Published at LXer:

Python is a dynamic programming language, which is completely enterprise ready, owing largely to the variety of support modules that are available to extend its capabilities. In order to build productive and feature-rich Python applications, we need to use MySQL for Python, a module that provides database support to our applications. In this article, we will have a look at the tips and tricks presented thru-ought on MySQL for Python.

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The problem with Python is that it's interpreted, which means that there's extra CPU overhead with Python apps -- just look at Ubuntu Software Center for instance: On my Acer netbook, it takes about ~10 seconds to load, which is about the same amount of time it takes Ubuntu to boot! Most C-based programs load in less than 1 second.

The kind of language I would really feel is a good compromise between Python, Java, C#, and C is Vala, which is multi-paradigm and close to Java in syntax but compiles first to C and then to native code, no different ABI or interpretation needed.

I think the problem here is that most people care more about language ease-of-use than load/runtime speed, hence the interpreted, "dynamic" languages like Python, Perl(?), etc. win out over compiled languages.

Isn't Genie easy to use?

Kenny, one reason I wrote my MPD client in Python and not C++ was because I knew it wouldn't have made a shred of difference in terms of execution speed.

Furthermore, the article is talking about writing code to connect to a database. That means that the speed bottleneck is going to be waiting for the database, not the execution speed of the program's instructions.