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In the previous post we have seen an introduction to FeatureServer, and we were just playing with the base edit sample, with the scribble layer.
Now it is time to use FeatureServer with our datasets: I am assuming that you will want to create FeatureServer services for shapefiles, PostGis layers, OpenStreetMap, Twitter and Flickr.

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…well, this is the solution to your problems (at least I hope so).

I am continuing receiving emails from people in despair that cannot successfully use this tutorial. I am sorry but I cannot answer to all this emails, so I thought to write this post in order to allow people to configure it correctly.

BTW, this demo is still working since 2 years without any problems, and the code there is just the same you can download from this blog. So it must work also for you

So if you just cannot use it, this is a check list:

If you receive the "Unable to load dll (mapscript)" error, look at this article from Tamas Szekeres (the mapscript c# mantainer).

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Some friends already spoke me well about FeatureServer by MetaCarta in the last weeks, so I already was waiting for having a bit of time to get started with it. Then James posted this on his blog, and my curiosity was definitely fired.

So I decided to spend a day for installing and testing it, without thinking of the lack of documentation (FeatureServer is still a young project, so no wonder here if the only way to get infos is digging in the source code and posting to the mailing list). The day I considered to spend on it then spawned to more and more hours that I could imagine, and given my actually very busy schedule at my job, I had to find free hours during the night and the weekend. I then decided to write this post to help people in getting started with FeatureServer in a quicker way that was for me.

FeatureServer is a simple and powerfull RESTful-Pythonic WFS server.
Only from this last sentence there are 3 very important things that made me like (and you should - also) FeatureServer before even getting started with it:

• Its RESTful architecture
• It is written in Python, and having chosen Plone as our CMS here at my office I am starting to like this language very much
• I truly believe that WFS is the way to go for remotely editing GIS data

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In the last post I showed you a configuration for serving Ruby on Rails applications with Mongrel cluster and Apache in a *nix environment (Ubuntu).
With this post I will reproduce the same configuration in a Windows environment.

The main difference in Windows is that you cannot use the mongrel_rails command with the cluster option (provided by the mongrel_cluster gem) that relies on daemonize functionality, only available on *nix platforms.
What you will need to do is to manually create n mongrel services for the n clusters you will need. Let's see how to do that.

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