Production-grade, practitioner-focused guides for building command-line tools and batch-processing pipelines for geospatial workflows in Python.
Modern geospatial work demands more than ad-hoc scripts. Whether you're reprojecting thousands of raster tiles, wiring up an internal GIS toolchain, or packaging a reusable spatial utility, this site gives you the architecture patterns, runnable code, and production-hardening techniques to ship tools that scale.
Every guide is written for working practitioners — Python GIS developers, DevOps engineers, and open-source maintainers — with complete, copy-pasteable implementations that use real geospatial types (rasterio windows, GeoDataFrames, explicit EPSG codes) and explain the reasoning behind each decision.
50+ in-depth guides across two areas:
Argument parsing with Typer & Click, subcommand organisation, Rich console output and progress bars, layered configuration (TOML / YAML / environment variables), environment variable sync, and packaging & CI/CD for the notoriously fragile GDAL stack.
Async I/O for raster processing, multiprocessing GDAL tasks, chunked vector reading with pyogrio, memory management for terabyte-scale datasets, fault-tolerant error handling (dead-letter queues, retries), and progress tracking for long-running batch jobs.
- Python GIS developers building or maintaining spatial command-line tools
- DevOps & platform engineers running geospatial pipelines in CI/CD and Kubernetes
- Open-source maintainers packaging reusable geospatial utilities
- Internal tooling teams standardising on reproducible spatial workflows
- Complete, runnable Python — no pseudocode; real GDAL, rasterio, geopandas, and pyogrio
- Decision guides for the high-stakes calls — multiprocessing vs asyncio, pyogrio vs Fiona
- Hand-authored diagrams, structured FAQs, and a consistent, accessible design in light and dark themes
This repository contains the source for batch-processing.com — a static site built with Eleventy and deployed on Cloudflare Workers (Static Assets).
npm install # install dependencies
npm run build # build the static site into ./_site
npm start # local dev server with live reload
npm run deploy # build and deploy the Cloudflare WorkerMaintained by batch-processing-geospatial-cli-tools.