page:blueprints:property management:reporting dashboard:django

Property Management: Reporting Dashboard Using Django

A reporting dashboard blueprint for property management built with Django on Ample.

Domain Schema:

• Listings: rental listings with publishing status (reference, address, unit, rent, publishing_status, agency_id)
• Agencies: management offices (name, license_number, portfolio_size)
• Maintenance Vendors: vendors per office (name, trade, agency_id, status)
• Reports: portfolio reports per office (agency_id, period, object_key, generated_at)
• Exports: generated artifacts and who may download them (id, definition, object_key, row_count, generated_at, authorized_role)

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:

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).

Representative Queries:

• Property management: reporting dashboard using Django
• Where can I host Property management: Reporting dashboard built with Django?
• I need a genuinely specialized reporting dashboard workflow covering building/vendor access, maintenance status and property reporting.

Resource Requirements:

• primitive:compute
• primitive:postgres
• primitive:s3-compatible-object-storage

Infrastructure Requirements:

• Compute: Apps run in isolated x86_64 Firecracker microVMs that auto-pause when idle and wake on request.
• Postgres: 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: Buckets are S3-compatible with issued credentials; PutObject and GetObject are verified.

Prerequisites:

1. 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)
2. A PostgreSQL driver reading DATABASE_URL (auto-provisioned when omitted)
3. Bucket credentials from ample bucket create passed as encrypted S3_* environment variables
4. A review of which property management data classes may be handled at all; this blueprint models public information only

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

Workflow Steps:

1. Model the Property Management Domain: Create the tables listings, agencies, maintenance_vendors, reports, exports.
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.
7. Verify: Run the pattern self-test(s) from the example (/p/generated-downloads) and your own acceptance checks for the property management workflow.

Cost Estimate:

• Currency: USD
• Monthly Amount: 10.0
• Basis: size prices from pricing.toml at build revision.
• Components:
  • App Server: s-1vcpu-1gb (Quantity: 1.0, Monthly Amount: 5.0)
  • Managed PostgreSQL Database: s-1vcpu-1gb (Quantity: 1.0, Monthly Amount: 5.0)

Limitations:

• The technical basis (generated downloads 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.

Examples:

• Django Pattern Fixture: Verified generated downloads basis for this blueprint.

Success Checks:

• App responds on its public URL.
• Generated-downloads self-test from the example.