Yes my sense is that battle is lost. However there is often an advantage in 
knowing a different toolset from the masses.

I'd be interested to hear you expand on your comments Doug as to why PDL is 
technically superior. I guess you are referring to the threading? I don't know 
much about scipy though I gather it has something like that? Maybe we should 
have a document on PDL's unique features.

Python has a lot of organisational support - in astronomy for example the 
Hubble Space Telescope folks are supporting it among others. That's a lot of 
warm bodies writing docs, cookbooks and click-2-install procedures. And there 
is also enthought doing the same sort of stuff. 

Here's a joke I like - what's the collective noun for a group of python 
programmers?


Karl


On 31/12/2013, at 6:46 AM, Craig DeForest <[email protected]> wrote:

> 
> Yes, these are the perennial issues.  A decade ago I marketed PDL pretty hard 
> in the solar physics community but the installation process at that time was 
> pretty difficult and that limited adoption. More recently, people are 
> migrating to Python within that community.  Numpy seems to have achieved 
> critical mass early on, in part because of the faster learning curve for the 
> underlying language.  (That's unfortunate since, as far as I can see, it is 
> *still* technically inferior to PDL...)
> 
> As near as I can tell the battle for widespread adoption/dominance has been 
> lost ever since Python became the de facto standard for introductory 
> programming courses -- there's just too much inertia (and too much anti-Perl 
> propaganda) steering new graduates in the direction of Numpy and Python.  
> That's not to say PDL is doomed -- It is technically superior and I continue 
> to exploit that routinely to get great science done.  And we do seem to have 
> a large and still-growing user base.
> 
> But I believe that PDL will remain a market underdog for the foreseeable 
> future, at least for interactive scientific computing.  
> 


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