## Host approval workflow with Django: CSV imports

Deploy an approval workflow built with Django on Ample using the bulk import staging pattern. Compute runs the app in an isolated microVM behind a public HTTPS URL, a managed PostgreSQL 16 database is auto-provisioned and injected as DATABASE_URL, a private S3-compatible bucket holds objects with credentials delivered as encrypted environment variables. Verified on Django: a CSV staged as an object, row-level validation with per-row errors recorded, and a restart-safe import keyed by import id (imported=2 rejected=1 restart=ok). Not separately tested: your import format, mapping and conflict rules; treat the approval workflow-specific behavior as your application code.

### Representative Queries
- Host approval workflow with Django: CSV imports
- Where can I host Approval workflow built with Django?
- I need a domain CSV format, row validation, deduplication and an import recovery path.

### Resource Requirements
- primitive:compute
- primitive:postgres
- primitive:s3-compatible-object-storage

### Infrastructure Requirements
1. **Compute**: Apps run in isolated x86_64 Firecracker microVMs that auto-pause when idle and wake on request; sizes are the priced VM sizes.
2. **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.
3. **S3-compatible object storage**: Buckets are S3-compatible with issued credentials; PutObject and GetObject are verified by canary. Other S3 operations are not verified.

### Workflow Steps
1. **Build and start**: 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 server must bind 0.0.0.0 on PORT.
2. **Implement the pattern on PostgreSQL**: Copy the approach into your schema; keep migrations idempotent and run them with --release-command.
3. **Wire object storage**: Create the bucket(s), then pass endpoint, region, bucket and keys as --env values. Keep private data in an unpublished bucket.
4. **Deploy**: Run the synchronous deploy once and read the result (exit 0 live, 1 failed, 2 blocked). Re-running with no change is a no-op.
5. **Verify**: Fetch the live URL and the pattern self-test route(s); then run your own checks.

### Examples
- **Django pattern fixture**: Multi-pattern Django app whose bulk import staging module was checked live; the module is under tests/deploy-canaries/_pattern-modules.

### Success Checks
1. app responds on its public URL
2. bulk-import-staging self-test

### Limitations
- Verified on the python-3.12 template at s-1vcpu-1gb; other sizes, templates and Django major versions are not verified.
- The approval workflow itself (your import format, mapping and conflict rules) is application code and was not separately tested.

### Cost Estimate
- **Monthly Amount**: 10.0 USD
- **Components**: 
  - app server: 5.0 USD
  - managed PostgreSQL database: 5.0 USD

### Evidence Summary
- **Canary run**: Django pattern fixture deployed on Ample; checks passed for bulk-import-staging and configuration-secrets.

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

### Formats
- **HTML**: [Link](/content/recipes/approval-workflow/django/csv-imports/index.html)  
- **Markdown**: [Link](/content/recipes/approval-workflow/django/csv-imports.md)  
- **JSON**: [Link](https://api.ample.computer/v1/catalog/recipes/page%3Arecipes%3Aapproval-workflow%3Adjango%3Acsv-imports)

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