broot vs. h5py vs. python-sql vs. zope.interface Comparison Chart

The h5py package is a Pythonic interface to the HDF5 binary data format. It lets you store huge amounts of numerical data, and easily manipulate that data from NumPy. For example, you can slice into multi-terabyte datasets stored on disk, as if they were real NumPy arrays. Thousands of datasets can be stored in a single file, categorized and tagged however you want. H5py uses straightforward NumPy and Python metaphors, like dictionary and NumPy array syntax. For example, you can iterate over datasets in a file, or check out the .shape or .dtype attributes of datasets. You don't need to know anything special about HDF5 to get started. In addition to the easy-to-use high level interface, h5py rests on a object-oriented Cython wrapping of the HDF5 C API. Almost anything you can do from C in HDF5, you can do from h5py.

This package is intended to be independently reusable in any Python project. It is maintained by the Zope Toolkit project. This package provides an implementation of “object interfaces” for Python. Interfaces are a mechanism for labeling objects as conforming to a given API or contract. So, this package can be considered as an implementation of the Design By Contract methodology support in Python. Interfaces are objects that specify (document) the external behavior of objects that “provide” them. An interface specifies behavior through informal documentation in a doc string, attribute definitions, and invariants, which are conditions that must hold for objects that provide the interface. Attribute definitions specify specific attributes. They define the attribute name and provide documentation and constraints of attribute values. Attribute definitions can take a number of forms.