# Hospitality: reporting dashboard using Django

## Summary

A reporting dashboard blueprint for hospitality built with Django on Ample. Domain schema: room_types (sku, name, capacity, base_rate, amenities): room and package catalog; inventory_movements (sku, date, delta, reason): availability per date as stock movements; bookings (booking_no, check_in, check_out, status): bookings with status transitions; booking_lines (booking_no, sku, nights, rate): booking contents; exports (id, definition, object_key, row_count, generated_at, authorized_role): generated artifacts and who may download them. Public information: room types, amenities and rates from, property location and policies, events and dining. Kept out of scope until handling is reviewed: guest identity documents, payment details, stay history. Guest identity documents are sensitive; only availability and booking status are modeled here. Technical basis verified on Django: an export query rendered to a CSV artifact stored with metadata in a private bucket and returned only to an authorized caller (401 without token, export=ok rows=3).

## Infrastructure requirements

- Compute: verified (Apps run in isolated x86_64 Firecracker microVMs that auto-pause when idle and wake on request; sizes are the priced VM sizes.)
- Postgres: verified (Managed PostgreSQL 16 runs in its own microVM and is auto-provisioned when an app needs a database and no DATABASE_URL is supplied.)
- S3-compatible object storage: verified (Buckets are S3-compatible with issued credentials; PutObject and GetObject are verified by canary. Other S3 operations are not verified.)

## Prerequisites

- A Django project (pip install into .ample/python from requirements.txt, then waitress serving project.wsgi from run.py reading PORT on the python-3.12 template)
- A PostgreSQL driver reading DATABASE_URL (auto-provisioned when omitted)
- Bucket credentials from `ample bucket create` passed as encrypted S3_* environment variables
- A review of which hospitality data classes may be handled at all; this blueprint models public information only

## Exact tested configuration

- template: `python-3.12`
- runtime: `python`
- size: `s-1vcpu-1gb`
- install: `python3 -m pip install --target .ample/python -r requirements.txt`
- start: `PYTHONPATH=.ample/python:${PYTHONPATH:-} python3 run.py`

## Steps

1. **Model the hospitality domain.** Create the tables room_types, inventory_movements, bookings, booking_lines, exports. Room and package catalog lives in room_types; keep the sensitive classes (guest identity documents, payment details, stay history) out of this schema.
2. **Workflow step 1.** Model report definitions scoped to the agency
3. **Workflow step 2.** Generate report artifacts from queries and store them with metadata
4. **Workflow step 3.** Authorize downloads (401 without identity)
5. **Workflow step 4.** Deploy and verify an authorized export and the rejected anonymous request
6. **Deploy.** Run the synchronous deploy once and read the result. Re-running with no change is a no-op.

```
   ample deploy . --name <app-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=...
   ```
7. **Verify.** Run the pattern self-test(s) from the example (/p/generated-downloads) and your own acceptance checks for the hospitality workflow.

```
   ample logs <deployment_id> --kind build
   ```

## Tested examples

- **Django pattern fixture** (tests/deploy-canaries/django-patterns): Verified generated downloads basis for this blueprint.

## Success checks

- app responds on its public URL (`/` on the live URL, expect ample canary django patterns)
- generated-downloads self-test from the example (`/p/generated-downloads` on the live URL, expect see the pattern fixture checks)

## Limitations

- The technical basis (generated downloads on Django) was verified with the pattern fixture; the hospitality schema and workflow are an original design for this blueprint and were not executed as a separate application.
- No health, financial, privacy or other compliance claim is made. Guest identity documents are sensitive; only availability and booking status are modeled here.
- Public content and synthetic examples only until actual data-handling requirements have been reviewed.
- Verified on the python-3.12 template at s-1vcpu-1gb; region, request-duration limits and other sizes are unknown or unverified.
- Managed PostgreSQL 16 only; extensions, connection limits and backup or restore procedures are not verified.
- PutObject and GetObject with path-style addressing are verified; other S3 operations and CDN cache rules are not.

## Cost estimate

Estimated 10.00 USD per month (size prices from pricing.toml at build revision a1b8c38919e59cd035ebabaced73cf84ece24371).
- app server x1 `s-1vcpu-1gb`: 5.00 USD
- managed PostgreSQL database x1 `s-1vcpu-1gb`: 5.00 USD

Always-on monthly price of the tested sizes; apps and databases auto-pause when idle. Buckets are allocation-priced per quota and not included.

## Verification evidence

- canary_run on 2026-09-20T03:31:44Z at revision `03b6402b1b3e19178985f08ea4033804521d85d4-dirty (CLI b75e104)`: Django pattern fixture deployed on Ample (pip install into .ample/python from requirements.txt, then waitress serving project.wsgi from run.py reading PORT on the python-3.12 template); the generated downloads checks passed: an export query rendered to a CSV artifact stored with metadata in a private bucket and returned only to an authorized caller (401 without token, export=ok rows=3). The blueprint's Hospitality schema and workflow below build on that verified basis and were not separately executed. (expires 2027-03-19T03:31:44Z)

Last verified: 2026-09-20T03:31:44Z