/home
5+ years of production Django applications for the real estate industry, including a nominations platform that replaced an expensive legacy vendor and now processes over a thousand submissions a year.
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/projects
/projects/lockbox-loaner-tool
A Django app that replaced a manual spreadsheet process, pulling live MLS listing data via RETS to automatically track lockbox loans from request to return - supporting over a thousand users and thousands of loans across dozens of participating locations.
/projects/nominations-platform
A custom nominations platform that replaced a costly third-party service, pulling listing and Realtor data directly from the MLS and internal records to eliminate manual verification work for an annual awards program.
/about
Self-taught, mostly by shipping things and fixing what broke - for local Realtor associations and MLSs here in Hawaii.
2026
I built a nominations platform to replace a third-party service whose cost had grown substantially over several years, while also fixing a clunky user experience - clients previously had to create an account and manually enter transaction details for every nomination. The new system integrates an MLS data feed with internal association records, so clients simply search for their Realtor by name and select the matching transaction from a list; the platform automatically determines each party's role and pulls the transaction date without manual entry. On submission, all parties receive tailored confirmation emails, and admins get a dashboard to track volume, flag unverified transactions, manage statuses, surface duplicates, and export data. Built with Django, HTMX, Alpine.js, and Tailwind CSS, with SQLAlchemy and Pandas handling backend data processing, the platform has driven a meaningful year-over-year increase in nominations since launch.
2022
I built a Django web application to collect weekly rate submissions from a group of participating local partners, replacing a manual, PDF-based process. Each week, partners submit data directly through the site, which is then compiled and distributed to stakeholders automatically. The application has been in continuous, reliable use since launch.
2022
When our trade show check-in provider announced they were discontinuing their smart card reader service, I was asked to find a replacement. Available SaaS options were expensive and required new hardware and an internet connection, which didn't work for us - our events needed to run offline (internet access at venues was costly) on existing 2010-era netbooks running Windows 7. I built a lightweight desktop app in PyGUI that let staff scan attendee QR codes for door prize entries, randomly select winners, and export contact information to CSV, with barcode scanners as the only new hardware purchase. The app - jokingly named "PewPew Reader" after an offhand comment at a staff meeting - was used by 45 trade show vendors at each event across 3 trade shows, before the original provider reinstated their service and our organization shifted to centralized check-in.
2021
After evaluating third-party options that didn't fit our needs, I proposed and built a Django web application to replace a manual, spreadsheet-based process for a regional equipment loaner program. The app connects to an MLS data feed to manage requests and keep listing and agent data in sync, while tracking overdue equipment and usage. Years later, it's still in daily use, having processed thousands of requests from over a thousand users across dozens of participating locations.
2019
Started writing Python scripts to pull data from APIs, CSVs, and Excel files into unified reports - replacing a manual, spreadsheet-heavy process.