Based on the research, I can tell you that there isn't currently a built-in way to automatically delete flows from the Prefect UI when they're removed from your prefect.yaml file. However, I can suggest a few approaches to manage this: 1. Manual API-based Solution: You could create a custom script that: - Reads your current prefect.yaml file - Queries the Prefect API to get all registered flows - Compares the two lists - Deletes flows that exist in the UI but not in your prefect.yaml 2. CI/CD Integration: You could integrate flow cleanup into your deployment pipeline, running the cleanup script after successful deployments. Here's a basic example of how you could implement this using the Prefect REST API:

python
from prefect.client import get_client
import yaml
import asyncio

async def cleanup_flows():
    async with get_client() as client:
        # Read flows from prefect.yaml
        with open("prefect.yaml", "r") as f:
            config = yaml.safe_load(f)
        
        # Get configured flow names from prefect.yaml
        configured_flows = set()
        for deployment in config.get("deployments", []):
            configured_flows.add(deployment.get("flow_name"))
        
        # Get all flows from the API
        flows = await client.read_flows()
        
        # Delete flows that aren't in prefect.yaml
        for flow in flows:
            if flow.name not in configured_flows:
                await client.delete_flow(flow.id)

# Run the cleanup
asyncio.run(cleanup_flows())

A few important notes: 1. Be cautious with automatic deletion scripts - make sure you have proper backups and testing in place. 2. Consider implementing a "dry run" mode that shows what would be deleted without actually deleting anything. 3. You might want to add additional safety checks, such as: - Only deleting flows that haven't run in X days - Only deleting flows matching certain naming patterns - Excluding certain flows from automatic deletion If you're interested in implementing this kind of solution, I can provide more detailed guidance on specific aspects you'd like to focus on.

Let me provide a more detailed example of how to implement a manual API-based solution for flow deletion. Here's a more comprehensive script that includes error handling, logging, and a dry-run mode: ```python import asyncio import yaml import logging from typing import Set, Optional from prefect.client import get_client from datetime import datetime, timedelta from uuid import UUID # Set up logging logging.basicConfig(level=logging.INFO) logger = logging.getLogger(name) class FlowCleanupManager: def __init__(self, yaml_path: str, dry_run: bool = True, inactive_days: Optional[int] = None): self.yaml_path = yaml_path self.dry_run = dry_run self.inactive_days = inactive_days def read_yaml_flows(self) -> Set[str]: """Read flow names from prefect.yaml""" try: with open(self.yaml_path, "r") as f: config = yaml.safe_load(f) configured_flows = set() for deployment in config.get("deployments", []): flow_name = deployment.get("flow_name") if flow_name: configured_flows.add(flow_name) logger.info(f"Found {len(configured_flows)} flows in {self.yaml_path}") return configured_flows except FileNotFoundError: logger.error(f"Could not find {self.yaml_path}") return set() except yaml.YAMLError as e: logger.error(f"Error parsing {self.yaml_path}: {e}") return set() async def should_delete_flow(self, flow, configured_flows: Set[str]) -> bool: """Determine if a flow should be deleted based on configuration""" # Check if flow is not in prefect.yaml if flow.name not in configured_flows: # If inactive_days is set, check last activity if self.inactive_days is not None: async with get_client() as client: # Get flow runs for this flow flow_runs = await client.read_flow_runs( flows=[flow.id], sort="-start_time", limit=1 ) if flow_runs: last_run = flow_runs[0] if last_run.start_time: cutoff_date = datetime.now() - timedelta(days=self.inactive_days) return last_run.start_time < cutoff_date # No runs found, consider it inactive return True return True return False async def cleanup_flows(self): """Main cleanup method""" configured_flows = self.read_yaml_flows() if not configured_flows: logger.error("No flows found in configuration. Aborting.") return async with get_client() as client: try: # Get all flows from the API flows = await client.read_flows() logger.info(f"Found {len(flows)} flows in Prefect server") for flow in flows: try: if await self.should_delete_flow(flow, configured_flows): if self.dry_run: logger.info(f"Would delete flow: {flow.name} (ID: {flow.id})") else: logger.info(f"Deleting flow: {flow.name} (ID: {flow.id})") await client.delete_flow(flow.id) except Exception as e: logger.error(f"Error processing flow {flow.name}: {e}") except Exception as e: logger.error(f"Error fetching flows: {e}") async def main(): # Initialize the cleanup manager manager = FlowCleanupManager( yaml_path="prefect.yaml",

dry_run=True, # Set to False to actually delete flows inactive_days=30 # Optional: Only delete flows inactive for 30 days ) await manager.cleanup_flows() if name == "__main__": asyncio.run(main())

This script includes several important features:

1. *Dry Run Mode*: By default, it runs in "dry run" mode, which shows what would be deleted without actually deleting anything.

2. *Inactivity Check*: You can specify `inactive_days` to only delete flows that haven't been run in a certain period.

3. *Error Handling*: Comprehensive error handling and logging for both YAML parsing and API operations.

4. *Logging*: Detailed logging of all operations and decisions.

To use this script:

1. Save it as `cleanup_flows.py`

2. Run it in dry-run mode first:
```bash
python cleanup_flows.py

3. When you're confident it's working correctly, modify the

dry_run

parameter to

False

in the script to perform actual deletions. You can customize the script further by: 1. Adding more filtering conditions:

python
async def should_delete_flow(self, flow, configured_flows: Set[str]) -> bool:
    # Add custom conditions, for example:
    if flow.name.startswith("test_"):  # Only delete test flows
        return True
    return False

2. Adding tags or other metadata checks:

python
# Check flow tags
if "do_not_delete" in flow.tags:
    return False

3. Adding backup functionality before deletion:

python
async def backup_flow(self, flow):
    # Implement flow backup logic here
    pass

Remember to: - Always test the script in dry-run mode first - Keep backups of your flow configurations - Consider implementing a restoration process - Add appropriate logging and monitoring - Consider rate limiting if you have many flows to delete Would you like me to elaborate on any particular aspect of this solution?