Host Approval Workflow with Flask: CSV Imports

Deploy an approval workflow 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 approval workflow-specific behavior as your application code.

Representative Queries

• Host approval workflow with Flask: CSV imports
• Where can I host Approval workflow 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

Infrastructure Requirements

1. Compute

   • Status: Verified
   • Summary: 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

   • Status: Verified
   • Summary: 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

   • Status: Verified
   • Summary: Buckets are S3-compatible with issued credentials; PutObject and GetObject are verified by canary. Other S3 operations are not verified.

Prerequisites

• A Flask project that builds and starts with the documented commands (pip install into .ample/python from requirements.txt, then waitress from app.py reading PORT on the python-3.12 template).
• A PostgreSQL driver reading DATABASE_URL at runtime (auto-provisioned when omitted, or supplied with --env).
• 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.

Workflow Steps

1. Build and Start

   • Command: pip install into .ample/python from requirements.txt, then waitress from app.py reading PORT on the python-3.12 template.
   • Note: The server must bind 0.0.0.0 on PORT.

2. Implement the pattern on PostgreSQL

   • Description: 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.

3. Wire Object Storage

   • Description: 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.

4. Deploy

   • Command: 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=...
   • Note: 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

   • Command: ample logs --kind build
   • Description: 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.

Examples

• Flask Pattern Fixture
  • Description: Multi-pattern Flask app whose bulk import staging module was checked live; the module is under tests/deploy-canaries/_pattern-modules.
  • Source Reference: tests/deploy-canaries/flask-patterns

Success Checks

1. App responds on its public URL

   • Kind: http_get
   • Path: /
   • Expectation: ample canary flask patterns

2. Bulk-import-staging self-test

   • Kind: http_get
   • Path: /p/bulk-import-staging
   • Expectation: imported=2 rejected=1 restart=ok

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 approval workflow itself (your import format, mapping and conflict rules) is application code and was not separately tested; the pattern checks are what was verified.
• Region, compliance attestations and request-duration limits are unknown and not claimed.
• Apps auto-pause when idle and wake on the next request; always-on is an operator setting, not a plan feature.

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: size s-1vcpu-1gb, quantity 1.0, monthly amount 5.0
  • Managed PostgreSQL Database: size s-1vcpu-1gb, quantity 1.0, monthly amount 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.