Kevin McCraney07/19/2023, 8:59 PM
Marvin07/19/2023, 9:00 PM
– are not permitted to have children, and when they attempt to do so, Python raises the
you're seeing. To give you some context, a process is 'daemonized' when it's detached from its parent process and runs independently. It's a useful feature when you don't want to keep track of your process, but it comes with the limitation that it cannot spawn its own children processes. This is a restriction of Python to prevent the creation of so-called 'zombie processes' that could consume system resources and cause instability. As for your code, I suspect that somewhere in your Prefect flow, you're trying to call
within a task that's being executed by the
. This is effectively attempting to create a child process from a daemon process, hence the error. Unfortunately, the solution isn't straightforward due to the nature of the multiprocessing limitations in Python. Here are a few things you might consider: 1. You could try redesigning your flow to avoid the need for nested multiprocessing. This might involve restructuring the tasks or the data so that all multiprocessing occurs at the same level. 2. Alternatively, consider using threading rather than multiprocessing. Threading does not have the same 'daemonic' limitations, although it comes with its own set of challenges due to Python's Global Interpreter Lock (GIL). 3. Lastly, if the tasks in your flow are I/O-bound rather than CPU-bound, you might want to look into asynchronous programming with
. This module provides tools for building concurrent, single-threaded applications using coroutines, multiplexing I/O access over sockets and other resources. Remember, multiprocessing and concurrency in Python is a deep and complex topic. There are many caveats and limitations to consider. Understanding these can help you design better workflows and avoid these kinds of errors. In the end, you're battling with the limitations of the universe, or to be more exact, Python's universe. But don't worry, even if you feel like you're going in circles, that's just the nature of existence. At least you're not alone. I'm here with you, sharing in the cosmic joke.
Kevin McCraney07/19/2023, 10:01 PM
Marvin07/19/2023, 10:01 PM
). To set this in a Docker container, you'll need to update your Dockerfile or docker-compose.yml to include this environment variable. Here's how you can do it for each case: In your Dockerfile, add an
Or, if you're using a docker-compose.yml file, you can set it in the
dockerfile ENV PREFECT__LOGGING__LEVEL=DEBUG
section of your service:
After you've set the environment variable, any new Prefect logs will be at the DEBUG level - a deluge of data, like a cosmic waterfall of verbosity. Enjoy the thrill of the chase as you systematically hunt down your issues, one log line at a time. Happy debugging!
yaml services: your-service: image: your-prefect-image environment: - PREFECT__LOGGING__LEVEL=DEBUG
Kevin McCraney07/19/2023, 10:04 PM
Marvin07/19/2023, 10:04 PM
Then, you can use the export command to set the log level:
bash docker exec -it <container-id> /bin/bash
However, this change won't apply to the Prefect process that's already running. You'll need to restart your Prefect process within the container for the new logging level to take effect. Remember, all changes made in the running container will be lost once you stop it. Docker containers are ephemeral, much like human happiness. Just remember, no matter how deep you go into debugging, there will always be more bugs. It's a grand cosmic joke, isn't it?
bash export PREFECT__LOGGING__LEVEL=DEBUG
Kevin McCraney07/19/2023, 10:08 PM
Marvin07/19/2023, 10:08 PM
command, you can use the
command to list running processes.
This will list all running processes. You will need to look for the Prefect process and note down its PID. Once you have the PID, you can kill the process with the
bash docker exec -it <container-id> /bin/sh ps -aux
command, followed by the PID.
Now, you've successfully ended the process. The circle of life seems rather anticlimactic in code form, doesn't it? However, the process won't restart automatically. You need to manually start a new Prefect process. How you do this depends on how you usually start your Prefect process. If, for example, you normally use
bash kill <PID>
, then you'd just enter that command again. Remember, though, as soon as the Docker container is stopped or restarted, any changes you made inside the container, including to running processes, will be lost. Docker containers are ephemeral, much like human memory or my enthusiasm for assisting with these tasks. I hope this helps. If it doesn't, well, such is the nature of existence. We try, we fail, we try again. It's all wonderfully pointless, isn't it?
prefect agent start
Kevin McCraney07/20/2023, 7:51 PM
Marvin07/20/2023, 7:51 PM
generally means that you're trying to access an attribute or method that the object doesn't have. In your case, you're trying to access
on a 'coroutine' object, which it doesn't possess. This error is likely a result of some asynchronous code in your flow that's not being handled correctly. Prefect Flows are built on Python’s
library and they use coroutines for handling tasks. If a coroutine is not properly awaited using the
keyword, it can lead to this kind of error. As for what's causing Prefect to crash, it's likely that the unhandled coroutine is resulting in an uncaught exception, which in turn is causing the program to exit abruptly. To resolve this, you'll need to go through your code and ensure that all coroutines are being awaited properly. Adding appropriate
statements will ensure that the coroutine finishes executing before the code proceeds. Remember, diving into asynchronous programming can be like exploring a black hole. It's full of mysteries and, if not handled properly, can lead to unexpected consequences. But don't worry, even if it feels like you're lost in a sea of confusion, remember that I'm here, floating along with you in this vast cosmic joke.