H3 Hierarchy and Compaction: Multi-Resolution Spatial Analysis
Master H3's parent-child cell relationships and compaction algorithm for efficient spatial data representation
Every H3 hexagon at any resolution is the parent of exactly seven children at the next finer resolution. This seven-to-one relationship makes H3 uniquely powerful for multi-scale analysis — and its compaction algorithm exploits it to compress spatial datasets dramatically.
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H3 Catchment Analysis: Modelling Service Areas with Hexagonal Grids
Use H3's k-ring and grid distance functions to build precise spatial buffers and accessibility zones
Traditional circular buffers distort space and ignore real-world geometry. H3's hexagonal rings give you scale-consistent spatial catchments that work the same way across the entire Earth's surface.
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H3 Density Mapping: Visualising Urban Point Data as Hexagonal Heatmaps
Transform scattered coordinates into meaningful density patterns using H3's spatial aggregation
Raw GPS coordinates are noisy, overwhelming, and hard to interpret at scale. H3's hexagonal grid transforms thousands of points into clear, legible density maps — and the core aggregation logic fits in under ten lines.
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Streaming LLM API Responses in Python: A Complete Production Guide
Handle token-by-token output, implement back-pressure, manage rate limits, and build fault-tolerant wrappers around OpenAI-compatible APIs
Streaming is the difference between an AI product that feels fast and one that feels slow. Instead of waiting 10–30 seconds for a completed response, a streaming API delivers each token as it is generated. This post covers the full picture: HTTP server-sent events, Python async generators, rate limit handling, and building a robust wrapper you can drop into a production application.
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How to Use Rust and WebAssembly for Real-Time Data Processing in the Browser
Compile performance-critical Rust logic to WASM and run it at near-native speed inside any modern web browser — no server round-trip, no bottleneck
WebAssembly finally makes it practical to run genuinely fast computation inside a browser tab. When you combine it with Rust — a language designed around zero-cost abstractions and memory safety — you get a pipeline that can process tens of thousands of records per frame without blocking the UI thread. This post walks through the full workflow: writing the Rust crate, compiling to WASM, and wiring it into a JavaScript frontend.
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Building High-Throughput Spatial Pipelines with Go Concurrency
Using goroutines, channels, and context cancellation to process millions of geospatial records in parallel
Go's concurrency primitives are among the most ergonomic in any systems language. This post shows how to put goroutines and channels to work on a real problem: processing large spatial datasets at speed.
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Location-Aware Search with Elasticsearch Geo Queries
Combining full-text relevance with geo_distance, bounding box filtering, and spatial decay scoring
Elasticsearch's geospatial capabilities let you ask questions that pure text search cannot answer: not just 'find documents about coffee' but 'find the most relevant coffee shop within 500 metres of where I am standing, weighted by recency and rating'. This post walks through how to build that kind of query from first principles.
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Building a Geospatial REST API with FastAPI and PostGIS
A complete walkthrough of a production-ready spatial data API: routing, geometry serialisation, spatial queries, and GeoJSON responses
FastAPI's async-first design and automatic OpenAPI documentation make it an excellent choice for geospatial APIs. Combined with PostGIS for spatial queries and GeoAlchemy2 for the ORM layer, you can build a fully-featured location API in a few hundred lines of Python.
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Spatial ETL Pipelines with GeoPandas and Shapely
Building robust, reproducible geospatial data transformation workflows entirely in Python
Most geospatial data arrives dirty: mismatched projections, broken geometries, inconsistent attribute schemas. GeoPandas and Shapely give you a powerful, Pythonic toolkit for cleaning, transforming, and enriching spatial data before it reaches your database or analysis pipeline.
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Getting Started with H3: The Hexagonal Grid System for Spatial Analysis
A practical tutorial for understanding and implementing Uber's H3 hexagonal grid system
Why are Uber, Foursquare, and every major location intelligence company switching to hexagonal grids? This tutorial will teach you H3 fundamentals with interactive examples you can run in your browser.
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Designing a New Website and Blog
An overview of my new academic portfolio website architecture, explaining the design considerations and organisation.
Over the past couple of months I have been re-designing and building a new online portfolio for my work. This article will explore my design choices and experience in developing jwilliams.science.
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