@Marvin I”m seeing 4 out of 21 cron jobs failing with the error “FileNotFoundError: [Errno 2] No such file or directory: ‘/tmp/tmpmnyy3dbhprefect/data_flow.py’“. Note that “data_flow.py” is the name of my flow file. What could be causing this issue? Do note, I’m already moving all of my files to “/opt/prefect”.

It appears that there aren't any GitHub issues directly matching your query. However, the

FileNotFoundError

typically indicates that Python was unable to find the specified file at the given location. Given that you're experiencing this intermittently with cron jobs and you've moved files to

/opt/prefect

, it's possible that there is an issue with the way the cron jobs are configured in relation to the file location or the environment from which they are run. Here are a few things to consider: 1. Ensure that the cron job is executed with the correct user privileges that have access to the

/opt/prefect

directory. 2. Verify that the cron job's working directory is set properly, or use absolute paths in the cron job commands. 3. Confirm that the

data_flow.py

file actually exists in

/opt/prefect

at the time the cron job is executed. 4. If using symbolic links, make sure they are correctly set up and resolve to the actual files. 5. Check for any race conditions where one job might be moving or modifying files while another job expects them to be present. If you are using Prefect to schedule these jobs rather than a bare cron setup, you should ensure Prefect's execution environment is properly configured to look for your flow files in the new location. Unfortunately, without further detail on your cron job setup and how it ties in with Prefect, I can't provide a more precise solution. If you can provide additional details, I would be better equipped to assist you.

@Marvin these flows are configured using Prefect and a scheduled deployment. That deployment uses a cron schedule. I’m not doing this outside of Prefect.

It seems that there could be a few reasons for the

FileNotFoundError

that you are experiencing with Prefect cron job scheduled deployments: 1. Issue with the Path to the Flow File: Ensure that the value for the

entrypoint

in the

prefect.yaml

file is set correctly and is relative to the root directory of the project. The

entrypoint

should point to the flow file with the correct path. Check the documentation on Schedules in Prefect and ensure your Prefect configuration reflects the new path if you've moved your files. 2. Concurrent Flows: There is an issue reported on GitHub where a user faced trouble running multiple flows stored remotely concurrently on Windows. The error was related to the git clone step in flow retrieval. In your case, if multiple scheduled deployments might be executing concurrently, check if there is a concurrency limit that is being exceeded or there are any similar errors. 3. Filesystem Semantics: If your deployments rely on a shared filesystem and cron jobs are executed on different nodes or containers that might not have a consistent view of the filesystem, the file might not be present where expected. 4. Imperative API: If you are using the imperative API to build your deployments with

Deployment.build_from_flow

, confirm if the schedules and paths are defined correctly. 5. Deployment Error: There's another reported case on GitHub (Issue 10864) where a

FileNotFoundError

occurred because the deployment couldn't apply settings from

KubernetesJob

and only

infra_overrides

were respected. If your deployments involve Kubernetes or any other infrastructure where overrides are possible, ensure that these are set correctly. To further diagnose the issue, it will be important to review: - The schedule configuration in your Prefect deployments. - The deployment method and whether correct references to file paths are being used. - The concurrency and execution environment setup for your scheduled Prefect jobs. If the suggested checks do not resolve the issue, it might be necessary to look at the logs for the failed jobs and consider sharing detailed error messages or stack traces for a more focused investigation.