A huge portion of the geospatial Python community have undoubtedly come by way of using ArcGIS, the leading Geographic Information System software, and its extremely convenient and easy-to-use geoprocessing/arcpy Python library that comes packaged with all its installations. But as ArcGIS Python users complete their education or change their workplace, they often end up losing access to ArcGIS, and with their newfound love for Python programming are left wanting a similar easy-to-use geospatial library. Unfortunately there are no obvious replacements.
It’s not that there are no open-source oppurtunities for geospatial Python programming, there are many and they are quite advanced. It’s just that they might just be a bit too advanced. The spatial extensions that are available are usually meant as low-level building blocks for the more experienced developers and as such require quite a bit of expertise and effort to link these together and do something useful. So for the purposes of everyday geospatial analysis by the more casual programmers, Python is just not there yet.
However, given the many tools available it shouldn’t be too difficult to make a library to serve as an open-source equivalent of Arcpy. And so I decided to create The Python-GIS Challenge, a set of related projects and steps in order to ultimately build a more fully comprehensive, integrated, and easy-to-use open-source Python platform for GIS analysis, for analysts and developers alike. As I complete each step or part of the system I will provide them here on the website so others can download them.
The Python-GIS Challenge 