Python progression path for GIS professionals

Over last years, I was working with Python almost full time either scripting some desktop GIS workflows or developing code for the back-end geoprocessing services using arcpy. I learned all kinds of Python packages, everything from data science packages such as pandas and numpy to more widely applicable ones such as xlsxwriter and reportlab. Being able to find a package and start using it producing the outputs needed in a matter of minutes is one of the key selling points of Python, I think.

However, due to the presence of such a large number of resources that are related to Python (just check this repository on GitHub – A curated list of awesome Python frameworks, libraries, software and resources)- one might feel a bit lost. There are so many things to learn, which are the most important ones? It also makes things a bit more complicated for niche developers or GIS analysts who do Python programming just occasionally. I have also experienced frustration being unable to identify the key competence areas to focus on and how to track my progress. Am I learning Python packages that are relevant for geospatial operations? What else should I learn after I’ve managed a certain feature of the language or a framework?

The result of this thought process is a public repository on GitHub which I am working on. It’s called Progression path for a GIS analyst who wants to become proficient in using Python for GIS: from apprentice to guru which is inspired partially by the awesome-python and partially by a SO post Python progression path – From apprentice to guru.

This is an attempt to provide a structured collection of resources that could help a GIS professional to learn how to use Python when working with spatial data management, mapping, and analysis. The resources are organized by progress category so basically everyone should be able to learn something new along the way. The resources will include books, web pages and blog posts, online courses, videos, Q/A from GIS.SE, links to code snippets, and some bedtime readings.

Be sure to check this one out, pick a topic of interest and start working on it. Also, feel free to star the repository if you have a GitHub account 🙂

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