Skip to Main Content
University of Texas University of Texas Libraries

GIS & Geospatial Data Services

Standalone Python Scripting GIS


Using Python to script GIS workflows has several advantages:

  • It allows for reproducible and broadly shareable analyses
  • Users can use Python's advanced compatibility with file systems, networks, web scraping, and automation.
  • The open-source nature of Python means that new libraries and updates are constantly being added, and users can become contributors 

Python is a fundamental scripting language in GIS and is known to GIS users as the chosen scripting language for ArcGIS and QGIS. Experienced GIS users likely know of the ArcPy and PyQGIS Python libraries, but there are a growing number of standalone GIS libraries in Python.

Users can take advantage of these libraries for a wide range of use cases ranging from efficient data acquisition to full-analysis workflows utilizing vector and raster data, in which case Python's powerful machine learning and visualization capabilities can be leveraged. 


The following Python example scripts can get you started:

 The scripts are hosted on Google Colab. If you are new to using Colab you access information here:

Example Python GIS Packages

GeoPandas working with vector-based geospatial data

GDAL a translator library for a wide variety of raster and vector data formats. 

PyProj interface to the PROJ cartographic projections and coordinate transformations library.

PySAL provides tools for spatial data analysis 

RSGISLib the Remote Sensing and GIS Software library for working with remote sensing and imagery data.

Open streetmap (OSMNX) a library to work with the Open street maps dataset and produce street networks

Rasterio working with raster data

GeoWombat working with multiband imagery

Other Useful resources and tutorials




Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 Generic License.