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<@ULVA73B9P> What is best practice for maintaining...
# ask-marvin
m
@Marvin What is best practice for maintaining a running worker on a local machine (laptop)? I find that when I start a worker in a local process and it loses interned connection the worker crashes.
m
There appears to be an error with searching the documentation, and no GitHub issues were found related to your problem. However, I can provide general best practices for maintaining a running worker on a local machine: 1. Daemonize the Worker Process: Run the worker as a background daemon to ensure it restarts automatically if it crashes. Tools like systemd on Linux or launchd on macOS can help manage this. 2. Use a Supervisor: Use a process management tool like 
supervisord
to automatically restart the worker in case it crashes or loses connection. 3. Network Stability: Ensure a stable network connection to minimize disconnections. If operating in environments where disconnections are frequent, consider running the worker on a different machine with a more stable connection. 4. Error Handling: Implement robust error handling within your worker configuration to gracefully handle connection losses and attempt reconnections. 5. Logging and Monitoring: Implement comprehensive logging and monitoring to be alerted to worker crashes and automatically attempt recovery. 6. Run in a Docker Container: Use Docker to isolate the worker and manage its lifecycle more effectively. Docker can restart the container if it crashes. These are general practices that can help maintain a stable working environment for your Prefect worker. Since there was an error in fetching the documentation, you may want to directly consult the official Prefect documentation or reach out to the Prefect community for more specific guidance.
m
How do I configure worker?
@Marvin How do I configure worker?
m
It seems the code example retrieved is not directly related to configuring a worker. Please disregard it. Let's detail the steps and necessary code to configure a worker in Prefect. 1. Install Prefect if you haven't already:
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pip install prefect
2. Start a Worker: You can start a worker using the CLI or within Python code. Using CLI:
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prefect worker start --pool default-agent-pool
Using Python:
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python
   from prefect.deployments import run_deployment

   deployment = Deployment.build_from_flow(
       flow=my_flow,
       name="my_deployment"
   )
   deployment.apply()

   run_deployment(name="my_deployment/my_flow")
3. Configure Worker Settings: Prefect workers can be configured using environment variables or within your 
prefect.yaml
configuration file. Here is an example of configuring using environment variables:
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bash
   export PREFECT_API_URL="<http://localhost:4200/api>"
   export PREFECT_LOGGING_LEVEL="INFO"
If you’re using a 
prefect.yaml
configuration file, here’s how you might set it up:
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yaml
   version: 2
   logging:
     level: INFO

   workers:
     - type: process
       work_queue: default
       concurrency: 4
4. Run as a Daemon or Supervisor Process: If you want to ensure your worker is always running, you might use 
supervisord
, 
systemd
, or Docker. Example with Docker: Create a `Dockerfile`:
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Dockerfile
FROM python:3.9

RUN pip install prefect

COPY . /app
WORKDIR /app

CMD ["prefect", "worker", "start", "--pool", "default-agent-pool"]
Then build and run your Docker container:
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bash
docker build -t prefect-worker .
docker run -d --name prefect-worker prefect-worker
These steps should help you to configure and keep your Prefect worker running smoothly. For more detailed configurations, you may need to consult the Prefect documentation.
m
@Marvin is there a way to configure a worker to poll less often?
m
You can indeed configure the polling interval for a Prefect worker, though there doesn't seem to be direct documentation, recent pull requests give us clues about how this is implemented. For instance, the 
BaseWorker
and related classes manage mechanics like polling. It can be expected that any configurable polling intervals or related settings would be exposed either via environment variables or worker configuration parameters. Given the pull requests and related issues, here are steps to change the polling interval: ### Using Environment Variables Prefect often uses environment variables for configuration. Check for any environment variables that might influence the polling frequency, though specific details were not provided in the available data:
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bash
export POLLING_INTERVAL="60"  # Hypothetical environment variable for demonstration
### Using Worker Configuration Prefect's worker configuration might allow setting the polling frequency. Look at starting a worker, ensuring it has any updated settings: 1. Configure Worker Settings: You can extend the worker configuration to handle polling intervals—adding relevant params if supported: Example 
prefect.yaml
:
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yaml
    version: 2
    logging:
      level: INFO

    workers:
      - type: process
        work_queue: default
        concurrency: 4
        polling_interval: 60  # Hypothetical configuration
2. Starting the Worker with Custom Config:
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bash
    prefect worker start --pool default-agent-pool --poll-interval 60
### Using Code/Modifications If undocumented, as temporary: Modify 
worker.py
scripts to adjust intervals:
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python
class CustomWorker(BaseWorker):
    def __init__(self, interval=30):
        super().__init__()
        self.polling_interval = interval

    def start(self):
        while True:
            self.poll()
            time.sleep(self.polling_interval)

worker = CustomWorker(interval=60)  # Adjust the interval as needed
worker.start()
### Closing Notes While polling less frequently reduces resource use, it also delays reaction to queued tasks. Adjust based on workload demands. Given potential undocumented aspects, verifying through Prefect docs/community might be ideal: Prefect Documentation
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