Inventory automation platform with scheduling, queues, and live progress
A full-stack system for scheduled scrapes, managed worker capacity, and clean outputs with admin controls and logs.
Problem
Scraping jobs ran ad-hoc and were hard to debug. There was no clear visibility into progress, capacity, failures, or outputs.
Stack
- - Python
- - Django
- - PostgreSQL
- - Workers/queues
- - Scheduling
- - Admin UI
Architecture
System architecture
A simplified view of how the system is wired. (Details and metrics are intentionally omitted until confirmed.)
- →
Step 01
Scheduler
Cron + job definitions
- →
Step 02
Workers
Concurrency + retries
- →
Step 03
Job state
DB-backed progress + logs
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Step 04
Outputs
Downloads + exports
- →
Step 05
Admin UI
Controls + observability
- - TODO: Add real concurrency + throughput numbers once measured.
Outcome
What changed
- More reliable scraping runs via managed worker capacity
- Clear progress and debugging via DB-backed logs
- Admin-friendly controls for operations teams
Metrics
Metrics are shown only when verified. Placeholders live in `lib/data.ts`.
Media
Demo / screenshots
System demo (click to load).
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