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
- 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
- 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.