It's no secret that Python has become one of, if not the most popular, programming languages for modern GIS. Beyond geospatial, the demand for Python and the supporting ecosystem has grown and continued to grow in recent years, driven in part by the rise of data science and broader analytics.
Geospatial and modern GIS have seen that wave grow as well. Year over year, core libraries for geospatial Python have grown in terms of downloads and usage. More workflows are using Python, both in a stand-alone workflow and with other core tools like QGIS.
In a recent poll, Python was by and large the winner as the modern GIS language of choice. And this was the result I was expecting for the most part. As modern GIS mostly deals with data and analysis, Python is a natrual choice (or R depending on your background and training).
In a recent poll, Python was by and large the winner as the modern GIS language of choice. And this was the result I was expecting for the most part. As modern GIS mostly deals with data and analysis, Python is a natrual choice (or R depending on your background and training).