## Logistics operators: public directory using Django

### Summary
A public directory blueprint for logistics operators built with Django on Ample. Domain schema: service_products (sku, name, mode, transit_days, price_basis): shipping services as SKUs; capacity_movements (sku, lane, date, delta, reason): capacity as stock movements; shipments (shipment_no, lane, status, booked_at): shipments with status transitions; shipment_lines (shipment_no, sku, units): shipment contents; state_transitions (record_type, from_state, to_state): the allowed state machine. Public information: service products and transit times, lanes served, tracking entry point. Kept out of scope until handling is reviewed: consignee addresses, commercial invoices, customs documents. Customs and consignee data are sensitive; only shipment status is modeled here. Technical basis verified on Django: a workspace-scoped table, an explicit state machine (draft to review to published) that rejects invalid transitions, and a cross-workspace read that returns nothing (transitions=true isolation=true).

### Representative Queries
1. Logistics operators: public directory using Django
2. Where can I host Logistics operators: Public directory built with Django?
3. I need a genuinely specialized public directory workflow covering shipment state, partner access and delivery exception reporting.

### Workflow Steps
1. **Model the logistics operators domain**: Create the tables service_products, capacity_movements, shipments, shipment_lines, state_transitions. Shipping services as skus lives in service_products; keep the sensitive classes (consignee addresses, commercial invoices, customs documents) out of this schema.
2. **Workflow step 1**: Model listings with a publishing_status state machine scoped to the agency.
3. **Workflow step 2**: Serve only published listings, with media from the CDN bucket.
4. **Workflow step 3**: Enforce the agency scope on every query.
5. **Workflow step 4**: Deploy and verify a published listing and that unpublished listings are absent.
6. **Deploy**: Run the synchronous deploy once and read the result. Re-running with no change is a no-op.
   Command: `ample deploy . --name  --public --start "python3 run.py" --env S3_ENDPOINT=... --env S3_REGION=... --env S3_BUCKET=... --env S3_ACCESS_KEY_ID=... --env S3_SECRET_ACCESS_KEY=... --env CDN_PUBLIC_URL=...`
7. **Verify**: Run the pattern self-test(s) from the example (/p/relational-records) and your own acceptance checks for the logistics operators workflow.
   Command: `ample logs  --kind build`

### Cost Estimate
- **Monthly Amount**: $10.00
- **Basis**: Size prices from pricing.toml (loaded by the API).
  - **app server**: size "s-1vcpu-1gb", quantity: 1.0, monthlyAmount: $5.00
  - **managed PostgreSQL database**: size "s-1vcpu-1gb", quantity: 1.0, monthlyAmount: $5.00
- **Note**: Always-on monthly price of the tested sizes; apps and databases auto-pause when idle. Buckets are allocation-priced per quota and not included.