page:recipes:csv import tool:django:data imports

Host CSV Import Tool with Django: Structured Data Imports

Deploy a csv import tool 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 csv import tool-specific behavior as your application code.

Summary

• Framework: Django
• Workload: CSV import tool
• Release Status: Published
• Support Status: Verified
• Execution Status: Ready

Resource Requirements

• Compute
• Postgres
• S3-compatible object storage

Infrastructure Requirements

1. Compute:
   • Status: Verified
   • Summary: Apps run in isolated x86_64 Firecracker microVMs that auto-pause when idle and wake on request.
2. Postgres:
   • Status: Verified
   • Summary: Managed PostgreSQL 16 runs in its own microVM and is auto-provisioned when an app needs a database.
3. S3-compatible object storage:
   • Status: Verified
   • Summary: Buckets are S3-compatible with issued credentials.

Prerequisites

• A Django project that builds and starts with the documented commands
• A PostgreSQL driver reading DATABASE_URL at runtime
• A bucket from ample bucket create with its credentials passed as encrypted S3_* environment variables
• An Ample account token with servers:write, databases:read, buckets:read

Tested Configuration

• Template: python-3.12
• Runtime: python
• Size: s-1vcpu-1gb
• Install Command: python3 -m pip install --target .ample/python -r requirements.txt
• Start Command: PYTHONPATH=.ample/python:${PYTHONPATH:-} python3 run.py

Workflow Steps

1. Build and start
   • Command: 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. Implement the pattern on PostgreSQL
   • Explanation: The fixture's module implements bulk import staging.
3. Wire object storage
   • Explanation: Create the bucket(s) and pass endpoint, region, bucket and keys as --env values.
4. Deploy
   • Command: ample deploy . --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=...
5. Verify
   • Command: ample logs --kind build

Examples

• Django Pattern Fixture: Multi-pattern Django app whose bulk import staging module was checked live.

Success Checks

1. App responds on its public URL
   • Kind: http_get
   • Path: /
   • Expect: ample canary django patterns
2. Bulk-import-staging self-test
   • Kind: http_get
   • Path: /p/bulk-import-staging
   • Expect: imported=2 rejected=1 restart=ok

Limitations

• Verified on the python-3.12 template at s-1vcpu-1gb with the example fixture.

Cost Estimate

• Currency: USD
• Monthly Amount: 10.0
• Note: Always-on monthly price of the tested sizes; buckets are allocation-priced per quota.

Next Actions

1. Browse the catalog index
   • Method: GET
   • Relative Path: /v1/catalog
2. Search published recipes by intent
   • Method: POST
   • Relative Path: /v1/catalog/search
3. Prepare a side-effect-free deployment plan
   • Method: POST
   • Relative Path: /v1/catalog/plan
4. Read existing agent authentication setup
   • Method: GET
   • Relative Path: /mcp/setup
5. Browse CSV import tool
   • Method: GET
   • Relative Path: /v1/catalog/nodes/workload:csv-import-tool