At work the functional test suite of our application used up quite a lot of RAM (over 500 megs). For a long time it was cheaper to buy the developers an extra gig of RAM than to spend time hunting down a possible memory leak, but finally curiosity overcame me and I started investigating.
Sometimes even good programmers at their first tries of Python use less than optimal solutions and language constructs. In the years Python has accumulated few redundancies and few warts (and some of them will be removed with Python 3.0), but it's a generally clean language still, so with a page like this you can avoid the most common ones. This page hopes to be really simple and short enough, you can find explanations online elsewhere.
This article explains the new features in Python 3.0, compared to 2.6. Python 3.0, also known as “Python 3000” or “Py3K”, is the first ever intentionally backwards incompatible Python release. There are more changes than in a typical release, and more that are important for all Python users. Nevertheless, after digesting the changes, you’ll find that Python really hasn’t changed all that much – by and large, we’re mostly fixing well-known annoyances and warts, and removing a lot of old cruft.
If you’d like to just get the executive summary, here it is: Please, for the love of Guido, stop using setuptools and easy_install, and use distutils and pip instead. If you’d like to know why, re
Guido van Rossum blogs "a series of articles on the history of the Python programming language and its community" aside of his personal blog. Today: Python's Design Philosophy. (via dlat)
What design patterns are applicable to Python? Some patterns are an intrinsic part of Python, other patterns require some careful coding to get the best from them. What new patterns appear in Python?
"I found the Google translate is pretty cool. I would like to use it to translate some text from my computer in batch(in script). Do you know any way that I could use it easily from shell?" And here we go...
"I was reading David Cramer's tip to use JSONField in Django to be able to store arbitrary fields in a SQL database. Nice. But is it fast enough? Well, I can't answer that but I did look into the difference in read/write performance between simplejson, cPickle and marshal."
The Computer Language Benchmarks Game is a collection of 429 programs, consisting of 13 benchmark reimplemented across 33 programming languages. It is a fantastic resource if you are trying to compare programming languages quantitatively. Which, oddly, very few people seems to be interested in doing.
"Dive Into Python 3 covers Python 3 and its differences from Python 2. Compared to Dive Into Python, it’s about 20% revised and 80% new material. I am publishing drafts online as I go. Please send feedback. The final version will be published on paper by Apress. The book will remain online under the CC-BY-SA-3.0 license."
