Python and HDF5

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Pre-build h5py can either be installed via your Python Distribution e. Skip to content.

HDF5 for FEA: A Standard for High Performance and Enterprise Integration

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  • Python & HDF5 - A Vision - The HDF Group;
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Add github issue template. Apr 2, Sep 19, Sep 25, Sep 20, New data models can be added by the HDF developers or users. HDF is self-describing, allowing an application to interpret the structure and contents of a file with no outside information. One HDF file can hold a mix of related objects which can be accessed as a group or as individual objects.

Users can create their own grouping structures called "vgroups. The HDF4 format has many limitations. Supporting many different interface styles images, tables, arrays leads to a complex API.

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Support for metadata depends on which interface is in use; SD Scientific Dataset objects support arbitrary named attributes, while other types only support predefined metadata. Perhaps most importantly, the use of bit signed integers for addressing limits HDF4 files to a maximum of 2 GB, which is unacceptable in many modern scientific applications. The HDF5 format is designed to address some of the limitations of the HDF4 library, and to address current and anticipated requirements of modern systems and applications.

This results in a truly hierarchical, filesystem-like data format. Metadata is stored in the form of user-defined, named attributes attached to groups and datasets. More complex storage APIs representing images and tables can then be built up using datasets, groups and attributes.

In addition to these advances in the file format, HDF5 includes an improved type system, and dataspace objects which represent selections over dataset regions.

Python and HDF5 - O'Reilly Media

The API is also object-oriented with respect to datasets, groups, attributes, types, dataspaces and property lists. Because it uses B-trees to index table objects, HDF5 works well for time series data such as stock price series, network monitoring data, and 3D meteorological data. The bulk of the data goes into straightforward arrays the table objects that can be accessed much more quickly than the rows of an SQL database, but B-tree access is available for non-array data.