Real estate brokerages: public directory using Django

Summary

A public directory blueprint for real estate brokerages built with Django on Ample. Domain schema: listings (reference, address, price, listing_type, publishing_status, agency_id): property listings with publishing status; agencies (name, license_number, region): agencies or branches; listing_media (listing_id, object_key, cdn_key, sort_order): public media per listing; reports (agency_id, period, object_key, generated_at): agency-scoped reports; state_transitions (record_type, from_state, to_state): the allowed state machine. Public information: published listings with media, agent and agency profiles, buying and selling guides. Kept out of scope until handling is reviewed: vendor and buyer identity, offers and negotiations, unpublished listings. Only listings with publishing_status = published appear publicly; offers and identities are out of scope. 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 real estate brokerages 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 real estate brokerages domain. Create the tables listings, agencies, listing_media, reports, state_transitions. Property listings with publishing status lives in listings; keep the sensitive classes (vendor and buyer identity, offers and negotiations, unpublished listings) 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 real estate brokerages 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 real estate brokerages 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. Only listings with publishing_status = published appear publicly; offers and identities are out of scope.
• 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 relational records checks passed: 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). The blueprint's Real estate brokerages schema and workflow below build on that verified basis and were not separately executed. (expires 2027-03-19T03:31:44Z)