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Hello - been trying to deploy a simple py script i...

marqeu

02/10/2025, 2:08 AM

Hello - been trying to deploy a simple py script in prefect cloud and keep getting this error. I have requirements txt as well and the flow works fine in local. Any ideas what I am missing? prefect.exceptions.ScriptError: Script at 'db_engine.py' encountered an exception: ModuleNotFoundError("No module named 'pandas'") @Marvin I also have the vairables:

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{
  "env": {
    "PREFECT_LOGGING_LEVEL": "INFO"
  },
  "pip_packages": [
    "prefect",
    "prefect-snowflake",
    "pandas",
    "snowflake-connector-python[pandas]"
  ]
}

Marvin

02/10/2025, 2:28 AM

It seems like you're facing a

ModuleNotFoundError

because the

pandas

module isn't available in your Prefect Cloud environment. Here's a concise breakdown of potential issues and solutions: 1. Environment Variables: The

pip_packages

environment variable you defined seems to have a typo. You listed

"pandassnowflake-connector-python[pandas]"

, which should likely be two separate packages:

"pandas"

and

"snowflake-connector-python[pandas]"

. Ensure your environment variable looks like this:

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json
   {
     "pip_packages": [
       "prefect",
       "prefect-snowflake",
       "pandas",
       "snowflake-connector-python[pandas]"
     ]
   }

2. Prefect Cloud Deployment: Make sure that your deployment configuration in Prefect Cloud is correctly set up to use these environment variables. You might need to verify that the environment is properly configured to install the required packages. 3. Deployment Process: Ensure that you are using the correct Prefect CLI commands to deploy your script. You can refer to the Prefect documentation for guidance on setting up your cloud infrastructure. If you've checked these and the issue persists, you might consider reaching out on Prefect's community forums or checking GitHub issues for similar problems.

Marvin

02/10/2025, 2:28 AM

It seems like you're facing a

ModuleNotFoundError

for the

pandas

module when deploying your script to Prefect Cloud, even though it works locally. Here are some potential reasons and solutions: 1. Environment Configuration: Ensure that your Prefect Cloud environment is correctly configured to include all necessary packages. The

pip_packages

you provided should be part of your deployment configuration in Prefect Cloud. Double-check that these packages are correctly specified in your deployment settings. 2. Deployment Method: Prefect 3.x has moved away from using agents and now uses workers and work pools. Ensure that your deployment is correctly set up with a worker that has access to the required packages. You might want to look into using the

prefect work-pool

CLI to manage this. 3. Infrastructure Provisioning: If you're using automatic infrastructure provisioning, ensure that you have the relevant cloud CLI libraries installed and authenticated with your cloud provider. This is necessary for Prefect to provision the infrastructure required to run your deployments. 4. Prefect 3.x Gotchas: Be aware of changes in Prefect 3.x, such as the replacement of agents with workers, and the use of

from_source

for deployments instead of previous methods. For more detailed guidance, you might find these resources useful: - Deploying in Prefect 3.x - Prefect's GitHub for deployment scripts If these suggestions don't resolve your issue, consider checking your deployment logs for more specific error messages or configurations that might be missing.

Marvin

02/10/2025, 2:29 AM

It appears the issue may stem from how your Prefect Cloud deployment is set up to handle package dependencies. Here are some insights and potential solutions: 1. Environment Variables: Ensure that the

pip_packages

environment variable is correctly configured in your deployment settings. It should be part of the YAML configuration or directly set in the UI for the deployment. 2. Requirements File: You can use a

requirements.txt

file to specify dependencies. Make sure this file is referenced correctly in your deployment configuration. Prefect Cloud allows you to specify this in the

prefect.yaml

under the

pull

step. 3. Managed Execution: If you're using managed execution, ensure that your dependencies are installed at runtime. Prefect Cloud's free tier has limitations on concurrency and work pools, so ensure your setup aligns with these restrictions. 4. Prefect Cloud Configuration: Double-check that your Prefect Cloud workspace and environment are correctly configured to use the specified packages. This includes ensuring that your workspace is authenticated properly and that the packages are accessible. For more detailed guidance, you might want to check the Prefect documentation on managed infrastructure examples and connecting to Prefect Cloud.

marqeu

02/10/2025, 2:42 AM

it seems to be working now. Thank you for the help!

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