HDF5 for Python¶
The h5py package is a Pythonic interface to the HDF5 binary data format.
HDF5 is an open-source library and file format for storing large amounts of numerical data, originally developed at NCSA. It is widely used in the scientific community for everything from NASA’s Earth Observing System to the storage of data from laboratory experiments and simulations. Over the past few years, HDF5 has rapidly emerged as the de-facto standard technology in Python to store large numerical datasets.
This is the reference documentation for the h5py package. Check out the Quick Start Guide if you’re new to h5py and HDF5.
The lead author of h5py, Andrew Collette, also wrote an O’Reilly book which provides a comprehensive, example-based introduction to using Python and HDF5 together.
Tutorial and reference documentation is available here at http://docs.h5py.org. We also have a mailing list at Google Groups. Anyone is welcome to post; the list is read by both users and the core developers of h5py.
High-level API reference¶
- HDF5 File Objects
- HDF5 Groups
- HDF5 Datasets
- HDF5 Attributes
- HDF5 Dimension Scales
- Configuring h5py
- Special types
- Strings in HDF5
- Object and Region References
- Parallel HDF5
- Single Writer Multiple Reader (SWMR)
Meta-info about the h5py project¶
- “What’s new” documents
- Bug Reports & Contributions
- What datatypes are supported?
- What compression/processing filters are supported?
- What file drivers are available?
- What’s the difference between h5py and PyTables?
- Does h5py support Parallel HDF5?
- Variable-length (VLEN) data
- Enumerated types
- NumPy object types
- Appending data to a dataset
- Licenses and legal info