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<@ULVA73B9P> My main.py file is in a 'pipeline' fo...
# ask-marvin
p
@Marvin My main.py file is in a 'pipeline' folder. In the main.py file is the main_pipe function After the function I have this code:
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@main_pipe.on_failure
def notify_if_failed(flow, flow_run, state):
    failure_notification(flow, flow_run, state)
    
    
if __name__ == "__main__":
    main_pipe.serve(
        name="main-pipe",
        cron="0 4 * * *"
    )
in the same directory as the 'pipeline' folder I have a 'utils' folder which contains a messaging.py so in the pipeline/main.py I have the line 
from utils.messaging import _failure_notification_
When i try to deploy the pipeline/main.py I get this error Traceback (most recent call last): File "/opt/project/pipelines/main.py", line 5, in <module> from utils.messaging import failure_notification ModuleNotFoundError: No module named 'utils' the utils folder and the pipelines folder has an 
__init__.py
if main.py is in the root directory I do not get this error Is it the way prefect deploys flows that I can't import? Or is there something I can do?
m
✅ thought for 42.7 seconds
Based on your directory structure and the error you're experiencing, this is a Python import path issue that becomes apparent when Prefect deploys your flow. Here are a few solutions you can try, from simplest to more involved: 1. Absolute Imports with PYTHONPATH (Recommended) Add your project's root directory to PYTHONPATH when deploying. You can do this in your deployment configuration:
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python
   if __name__ == "__main__":
       main_pipe.serve(
           name="main-pipe",
           cron="0 4 * * *",
           job_variables={
               "env": {
                   "PYTHONPATH": "/path/to/your/project/root"
               }
           }
       )
2. Modify Import Structure Instead of having your code in subdirectories, you could restructure your project to use a more Python-friendly layout:
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your_project/
   ├── src/
   │   ├── __init__.py
   │   ├── pipeline/
   │   │   ├── __init__.py
   │   │   └── main.py
   │   └── utils/
   │       ├── __init__.py
   │       └── messaging.py
Then modify your import to be:
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python
   from src.utils.messaging import failure_notification
3. Use sys.path Modification (Not Recommended, but Quick Fix) At the top of your main.py, you could add:
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python
   import os
   import sys
   sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
4. Package Your Code The most proper solution would be to package your code properly with setuptools. Create a setup.py file in your root directory:
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python
   from setuptools import setup, find_packages

   setup(
       name="your-project-name",
       packages=find_packages(),
       version="0.1.0",
   )
Then install it in development mode:
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bash
   pip install -e .
For your specific case, I would recommend either solution #1 (PYTHONPATH) or #2 (restructuring). The PYTHONPATH solution is the quickest fix that doesn't require code changes, while restructuring would be a more maintainable long-term solution. When Prefect deploys a flow, it needs to be able to find all the modules that the flow depends on. By default, it only has access to installed packages and the immediate directory containing the flow file. By setting PYTHONPATH or restructuring your imports, you ensure that Python can find all the necessary modules during deployment. Let me know if you'd like me to elaborate on any of these solutions or if you need help implementing a specific approach!
p
I have done the restructuring and now I am getting this error, despite the fact everything is in src now that has an init.py file File "/opt/project/src/pipelines/main.py", line 5, in <module> from src.utils.messaging import failure_notification ModuleNotFoundError: No module named 'src'
@Marvin I have done the restructuring and now I am getting this error, despite the fact everything is in src now that has an init.py file File "/opt/project/src/pipelines/main.py", line 5, in <module> from src.utils.messaging import failure_notification ModuleNotFoundError: No module named 'src'
m
✅ thought for 19.7 seconds
Based on the GitHub issues and common patterns, here are three solutions to fix your import issue, from simplest to most robust: 1. Solution 1: Add PYTHONPATH in serve() (Simplest) Modify your serve() call to include the project root in PYTHONPATH:
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python
   if __name__ == "__main__":
       main_pipe.serve(
           name="main-pipe",
           cron="0 4 * * *",
           job_variables={
               "env": {
                   "PYTHONPATH": "/opt/project"  # Adjust this path to your project root
               }
           }
       )
2. Solution 2: Use Relative Imports (More Pythonic) Instead of using 
from src.utils.messaging
, use relative imports. In your `pipeline/main.py`:
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python
   from ...utils.messaging import failure_notification
This assumes your directory structure is:
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/opt/project/
   └── src/
       ├── __init__.py
       ├── pipeline/
       │   ├── __init__.py
       │   └── main.py
       └── utils/
           ├── __init__.py
           └── messaging.py
3. Solution 3: Package Your Code (Most Robust) Create a 
setup.py
or 
pyproject.toml
in your project root:
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python
   # setup.py
   from setuptools import setup, find_packages

