Not much news in terms of new libraries nowadays, so just giving a little update on my own projects.
Just wrapped up a new library called PyGeoj that makes it a breeze to read and write geojson as files. By treating geojson as an actual fileformat instead of just as a set of formatting rules, the aim of PyGeoj is to make it just as easy to deal with .geojson files as with .shp files — sort of like the PyShp for Geojson data.
Earlier this summer, I started work on but not yet completed a pure-Python geometry manipulation library called Shapy. Don’t have much time to focus on it at current, so the more people test it out, give feedback, or would consider contributing to it, the better! Leave a reply or email me for more info.
I’ve been wanting to do some changes to the website for a while, and finally got the time.
The changes aren’t drastic, but the front page is now a brief welcome screen explaining what the website is about, instead of the blog post section which might have been confusing for first-time visitors, The blog posts have instead been moved to a “Latest News” page and can now be seen in the right-hand widget area.
The other big change is the category overview page accessible from the top menu. It provides a visual overview of all the categories and links to them, and with each category page now being linked to a thematic graphic.
In terms of the package listings I think it’s gotten to the point that there aren’t many more packages to add. Besides some slight changes and rewordings in the now renamed Web Services category, I have also added an open-source variety of the ESRI spatial index to the Indexing category.
And more recently, today, I finished writing a pure-Python package for QuadTree spatial indexing, as an alternative to PyRtree, which I have added to the Indexing category. Click here to read more about or try it out.
The number and variety in packages listed on this website, as well as the number of visitors, is growing. Thanks to the helpful suggestions and contributions of visitors and package-authors Python GIS Resources is once again updated with several new additions. The following categories have been updated:
- Web Mapping (PyWPS, OWSLib, PyCSW,GeoNode)
- Read/Write (PyShapefile, different from previous one)
- Conversion (Stetl, FastKML, GpxData)
- Indexing (QuadTree, Python-Geohash)
- Spatial Analysis (GeoCoon)
- Visualizing (Kartograph, Heatmap)
- Projections (GeographicLib, UTM)
As well as an entirely new category:
- GeoDatabases (GeoAlchemy, PPyGIS, Python-dbgis, PySpatialite)
I can also mention that I have released version 0.2.0 of my GeoVis visualizing library, which now also supports several map classification algorithms, zooming, text rendering, and point symbolizer icons.
So thanks to all and keep the suggestions coming 🙂
I’ve just added two new categories of Python tools. One is Web GIS, with the following packages: GeoDjango, Mapfish, Papyrus, and Follium. And the other is Conversion, with the following tools: Pygeoif, and Python-Geojson.
I just recently discovered and added to the site some geospatial Python packages that I had never heard of before. Though I have not tested them, and not sure how widely used they are, I thought I would mention that I have added them to their respective categories in case anyone would be interested to learn more about them:
I have always wanted a quick and simple way to view what the outcome of my geoprocessing looked like without having to open a Desktop GIS everytime, and the only alternatives have traditionally been to install Matplotlib and a bunch of other heavy dependencies, spend hours trying to learn them, only to complicate my script with lengthy and confusing syntax that I still don’t quite get (what does it even mean to “add data to an axis”?). All I wanted to do was to view my shapefile.
So as a new addition to our list of resources, I decided to write and just finished and released a new geo-library that does exactly this, the Python Geographic Visualizer (GeoVis). It is lightweight, has no dependencies, and lets you view or save an image of your shapefile with just a single line of code. It is also possible to build a map from scratch and play around with colors and symbols. Read more or try it for yourself by clicking here and you can easily create maps like the one above (though that map was cropped to better fit the post).
There are many extensions for doing spatial analysis in Python, but it is not always easy to find, install, or understand how to use the tool you need. The Python GIS Resources website is here to guide you through the wilderness and help you get the most out of open-source geospatial programming in Python.