# Host GraphQL API with Flask: Streamed Responses

Deploy a GraphQL API built with Flask on Ample using the streaming response service 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.

Verified on Flask: a Server-Sent Events endpoint read incrementally through the public HTTPS gateway: five one-second chunks arrived spread over time with the first within seconds (not buffered), a 70-second stream of 36 chunks completed past common 60-second idle timeouts, and a client that disconnected after two chunks was observed and recorded by the server (disconnected=true).

Not separately tested: your event schema, reconnection strategy and any per-request duration ceiling beyond the 70 seconds measured; treat the GraphQL API-specific behavior as your application code.

## Resource Requirements
- **Compute**
- **Postgres**

## Infrastructure Requirements
### Compute
Apps run in isolated x86_64 Firecracker microVMs that auto-pause when idle and wake on request; sizes are the priced VM sizes.

### PostgreSQL
Managed PostgreSQL 16 runs in its own microVM and is auto-provisioned when an app needs a database and no DATABASE_URL is supplied.

## 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).
- An Ample account token with servers:write, databases:read.

## 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 app.py

## Workflow Steps
1. **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.
2. **Implement the Pattern on PostgreSQL**: Copy the approach into your schema; keep migrations idempotent and run them with --release-command.
3. **Deploy**: Run the synchronous deploy once and read the result (exit 0 live, 1 failed, 2 blocked).
4. **Verify**: Fetch the live URL and the pattern self-test route(s) (/p/streaming-response-service) from the example; then run your own checks.

## Limitations
- Verified on the python-3.12 template at s-1vcpu-1gb; other sizes, templates, and Flask major versions are not verified.
- The GraphQL API itself (your event schema, reconnection strategy) was not separately tested; the pattern checks are what was verified.

## Cost Estimate
- **Currency**: USD
- **Monthly Amount**: 10.0
- **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.