Last weekend I spent some time with the rest of the Neo4j team at Neo Technology for our Code Camp weekend. Among the things I worked on was our Python bindings for Neo4j. They obviously work with the recently released Jython 2.5, but also fairly well with CPython 2.5 (or later), with the current caveat that you have to install JPype on your own (I am working on replacing JPype with something that is maintained and more light weight, and works with Python 3.x). I also want these Python bindings to work with the previous version of Jython (2.2), for those who for some reason cannot update. So for the first time in a while I used a version of Jython that was not the very latest. This is my summary of that experience.
When comparing Jython 2.5 with Jython 2.2 it suddenly becomes obvious how much work the Jython team (including myself) have put into making this a fully compatible implementation of the Python programming language. The fact that Jython now runs Django, Pylons, SQLAlchemy, and a ton of other things is genuinely impressive. And I am more than a little proud for the part I played in making this happen, even if it was only a small part. Jython has, with the step from 2.2 to 2.5, graduated from being a system for scripting Java applications with Python to a system on which you can build full applications.
The first thing I missed when testing Neo4j with Jython 2.2 was virtualenv. I run so many different unstable applications and libraries on different versions of Python and Jython that it's inevitable to mess up on a daily basis. A lot of these have different dependencies, and dependencies on conflicting versions of the same thing and other horrible constraints. And of course I patch and rebuild my Jython at the same time as well, meaning that all libraries I've installed directly into the Jython dist directory gets wiped (I've lost a lot of work this way). In all these situations virtualenv is a saving angel, and it doesn't work with Jython 2.2. (If you have not tried virtualenv yet, do so now! I was a late user, but it was love at first use.) This is a pain - Upgrade to Jython 2.5.
The second thing I was screaming after in Jython < 2.5 was of course easy-install. If not for any other reason to install virtualenv. How about distutils? - Nope. Jython 2.2 has no pleasant way of installing libraries for you - you are on your own. Fail. The same is true for the Python bindings for Neo4j, if you use Jython 2.2 it will still download the required Java libraries for you, and you will be able to use it, but installing it into your
sys.path is up to you. This is a pain - Upgrade to Jython 2.5.
I lied before. The first thing I missed was the Python 2.5 syntax. In particular the with statement. This was in fact the reason I joined the Jython project in the first place, to get Python 2.5 syntax support for Jython (and I succeeded in prototyping it during that first Google Summer of Code in 2007). Just consider the following two pieces of code, and I think you will get my point:
with neo.transaction: with_node = neo.node(language="Python", feature="with statement") example__node = neo.node(language="Python", example="Using the with statement") example_node.USES(with_node)
tx = neo.transaction.begin() try: try: try_node = neo.node(language="Python", feature="try block") example__node = neo.node(language="Python", example="Not using the with statement") example_node.USES(try_node) except: tx.failure() raise else: tx.success() finally: tx.finish()
It should be obvious which one is beautiful and which one is not. The with statement is one nice piece of syntactic sugar. Not having it is a pain - Upgrade to Jython 2.5.
Ok, so there is still a lot of work to be done on Jython. Mainly on performance. The focus up until now has been compatibility, and we've done a good job at that. In the next major version of Jython you should expect a substantial improvement of performance. Not that performance is bad now. But we know that we can do better. More on that in a later post.