### Host crm with Flask: CSV imports

Deploy a crm 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 crm-specific behavior as your application code.

#### Representative Queries
- Host crm with Flask: CSV imports
- Where can I host CRM 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**: 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**: 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**: 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**: 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**: 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 app.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`

#### Success Checks
1. App responds on its public URL.
   - Kind: `http_get`
   - Path: `/`
   - Expect: `ample canary flask patterns`
2. 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 Flask major versions are not verified.
- The crm 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 verified.

#### Cost Estimate
- **Currency**: USD  
- **Monthly Amount**: $10.00  
- **Basis**: size prices from pricing.toml (loaded by the API) at build revision 1ac5595375130d45290090e82ed0f554ccd45405-dirty  
- **Components**:
  - App server:  s-1vcpu-1gb  (monthly amount: $5.00)
  - Managed PostgreSQL database: s-1vcpu-1gb (monthly amount: $5.00)
  
**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.

#### Evidence Summary
- **Kind**: canary_run  
  - **Summary**: Flask pattern fixture deployed on Ample; checks passed for bulk-import-staging and configuration-secrets.  
  - **Observed At**: 2026-09-21T01:14:18Z  
  - **Implementation Revision**: 50dbac567d2c5cc8e55e6c748a646be0025d9cfb-dirty  
  - **Expires At**: 2027-03-20T01:14:18Z

- **Kind**: canary_run  
  - **Summary**: The same Flask app deployed with a --release-command migration; the marker it created was readable after activation.
  - **Observed At**: 2026-09-20T01:54:51Z  
  - **Implementation Revision**: 199ff1dfd52683832ae75d3f98b53a7a4bff7f96-dirty  
  - **Expires At**: 2027-03-19T01:54:51Z

#### Known Unknowns
- Region availability is unknown until a verified region fact is recorded.
- Compliance attestations are unknown; none are claimed.

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