### Host Company Website with Django: Bulk Content Imports

Deploy a company website built with Django 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 Django: 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 company website-specific behavior as your application code.

#### Summary
- **Family**: Workload Recipe
- **Framework**: Django
- **Workload**: Company Website
- **Release Status**: Published
- **Support Status**: Verified
- **Execution Status**: Ready

#### Resource Requirements
- Compute
- Postgres
- S3-compatible Object Storage

#### Prerequisites
1. A Django project that builds and starts with the documented commands (pip install into .ample/python from requirements.txt, then waitress serving project.wsgi 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. A bucket from `ample bucket create` with its credentials passed as encrypted S3_* environment variables
4. An Ample account token with servers:write, databases:read, buckets: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 waitress serving project.wsgi 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 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**  
   - 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**  
   - 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" --env S3_ENDPOINT=... --env S3_REGION=... --env S3_BUCKET=... --env S3_ACCESS_KEY_ID=... --env S3_SECRET_ACCESS_KEY=...`  
5. **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`.  
   - Command: `ample logs  --kind build`

#### Examples
- **Django Pattern Fixture**: Multi-pattern Django app whose bulk import staging module was checked live; the module is under tests/deploy-canaries/_pattern-modules. Source Ref: `tests/deploy-canaries/django-patterns`

#### Success Checks
- **App Responds on Its Public URL**  
   - Kind: `http_get`  
   - Path: `/`  
   - Expect: `ample canary django patterns`
- **Bulk Import Staging Self-Test**  
   - Kind: `http_get`  
   - Path: `/p/bulk-import-staging`  
   - Expect: `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 Django major versions are not verified.
- The company website 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.
- Managed PostgreSQL 16 only; extensions, connection limits and backup or restore procedures are not verified; apps and their databases are placed together.
- PutObject and GetObject with path-style addressing are verified; multipart upload, listing, presigned URLs and lifecycle rules are not.