django.md
Nonprofits: event registration using Django
Summary
A event registration blueprint for nonprofits built with Django on Ample. Domain schema: course_groups (program, cohort, start_at, end_at): programs and cohorts; memberships (course_group_id, participant_reference, role): participants, volunteers and staff; sessions (course_group_id, starts_at, title, location): program sessions and events; materials (course_group_id, title, object_key, visibility): program materials; events (seq, record_type, record_id, kind, at): application-owned history written in the same transaction. Public information: mission and programs, events, donation entry point. Kept out of scope until handling is reviewed: beneficiary identity and case notes, donor records. Beneficiary and donor data are sensitive; donations are handled by your payment provider and are not modeled here. Technical basis verified on Django: an optimistic version check and an event row written in the same transaction, a stale update rejected, and a history query over the application-owned events (history=2 conflict=rejected).
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.)
- S3-compatible object storage: verified (Buckets are S3-compatible with issued credentials; PutObject and GetObject are verified by canary. Other S3 operations are not verified.)
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 createpassed as encrypted S3_* environment variables - A review of which nonprofits 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
Model the nonprofits domain. Create the tables course_groups, memberships, sessions, materials, events. Programs and cohorts live in course_groups; keep the sensitive classes (beneficiary identity and case notes, donor records) out of this schema.
Workflow step 1. Model sessions with capacity and registrations with status.
Workflow step 2. Register transactionally with a capacity check and an event per registration.
Workflow step 3. Reject stale concurrent updates.
Workflow step 4. Deploy and verify history and conflict handling.
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=...Verify. Run the pattern self-test(s) from the example (/p/transactional-workflows) and your own acceptance checks for the nonprofits workflow.
ample logs <deployment_id> --kind build
Tested examples
- Django pattern fixture (tests/deploy-canaries/django-patterns): Verified transactional workflows basis for this blueprint.
Success checks
- app responds on its public URL (
/on the live URL, expect ample canary django patterns) - transactional-workflows self-test from the example (
/p/transactional-workflowson the live URL, expect see the pattern fixture checks)
Limitations
- The technical basis (transactional workflows on Django) was verified with the pattern fixture; the nonprofits 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. Beneficiary and donor data are sensitive; donations are handled by your payment provider and are not 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.