Below you will find pages that utilize the taxonomy term “Zope”
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Storm 0.13
Yesterday, Thomas rolled the 0.13 release of Storm, which can be downloaded from Launchpad. Storm is the object relational mapper for Python used by Launchpad and Landscape, so it is capable of supporting quite large scale applications. It is seven months since the last release, so there is a lot of improvements. Here are a few simple statistics:
0.12 | 0.13 | Change | |
---|---|---|---|
Tarball size (KB) | 117 | 155 | 38 |
Mainline revisions | 213 | 262 | 49 |
Revisions in ancestry | 552 | 875 | 323 |
So it is a fairly significant update by any of these metrics. Among the new features are:
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Using Storm with Django
I've been playing around with Django a bit for work recently, which has been interesting to see what choices they've made differently to Zope 3. There were a few things that surprised me:
- The ORM and database layer defaults to autocommit mode rather than using transactions. This seems like an odd choice given that all the major free databases support transactions these days. While autocommit might work fine when a web application is under light use, it is a recipe for problems at higher loads. By using transactions that last for the duration of the request, the testing you do is more likely to help with the high load situations.
- While there is a middleware class to enable request-duration transactions, it only covers the database connection. There is no global transaction manager to coordinate multiple DB connections or other resources.
- The ORM appears to only support a single connection for a request. While this is the most common case and should be easy to code with, allowing an application to expand past this limit seems prudent.
- The tutorial promotes schema generation from Python models, which I feel is the wrong choice for any application that is likely to evolve over time (i.e. pretty much every application). I've written about this previously and believe that migration based schema management is a more workable solution.
- It poorly reinvents thread local storage in a few places. This isn't too surprising for things that existed prior to Python 2.4, and probably isn't a problem for its default mode of operation.
Other than these things I've noticed so far, it looks like a nice framework.