A new and improved version of OntoSpy (1.6.7) is available online. OntoSpy is a lightweight Python library and command-line tool for inspecting and visualizing vocabularies encoded in the RDF family of languages.

This update includes support for Python 3, plus various other improvements that make it easier to query semantic web vocabularies using OntoSpy's interactive shell module. To find out more about OntoSpy, here are a few good places to start:

• Official documentation: http://ontospy.readthedocs.org
• PyPI (CheeseShop): https://pypi.python.org/pypi/ontospy
• GitHub: https://github.com/lambdamusic/ontospy

Here's a short video showing a typical session with the OntoSpy REPL:

What's new in this release

The main new features of version 1.6.7:

• Added support for Python 3.0 (thanks to a pull request from https://github.com/T-002)
• The import command: this makes it easier to load models into the local repository. You can import a local RDF file or a web resource via its URI. The repo option allows you to select an ontology by listing those available in a couple of online public repositories. Finally, the starter-pack option can be used to automatically download a few widely used vocabularies (e.g., FOAF, DC, etc.) into the local repository - mostly useful after a fresh installation to get started
• The info command allows you to print more detailed information about entities
• Added an incremental search mode based on text patterns, e.g., to reduce the options returned by the ls command
• Calling the serialize command at the ontology level now serializes the whole graph
• Made the caching functionality version-dependent
• Added JSON serialization option (via rdflib-jsonld)

Install or update OntoSpy simply by typing pip install ontospy -U in your terminal window (see this page for more information).

What's next

• I'd really like to add more output visualizations, e.g., VivaGraphJS or one of the JavaScript InfoVis Toolkit options.
• Probably even more interesting, I'd like to refactor the code generating visualizations so that it allows people to develop their own via a standard API and then publish them on GitHub.
• Lastly, more support for instance management: querying and creating instances from any loaded ontology.

Stay tuned for more!