in 1.3 -------------------
- Full support for soft and external links
- Full support for object and region references, in all contexts (datasets, attributes, etc). Region references can be created using the standard NumPy slicing syntax.
- A new get() method for HDF5 groups, which also allows the type of an object or link to be queried without first opening it.
- Improved locking system which makes h5py faster in both multi-threaded and single-threaded applications.
- Automatic creation of missing intermediate groups (HDF5 1.8)
- Anonymous group and dataset creation (HDF5 1.8)
- Option to enable cProfile support for the parts of h5py written in Cython
- Many bug fixes and performance enhancements
Other changes -------------
- Old-style dictionary methods (listobjects, etc) will now issue DeprecationWarning, and will be removed in 1.4.
- Dataset .value attribute is deprecated. Use dataset[...] or dataset[()].
- new_vlen(), get_vlen(), new_enum() and get_enum() are deprecated in favor of the functions h5py.special_dtype() and h5py.check_dtype(), which also support reference types.
Where to get it ---------------
* Main website, documentation: http://h5py.alfven.org
* Downloads, bug tracker: http://h5py.googlecode.com
* Mailing list (discussion and development): h5py at googlegroups.com
* Contact email: h5py at alfven.org
* Linux, Mac OS-X or Windows
* Python 2.5 or 2.6
* NumPy 1.0.3 or later
* HDF5 1.6.5 or later (including 1.8); HDF5 is included with the Windows version.
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