PyWPS

(Python Web Processing Service) is an implementation of the Web processing Service standard from Open Geospatial Consortium. It offers an environment for programming own processes (geofunctions or models) which can be accessed from the public. The main advantage of PyWPS is, that it has been written with native support for GRASS GIS. Access to GRASS modules via web interface should be as easy as possible.

http://pywps.wald.intevation.org/

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MapFish

MapFish is a flexible and complete framework for building rich web-mapping applications. It emphasizes high productivity, and high-quality development. MapFish extends the Pylons Python web framework with geospatial-specific functionality. For example MapFish provides specific tools for creating web services that allows querying and editing geographic objects.

http://mapfish.org/

GeoPandas

GeoPandas is an open source project to make working with geospatial data in python easier. GeoPandas extends the datatypes used by pandas to allow spatial operations on geometric types. Geometric operations are performed by shapely.

http://geopandas.org/

Status: Actively developed

Depends on: Numpy, Pandas, Shapely, Fiona, six

Optional extensions: GeoPy, Psycopg2, Matplotlib, Descartes, PySAL

Python versions: 2.6, 2.7, 3.2+

OS Platforms: N/A

 

Installation:

Pip

pip install geopandas

Karta

The goals of Karta is to expose a simple and fast framework for spatial analysis. Karta serves as a Leatherman for geographic analyses. It provides simple and clean vector and raster data types, a selection of geographical analysis methods, and the ability to read and write several formats, including GeoJSON, shapefiles, and ESRI ASCII.

http://ironicmtn.com/karta.html

Status: Actively developed

Depends on: Numpy, PyShp, PyProj

Optional extensions: GDAL, SciPy

Python versions: 2.7, 3.3+

OS Platforms: N/A

 

Installation:

Pip

pip install karta

GDAL

This Python package and extensions are a number of tools for programming and manipulating the GDAL Geospatial Data Abstraction Library.

https://pypi.python.org/pypi/GDAL/

Status: Actively developed

Depends on: GDAL C++, Numpy

Optional extensions:

Python versions: 2, 3

OS Platforms: N/A

 

Examples:

Official package examples

https://pcjericks.github.io/py-gdalogr-cookbook/

 

Installation:

Windows binary

http://www.lfd.uci.edu/~gohlke/pythonlibs/#gdal

Commandline

python setup.py install

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