Accounting firms: project tracker using Django

A project tracker blueprint for accounting firms built with Django on Ample. Domain schema:

• client_entities (legal_name, entity_type, fiscal_year_end, jurisdiction): the businesses and individuals served;
• engagements (client_entity_id, service_line, period_start, period_end, status): bookkeeping, tax and audit engagements by period;
• document_requests (engagement_id, title, due_at, status, uploaded_object_key): requests for source documents;
• deliverables (engagement_id, title, object_key, released_at): returns and statements released to the client;
• state_transitions (record_type, from_state, to_state): the allowed state machine.

Public information: service lines and typical engagement periods, filing calendars and deadlines, office locations. Kept out of scope until handling is reviewed: tax identifiers and financial statements, bank and payroll records, identity documents. Financial records and tax identifiers are regulated in most jurisdictions; the portal flows here model authorization only and claim no compliance.

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).

Representative Queries

• Accounting firms: project tracker using Django
• Where can I host Accounting firms: Project tracker built with Django?
• I need a genuinely specialized project tracker workflow covering engagement periods, client entities and document authorization.

Workflow Steps

1. Model the accounting firms domain
   Create the tables client_entities, engagements, document_requests, deliverables, state_transitions. The businesses and individuals served lives in client_entities; keep the sensitive classes (tax identifiers and financial statements, bank and payroll records, identity documents) out of this schema.
2. Workflow step 1
   Model engagements and workstreams with explicit status transitions.
3. Workflow step 2
   Scope every query by client entity.
4. Workflow step 3
   Attach deliverables as private objects linked to workstreams.
5. Workflow step 4
   Deploy and verify transitions and cross-client isolation.
6. Deploy
   Run the synchronous deploy once and read the result. Re-running with no change is a no-op.
   Command: ample deploy . --name <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/relational-records) and your own acceptance checks for the accounting firms workflow.
   Command: ample logs --kind build

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 accounting firms data classes may be handled at all; this blueprint models public information only

Limitations

• The technical basis (relational records on Django) was verified with the pattern fixture; the accounting firms schema and workflow are an original design for this blueprint and were not executed as a separate application.
• Public content and synthetic examples only until actual data-handling requirements have been reviewed.

Success Checks

• App responds on its public URL
• Relational-records self-test from the example.

Example

• Django pattern fixture: Verified relational records basis for this blueprint.

Cost Estimate

• Monthly Amount: $10.00, authoritative
  • Basis: size prices from pricing.toml (loaded by the API)
  • High-level components:
  • App server (s-1vcpu-1gb): $5.00
  • Managed PostgreSQL database (s-1vcpu-1gb): $5.00

Evidence Summary

• Django pattern fixture deployed on Ample: 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).

• Last Verified At: 2026-09-20T03:31:44Z

Formats

• HTML: Accounting Firms Project Tracker
• Markdown: click here
• JSON: click here