On Wednesday, January 7, 2015 12:56:29 PM UTC-8, Devin Jeanpierre wrote: [snip]
> If you never run model directly, and only ever import it or run it as > my_svr.model, then you will be fine, and pickles will all serialize > and deserialize the same way. Thank you Devin... I re-ran TrainingSession from within ipython, and everything worked the way I hoped. I obtained an SVRModel object which I could pickle to disk, and unpickle in a subsequent session. I don't actually need to run the test code that I appended to training.py any more, so I won't. [snip] > P.S. don't use pickle, it is a security vulnerability equivalent in > severity to using exec in your code, and an unversioned opaque > schemaless blob that is very difficult to work with when circumstances > change. For all of its shortcomings, I can't live without pickle. In this case, I am doing data mining. My TrainingSession class commandeers seven CPU cores via Multiprocessing.Pool. Still, even my "toy" TrainingSessions take several minutes to run. I can't afford to re-run TrainingSession every time I need my models. I need a persistent object. Besides, the opportunity for mischief is low. My code is for my own personal use. And I trust the third-party libraries that I am using. My SVRModel object wraps the NuSVR object from scikit-learn, which in turn wraps the libsvm binary. > > try: > > from model import * > > from sampling import * > > except ImportError: > > from .model import * > > from .sampling import * > > > > > > This bothers me. I don't know whether it is correct usage. I don't know > > whether it is causing my remaining ImportError problem. > > This is a symptom of the differing ways you are importing these > modules, as above. If you only ever run them and import them as > my_svr.blahblah, then only the second set of imports are necessary. OK, I will try refactoring the import code at some point. > I hope that resolves all your questions! I think so, thanks. -- https://mail.python.org/mailman/listinfo/python-list
