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.

Framework

Django

Workload

Reporting dashboard

Industry

Hospitality

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

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).

Workflow 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.
7. Verify
   Run the pattern self-test(s) from the example (/p/generated-downloads) and your own acceptance checks for the hospitality workflow.

Success Checks

• App responds on its public URL
  Kind: http_get
  Path: /
  Expect: ample canary django patterns
• Generated-downloads self-test from the example
  Kind: http_get
  Path: /p/generated-downloads
  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

• Currency: USD
• Monthly Amount: 10.0
• Authoritative: true
• Basis: size prices from pricing.toml (loaded by the API) at build revision 1ac5595375130d45290090e82ed0f554ccd45405-dirty

Components

• App server
  Size: s-1vcpu-1gb
  Quantity: 1.0
  Monthly Amount: 5.0
• Managed PostgreSQL database
  Size: s-1vcpu-1gb
  Quantity: 1.0
  Monthly Amount: 5.0

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.

Evidence Summary

• Kind: canary_run
  Summary: 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. Observed At: 2026-09-20T03:31:44Z
  Implementation Revision: 03b6402b1b3e19178985f08ea4033804521d85d4-dirty (CLI b75e104) Expires At: 2027-03-19T03:31:44Z

Last Verified At

2026-09-20T03:31:44Z

Next Actions

• Browse the catalog index
  Method: GET
  Path: /v1/catalog
• Search published recipes by intent, stack and constraints
  Method: POST
  Path: /v1/catalog/search
• Prepare a side-effect-free deployment plan for an authorized project
  Method: POST
  Path: /v1/catalog/plan
• Read the existing agent authentication setup
  Method: GET
  Path: /mcp/setup
• Browse Hospitality
  Method: GET
  Path: /v1/catalog/nodes/industry%3Ahospitality
• Browse Reporting dashboard
  Method: GET
  Path: /v1/catalog/nodes/workload%3Areporting-dashboard
• Browse Django
  Method: GET
  Path: /v1/catalog/nodes/stack%3Aframework-django
• Browse Deploy web app
  Method: GET
  Path: /v1/catalog/nodes/intent%3Adeploy-web-app