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Old 12-30-2010, 11:30 AM   #1
LXer
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LXer: Tips & Tricks on MySQL for Python


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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Old 12-30-2010, 11:52 AM   #2
Kenny_Strawn
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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.
 
Old 12-30-2010, 12:00 PM   #3
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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.
 
Old 12-30-2010, 12:06 PM   #4
Kenny_Strawn
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Isn't Genie easy to use?
 
Old 12-30-2010, 12:14 PM   #5
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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.

Last edited by dugan; 12-30-2010 at 12:31 PM.
 
  


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