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Browse Geocoding Tutorials, Guides & Updates
How to Cache Geocoding Results: TTL, Keys, and 90% Cost Reduction
A million geocoding lookups per month at $0.50 per thousand is $500. With a 90% cache hit rate, that bill drops to $50. With a 95% hit rate it drops to $25. Caching is not a nice-to-have at the bottom of a performance checklist — it is the single largest lever in geocoding economics, and most teams leave it half-pulled. This post is the practical version: cache key design, TTL strategies, the actu...
| May 02, 2026
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Benchmarking Geocoding APIs: Methodology, Pitfalls, and Honest Numbers
"I ran 1,000 addresses through 5 geocoders, here's the winner" is, almost without exception, the wrong methodology. The post that follows will show beautiful charts. The numbers will be precise to two decimals. The conclusion will be confident. And it will be wrong, because at least three load-bearing assumptions in the experiment were never examined. The three assumptions, in order of how much da...
| May 01, 2026
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Geocoding 1 Million Addresses: From 8 Hours to 12 Minutes
A logistics customer ran a nightly geocode of roughly one million delivery addresses. The job started after the 22:00 cutoff for next-day routing and was supposed to finish before drivers logged in at 06:00. For months, it usually did. Then volume crept up, the job started bleeding into the morning, and one bad night it finished at 09:15 — by which point dispatch had already cut routes by hand. Th...
| Apr 30, 2026
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Streaming Geocoding at Scale: Backpressure, Memory, and Throughput
The difference between geocoding 100,000 rows on your laptop and 100,000,000 rows in production is one principle: never load the whole file. Stream it. Backpressure it. Bounded buffers everywhere. Get this wrong and your worker either OOMs at 3am or quietly thrashes the page file at 200 rows per minute. Get it right and the same 1GB worker that crashes on a naive script will chew through a 50GB CS...
By CSV2GEO Team
| Updated Apr 28, 2026
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Python Geocoding API Tutorial: Async, Retries, and a 100K-Row CSV Pipeline
This is a working Python tutorial for geocoding addresses through a REST API. Every snippet in this post was written, copy-pasted into a file, and executed against the live API on a clean Python 3.11 install before publishing. Two dependencies ( httpx , aiofiles ) — no SDK, no framework, no magic. By the end of the post you will have a script that streams a CSV of any size, geocodes its rows conc...
| Updated Apr 27, 2026
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Node.js Geocoding API Tutorial: Concurrency, Retries, and CSV Streaming
This is a working Node.js tutorial for geocoding addresses through a REST API. The code in this post was written, copy-pasted into files, and executed before publishing. Every snippet runs on a clean Node 22 install with two dependencies (p-limit, csv-parse). No frameworks, no SDK, no magic. What you will end up with by the end of the post: a script that reads a CSV of addresses, geocodes them c...
| Apr 26, 2026
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Door-to-Door Canvassing Software in 2026 — And the One Data Rule That Saves Every Walk
A field director in Phoenix hands her walk captains a list of 12,400 addresses pulled from the state voter file. By the end of the weekend, her 48 volunteers have knocked on 8,800 doors. Contact rate: 71%. The rest — nearly 3,600 attempts — hit vacant lots, demolished homes, PO boxes, and buildings that were never residential to begin with. Over a 12-week cycle, that is the equivalent of paying 4...
| Apr 22, 2026
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Geocoding for Healthcare: Patient Mapping, Facility Planning & HIPAA Compliance
A community health center in rural Appalachia serves 14 counties across three states. Their patient records contain 23,000 home addresses. The director needs to answer a question that determines next year’s $2.4 million federal grant renewal: How many patients live more than 30 miles from the nearest clinic? Without geocoding, answering this question means someone opening Google Maps 23,000 times....
| Apr 14, 2026
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Geocoding for Logistics & Fleet Management: The Complete Guide
If you run a logistics operation, you already know the numbers: failed deliveries cost $17.20 each on average , fuel is your second-largest expense, and your drivers waste 20-30% of their time just figuring out where to go. The root cause behind most of these problems? Bad address data. Geocoding — converting street addresses into GPS coordinates (latitude and longitude) — is the foundational la...
| Apr 12, 2026
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How to Geocode Addresses in Google Sheets: 4 Methods That Actually Work
If you have a Google Sheet full of addresses and need latitude/longitude coordinates, you are in the right place. Whether you are mapping customer locations, planning delivery routes, or building a store locator, geocoding in Google Sheets is one of the most common data tasks that nobody teaches you how to do properly. The problem? Google Sheets has no built-in geocoding function. There is no =G...
| Apr 10, 2026
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