Ingest CSV/Excel property data into PostGIS with validation and geocoding.
npx skills add https://github.com/toobutta/maptelli --skill data-ingest-toobutta
Please help me install this Agent Skill. Skill: data-ingest Source: https://github.com/toobutta/maptelli/tree/main/.claude/skills/data-ingest Command: npx skills add https://github.com/toobutta/maptelli --skill data-ingest-toobutta
Ingest property data from CSV/Excel into a PostGIS-enabled backend, with robust validation, per-row error reporting, and geocoding fallback to enrich incomplete records.
Run a small sample CSV through the bulk import workflow to ingest data and verify results.
High-intent search queries and answers about installing and using this skill.
To ingest real estate data from Excel into a PostGIS database, you can use a bulk import workflow that handles strict column validation, geocoding fallbacks, and PostGIS geometry creation from latitude and longitude coordinates. It processes files into seed-ready data for development and analytics.
The best way to handle row-level errors during CSV property data imports is using per-row error collection with detailed context. This approach diagnoses data issues without failing the entire file, allowing valid records to process while isolating problematic rows for correction.
Yes, you can automatically geocode missing coordinates when ingesting property data. The ingestion workflow includes a geocoding fallback that uses a free service to enrich incomplete records, subsequently creating PostGIS geometry from the retrieved latitude and longitude values.
Yes, asynchronous processing supports progress tracking for large real estate files via Celery. It provides an import ID for polling, allowing you to monitor bulk import status and track endpoint-based data processing without blocking the main application thread.
Column validation fails when importing CSV property data if required fields are missing before processing begins. Strict column validation ensures mandatory data points are present, triggering per-row error collection to provide detailed context for diagnosing incomplete records.
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