BlackPrint Technologies · Jul 2026
Mall Mobility Report
Foot-Traffic Rhythms Across Five Shopping Centers
Overview
Built a self-contained mobility report for a national athletic-footwear retailer comparing device-based foot traffic, weekly rhythm and peak hours across five shopping centers.
Highlights
- 01
Built a single-file, dependency-free report with embedded data and a Content Security Policy that blocks every runtime network call, comparing foot traffic across 5 shopping centers measured over each building footprint plus 500 m.
- 02
Wrote Python extraction from PostgreSQL and a build step that sanitizes enrichment data, dropping internal names and coordinates and aggregating socioeconomic levels into three tiers before injection.
- 03
Added a Node verification script that checks the embedded data for exact equality with the source aggregates and enforces the report's forbidden-term rules before delivery.
Stack
- Python
- PostgreSQL
- psycopg2
- Node.js
- JavaScript
- HTML/CSS
- Content Security Policy
- Mobility Analytics
- Data Sanitization
- Vercel
Working on something similar?
Tell me about the problem and the data behind it. I reply within 24–48 hours.
Discuss a project