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NOTICE: This version of the NSF Unidata web site (archive.unidata.ucar.edu) is no longer being updated.
Current content can be found at unidata.ucar.edu.
To learn about what's going on, see About the Archive Site.
<div class="socmaildefaultfont" dir="ltr" style="font-family:Arial, Helvetica, sans-serif;font-size:10pt" ><div dir="ltr" ><div>Hello, all!</div> <div> </div> <div>I’m thrilled to announce that a new major release of User-Defined Functions for HDF5 is now available. HDF5-UDF is a tool that allows embedding routines written in C/C++, Python, and Lua on HDF5 files in a way that such routines execute each time the dataset behind that UDF is read.</div> <div> </div> <div>The two highlights of this release are:</div> <div> </div> <div>1. UDF signing: datasets are now signed when saved to HDF5. When a user reads that UDF dataset for the first time, we extract and associate the public key behind that UDF to a trust profile that limits which system calls that UDF can execute – and which file system paths it can access.</div> <div> </div> <div>2. HDF5-UDF is now available as a library and comes with Python bindings that let you write and store UDFs from Jupyter Notebooks and regular Python scripts.</div> <div> </div> <div>Also worth mentioning: we now have a more structured documentation at <a href="https://hdf5-udf.readthedocs.io/en/latest"; >https://hdf5-udf.readthedocs.io/en/latest</a> that should serve as a good landing point. More details about the project along with download pointers and installation instructions can be found on our GitHub page at <a href="https://github.com/lucasvr/hdf5-udf"; >https://github.com/lucasvr/hdf5-udf</a></div> <div> </div> <div>Have fun!</div> <div>Lucas</div></div></div><BR>
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