We are proud to announce the availability of HDF REST Server (h5serv) 0.1.0!
The HDF REST Server project page is located here:
HDF REST Server is a Python-based web service that can be used to send and
receive HDF5 data using an HTTP-based REST interface. HDF Server supports CRUD
(create, read, update, delete) operations on the full spectrum of HDF5 objects
including: groups, links, datasets, attributes, and committed data types. As a
and other common languages.
The HDF Server extends the HDF5 data model to efficiently store large data
objects (e.g. up to multi-TB data arrays) and access them over the web using a
RESTful API. As datasets get larger and larger, it becomes impractical to
download files to access data. Using HDF Server, data can be kept in one
central location and content vended via well-defined URIs. This enables
exploration and analysis of the data while minimizing the number of bytes that
need to be transmitted over the network.
Since HDF Server supports both reading and writing of data, it enables some
interesting scenarios such as:
Collaborative annotation of data sets
Compute clusters that use HDF Server for data access
Continually updated data shares (e.g. Stock Market quotes, sensor data)
Storing the analysis of the data (say a visualization) with the original
In addition to these, we would like to hear your ideas of how HDF Server could
be utilized (as well as any other feedback you might have).
Thanks to everyone who helped and advised on this project.