# Host Appointment Booking with FastAPI: Structured Data Imports

Deploy an appointment booking built with FastAPI 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.

## Summary
Verified on FastAPI: 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 appointment booking-specific behavior as your application code.

## Representative Queries
- Host appointment booking with FastAPI: structured data imports
- Where can I host Appointment booking built with FastAPI?
- I need a workload-specific import mapping, conflict rules and restart behavior.

## 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; 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 FastAPI project that builds and starts with the documented commands.
- A PostgreSQL driver reading DATABASE_URL at runtime.
- A bucket created with its credentials passed as encrypted S3_* environment variables.
- An Ample account token with appropriate scopes.

## 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.`
2. **Implement the Pattern on PostgreSQL**  
   Copy the approach into your schema; keep migrations idempotent.
3. **Wire Object Storage**  
   Create the bucket(s), then pass endpoint, region, bucket and keys as --env values.
4. **Deploy**  
   Run the synchronous deploy once and read the result.
5. **Verify**  
   Fetch the live URL and the pattern self-test route(s).

## 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`

## Success Checks
- App responds on its public URL.
- Bulk-import-staging self-test.

## Limitations
- Verified on the python-3.12 template at s-1vcpu-1gb; other versions are not verified.
- The appointment booking itself is application code and was not separately tested.

## Cost Estimate
- **Currency**: USD
- **Monthly Amount**: 10.0
- **Components**:
   - **App Server**: s-1vcpu-1gb (5.0)
   - **Managed PostgreSQL Database**: s-1vcpu-1gb (5.0)

## Evidence Summary
- FastAPI pattern fixture deployed on Ample; checks passed for bulk-import-staging.

## Next Actions
- Browse the catalog index.
- Search published recipes by intent, stack, and constraints.
- Prepare a side-effect-free deployment plan for an authorized project.