## Host rest api with Starlette: Postgres-backed state

Deploy a rest api built with Starlette on Ample using the durable job state 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 Starlette: a jobs table with a state and attempts counter, processing inside a row-locked transaction, and a second run that is a no-op (job=done attempts=1 idempotent=true). Not separately tested: your job types, payload schema and retry policy; treat the rest 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.
- **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.

### Prerequisites
1. A Starlette project that builds and starts with the documented commands (pip install into .ample/python from requirements.txt, then uvicorn from run.py reading PORT on the python-3.12 template)
2. A PostgreSQL driver reading DATABASE_URL at runtime (auto-provisioned when omitted, or supplied with --env)
3. 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 run.py

### Workflow Steps
1. **Build and start**: pip install into .ample/python from requirements.txt, then uvicorn 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**: The fixture's module implements durable job state: a jobs table with a state and attempts counter, processing inside a row-locked transaction, and a second run that is a no-op (job=done attempts=1 idempotent=true). 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). Re-running with no change is a no-op.
   Command: ample deploy . --name --public --start "python3 run.py"
4. **Verify**: Fetch the live URL and the pattern self-test route(s) (/p/durable-job-state) from the example; then run your own checks. On failure read `ample logs  --kind build` then `--kind runtime`.
   Command: ample logs  --kind build

### Examples
- **Starlette pattern fixture**: Multi-pattern Starlette app whose durable job state module was checked live; the module is under tests/deploy-canaries/_pattern-modules.

### Success Checks
1. App responds on its public URL
   - **Kind**: http_get
   - **Path**: /
   - **Expect**: ample canary starlette patterns
2. Durable-job-state self-test
   - **Kind**: http_get
   - **Path**: /p/durable-job-state
   - **Expect**: job=done attempts=1 idempotent=true

### Limitations
- Verified on the python-3.12 template at s-1vcpu-1gb with the example fixture; other sizes, templates and Starlette major versions are not verified.
- The rest api itself (your job types, payload schema and retry policy) is application code and was not separately tested; the pattern checks are what was verified.