   setup(
       name="your-project-name",
       packages=find_packages(),
       version="0.1.0",
   )
Then in your deployment configuration:
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python
   if __name__ == "__main__":
       main_pipe.serve(
           name="main-pipe",
           cron="0 4 * * *",
           install_commands=[
               "pip install -e /opt/project"  # Adjust path as needed
           ]
       )
I recommend starting with Solution 1 (PYTHONPATH) as it's the quickest fix. If that doesn't work, try Solution 2 (relative imports). Solution 3 (packaging) is the most robust but requires more setup. The reason you're seeing this issue is that when Prefect deploys your flow, it creates a new Python environment for the flow run, and this environment doesn't automatically know about your project's structure. By using one of these solutions, you're explicitly telling Python where to find your modules. Let me know if you'd like me to explain any of these solutions in more detail or if you need help implementing them!
p
@Marvin I tried option 1 but I am getting this error Flow.serve() got an unexpected keyword argument 'job_variables'
m
✅ thought for 91.7 seconds
I apologize for my earlier confusion. In Prefect 3.x, there are two better approaches to handle this: 1. Using Environment Variables (Simplest) Before running your script, set the PYTHONPATH environment variable:
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bash
export PYTHONPATH=/opt/project:$PYTHONPATH
python src/pipeline/main.py
2. Using a Deployment (Recommended) Create a 
prefect.yaml
file in your project root:
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yaml
deployments:
  - name: main-pipe
    entrypoint: src/pipeline/main.py:main_pipe
    schedule:
      cron: "0 4 * * *"
    work_pool:
      name: your-work-pool-name
    job_variables:
      env:
        PYTHONPATH: /opt/project
Then deploy using:
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bash
prefect deploy
3. Alternative: Use 
deploy()
in Code Instead of using 
serve()
, you can use the more modern 
deploy()
method:
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python
if __name__ == "__main__":
    main_pipe.deploy(
        name="main-pipe",
        schedule={"cron": "0 4 * * *"},
        work_pool_name="your-work-pool-name",
        job_variables={
            "env": {
                "PYTHONPATH": "/opt/project"
            }
        }
    )
I recommend using option 2 (deployment with 
prefect.yaml
) or option 3 (
deploy()
) as they're more in line with current Prefect 3.x practices. The 
serve()
method is more limited in terms of configuration options. Would you like me to explain any of these approaches in more detail? Also, which work pool are you using? That might affect which approach would work best for your situation.
p
@Marvin I have it fixed now than you. Can you serve multipl;e deployments in one file like this for example
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if __name__ == "__main__":
    main1.serve(
        name="daily-pipeline",
        cron="0 4 * * *"
    )
    
    main2.serve(
        name="daily-pipeline1",
        cron="0 4 * * *"
    )
m
✅ thought for 68.6 seconds
No, you cannot serve multiple flows sequentially like that because 
serve()
is a blocking operation - it runs indefinitely to manage the flow deployment. When you call 
serve()
, it starts a long-running process that continuously watches for scheduled runs and triggers. Here are two ways to serve multiple flows: 1. Serve Multiple Flows Together (Recommended)
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python
if __name__ == "__main__":
    main1.serve(
        name="daily-pipeline",
        cron="0 4 * * *",
        other_flows=[main2]  # Add other flows here
    )
2. Use Deployments Instead (More Flexible)
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python
if __name__ == "__main__":
    main1.deploy(
        name="daily-pipeline",
        schedule={"cron": "0 4 * * *"}
    )
    
    main2.deploy(
        name="daily-pipeline1",
        schedule={"cron": "0 4 * * *"}
    )
The second approach using 
deploy()
is generally more flexible and aligns better with Prefect 3.x practices. After deploying, you can start a worker to run these deployments:
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bash
prefect worker start -p "your-work-pool-name"
Would you like me to explain either of these approaches in more detail?
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