👋 Hi there! In this edition of The Geodata Insider, we're covering major changes USPS has made to its free API tool, as well as core updates to our Brazil postcodes and Thailand boundary data.
4:00 minute read
🗽USPS free address validation just dropped to 60 requests/hour
📍 Core update on the Brazil postal database
🌟 Calculate distances between ZIP codes on Python and Excel
🔎 Monthly changes
🌍 The quiet drift of continents
USPS free address validation just dropped to 60 requests/hour
On January 25, 2026, USPS retired its legacy Web Tools and replaced them with a new, rate-limited Address Validation API.
For teams running address checks at scale, the default limit of 60 requests per hour quickly becomes a bottleneck for bulk validation, order fulfillment, and downstream processes that depend on stable throughput.
If you're currently using the USPS API, now is the perfect time to switch to GeoPostcodes' self-hosted U.S. address data, built for reliable, high-volume address validation.
If you need assistance adapting your address validation workflows,
please contact us by replying to this email.
Core update on the Brazil postal database
An upcoming release will introduce a breaking change to the Brazil dataset. To better align with the official administrative structure and postal standards:
Districts will be added as a fourth level of administrative divisions,
The locality field will be refactored to use the name expected by Correios when writing an address,
The current suburbs layer will be removed, and their Correios-recommendednamewill now be displayed uniquely in the locality column.
What this means for you: Simplified address capture by allowing customers to focus on State (level 1), Municipality (level 3), and locality.
Photo by Samuel Costa Melo on Unsplash
Calculate distances between ZIP codes on Python and Excel
Turning ZIP code and coordinate data into actionable insights often starts with basic geospatial calculations,such as measuring the distance between two ZIP codes.
A simple 2D plane approximation can be fast and sufficient for small areas, while formulas like Haversine (spherical Earth) or Vincenty (ellipsoidal, geodesic) provide increasing accuracy for longer distances.
In this issue, we share two practical guides to help you implement distance calculations in Python and Excel using popular geospatial libraries and GeoPostcodes' latitude and longitude data.
Distance between E14 3PW in London and 01490 in Mexico City based on the Python script provided in GeoPostcodes' article.
Sharper postal boundaries in Thailand
We’ve improved the granularity of our Thailand postal boundaries to better delineate borders between neighboring postal codes.
This improvement delivers more accurate spatial results, especially for distance calculation, proximity analysis, service-area definition, and coverage modeling.
MONTHLY CHANGES
In January, we updated29,040rowsin our postal database.
