3360eb6c5f
Former-commit-id:9f19e3f712[formerly 64fa9254b946eae7e61bbc3f513b7c3696c4f54f] Former-commit-id:06a8b51d6d
100 lines
3.2 KiB
Text
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100 lines
3.2 KiB
Text
Executable file
HDF5 for Python (h5py) 1.3.0 BETA
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=================================
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I'm pleased to announce that HDF5 for Python 1.3 is now available! This
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is a significant release introducing a number of new features, including
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support for soft/external links as well as object and region references.
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I encourage all interested HDF5/NumPy/Python users to give the beta a try
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and to do your best to break it. :) Download, documentation and contact
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links are below.
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What is h5py?
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-------------
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HDF5 for Python (h5py) is a general-purpose Python interface to the
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Hierarchical Data Format library, version 5. HDF5 is a mature scientific
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software library originally developed at NCSA, designed for the fast,
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flexible storage of enormous amounts of data.
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From a Python programmer's perspective, HDF5 provides a robust way to
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store data, organized by name in a tree-like fashion. You can create
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datasets (arrays on disk) hundreds of gigabytes in size, and perform
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random-access I/O on desired sections. Datasets are organized in a
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filesystem-like hierarchy using containers called "groups", and
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accesed using the tradional POSIX /path/to/resource syntax.
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In addition to providing interoperability with existing HDF5 datasets
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and platforms, h5py is a convienient way to store and retrieve
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arbitrary NumPy data and metadata.
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HDF5 datasets and groups are presented as "array-like" and "dictionary-like"
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objects in order to make best use of existing experience. For example,
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dataset I/O is done with NumPy-style slicing, and group access is via
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indexing with string keys. Standard Python exceptions (KeyError, etc) are
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raised in response to underlying HDF5 errors.
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New features in 1.3
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-------------------
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- Full support for soft and external links
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- Full support for object and region references, in all contexts (datasets,
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attributes, etc). Region references can be created using the standard
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NumPy slicing syntax.
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- A new get() method for HDF5 groups, which also allows the type of an
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object or link to be queried without first opening it.
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- Improved locking system which makes h5py faster in both multi-threaded and
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single-threaded applications.
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- Automatic creation of missing intermediate groups (HDF5 1.8)
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- Anonymous group and dataset creation (HDF5 1.8)
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- Option to enable cProfile support for the parts of h5py written in Cython
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- Many bug fixes and performance enhancements
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Other changes
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-------------
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- Old-style dictionary methods (listobjects, etc) will now issue
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DeprecationWarning, and will be removed in 1.4.
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- Dataset .value attribute is deprecated. Use dataset[...] or dataset[()].
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- new_vlen(), get_vlen(), new_enum() and get_enum() are deprecated in favor
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of the functions h5py.special_dtype() and h5py.check_dtype(), which also
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support reference types.
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Where to get it
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---------------
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* Main website, documentation: http://h5py.alfven.org
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* Downloads, bug tracker: http://h5py.googlecode.com
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* Mailing list (discussion and development): h5py at googlegroups.com
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* Contact email: h5py at alfven.org
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Requires
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--------
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* Linux, Mac OS-X or Windows
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* Python 2.5 or 2.6
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* NumPy 1.0.3 or later
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* HDF5 1.6.5 or later (including 1.8); HDF5 is included with
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the Windows version.
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