page:recipes:recruiting tracker:flask:csv imports

Host recruiting tracker with Flask: CSV imports

Deploy a recruiting tracker built with Flask 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 Flask: 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 recruiting tracker-specific behavior as your application code.

Representative Queries

Host recruiting tracker with Flask: CSV imports
Where can I host Recruiting tracker built with Flask?
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

Workflow Steps

Build and start
pip install into .ample/python from requirements.txt, then waitress from app.py reading PORT on the python-3.12 template. The server must bind 0.0.0.0 on PORT.
Implement the pattern on PostgreSQL
The fixture's module implements bulk import staging: 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). Copy the approach into your schema; keep migrations idempotent and run them with --release-command.
Wire object storage
Create the bucket(s), then pass endpoint, region, bucket and keys as --env values. Use path-style addressing. Keep private data in an unpublished bucket.

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.

ample deploy . --name  --public --start "python3 app.py" --env S3_ENDPOINT=... --env S3_REGION=... --env S3_BUCKET=... --env S3_ACCESS_KEY_ID=... --env S3_SECRET_ACCESS_KEY=...

Verify
Fetch the live URL and the pattern self-test route(s) (/p/bulk-import-staging) from the example; then run your own checks. On failure read ample logs --kind build then --kind runtime.
```
ample logs  --kind build  
```

Examples

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

Limitations

Verified on the python-3.12 template at s-1vcpu-1gb with the example fixture; other sizes, templates and Flask major versions are not verified.
The recruiting tracker itself (your import format, mapping and conflict rules) is application code and was not separately tested; the pattern checks are what was verified.

Cost Estimate

Currency: USD
Monthly Amount: 10.0
- Basis: size prices from pricing.toml (loaded by the API) at build revision 1ac5595375130d45290090e82ed0f554ccd45405-dirty
- Components:
  - App server: s-1vcpu-1gb, 1.0, 5.0
  - Managed PostgreSQL database: s-1vcpu-1gb, 1.0, 5.0
Note: Always-on monthly price of the tested sizes; apps and databases auto-pause when idle. Buckets are allocation-priced per quota and not included.