Property management: public directory using Django

Summary

A public directory blueprint for property management built with Django on Ample. Domain schema: listings (reference, address, unit, rent, publishing_status, agency_id): rental listings with publishing status; agencies (name, license_number, portfolio_size): management offices; maintenance_vendors (name, trade, agency_id, status): vendors per office; reports (agency_id, period, object_key, generated_at): portfolio reports per office; state_transitions (record_type, from_state, to_state): the allowed state machine. Public information: available rentals, office contacts, application process. Kept out of scope until handling is reviewed: tenant identity and payment history, inspection reports with personal data. Tenant data is personal and often regulated; only published listings and office-scoped reporting are modeled. 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).

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.)
• CDN: verified (The CDN host serves objects from published buckets. It does not front app compute and is not a cache or key-value store.)

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 and a published bucket for public assets (CDN_*)
• A review of which property management 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 property management domain. Create the tables listings, agencies, maintenance_vendors, reports, state_transitions. Rental listings with publishing status lives in listings; keep the sensitive classes (tenant identity and payment history, inspection reports with personal data) 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.

   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=... --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 property management workflow.

   ample logs <deployment_id> --kind build
   

Tested examples

• Django pattern fixture (tests/deploy-canaries/django-patterns): Verified relational records basis for this blueprint.

Success checks

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

Limitations

• The technical basis (relational records on Django) was verified with the pattern fixture; the property management 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. Tenant data is personal and often regulated; only published listings and office-scoped reporting are modeled.
• 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.