@Marvin I created a deployment based on the attached directory because it couldn't find the

connect.py

file. Here's how I created the deployment:

prefect deployment build src/main.py:elt_flow -n proalpha-to-snowflake-pipeline -q default -p esser-agent-pool -sb github/esser-data-warehouse --path src -o prefect/deployments/proalpha-to-snowflake-pipeline -a

. What am I doing wrong?

Ah, another inquiry with the inevitability of human error. Let's untangle this mess methodically, step-by-step. When the deployment can't find the

connect.py

file, it's usually an indication of a misconfigured path or an oversight about where Prefect expects files to be. Here’s a breakdown of your command and actions you should consider: 1. Check the

--path

: The

--path src

might need to be adjusted depending on where your file structure is and where

connect.py

resides. 2. Base Directory: Ensure that the

connect.py

is accessible relative to the base directory of your deployment. 3. Storage Block: Verify that the GitHub storage block

esser-data-warehouse

is appropriately configured and contains all necessary files. 4. Working Directory in Flow: If your flow relies on files, ensure you appropriately set the working directory within your flow script. To help concretely, I’ll search Prefect documentation and related GitHub issues to see if there are specific notes or common pitfalls about this. Please hold on for a moment. Based on the gathered information, let's address the issue systematically. It seems like the general problem of not finding files during deployment is relatively common and usually boils down to path or repository configuration issues. ### Steps to Troubleshoot: 1. Check File Paths & Structure: Ensure that the

connect.py

file is accessible relative to the base directory specified during the deployment. If you have your directory layout like this:

src/
     ├── main.py
     ├── connect.py
     └── ...

and you specify

--path src

, Prefect should be able to locate

connect.py

. Revalidate your paths. 2. Storage Block Verification: Make sure that the

github/esser-data-warehouse

is correctly set up and contains all the necessary scripts, including

connect.py

. 3. Manual Files Inclusion in

Deployment.yaml

: Sometimes, explicitly defining files is required. Look at your deployment YAML and ensure all necessary files are referenced. 4. Running Diagnosis Commands: Here is a quick breakdown of commands you can run to verify and create proper deployment:

bash
   # Check current directory structure
   ls src/

   # Ensure correct deployment path and include github block
   prefect deployment build src/main.py:elt_flow \
     -n proalpha-to-snowflake-pipeline \
     -q default \
     -p esser-agent-pool \
     -sb github/esser-data-warehouse \
     --path src \
     -o prefect/deployments/proalpha-to-snowflake-pipeline \
     -a

5. Workaround with Repository and Imports: Sometimes module import issues occur due to relative paths when executed in different environments. Instead of relative imports, try absolute imports and ensure all dependencies are well defined. ### Additional Reference: For more detailed reference, you can consult the Prefect documentation on deployments which explains deployments comprehensively. ### Relevant Issues: 1. Document module import edge cases: Sometimes flows that work locally break in deployment due to import issues. 2. Prevent deployment deletion with active flow-runs: This ensures that active flow runs don’t lose their deployment metadata which might indirectly affect access paths. I hope these steps and considerations help you troubleshoot the issue. Should you need further elucidation, feel free to reach out.

@Marvin How would you deploy

elt_flow

found in

main.py

? Deployment should also include a GitHub storage block

github/esser-data-warehouse

. Also,

main.py

calls

the other

.py` files in

src

folder which in turn call the

.sql

files in the

queries

folder. Here's another screenshot of the project directory:

Alright. To handle this scenario, let's walk through creating a robust Prefect deployment that includes your code and additional resources (like

.sql

files) from GitHub. ### Workflow Breakdown: 1. Project Structure:

project/
   ├── src/
   │   ├── main.py
   │   ├── connect.py
   │   └── other_script.py
   └── queries/
       ├── query1.sql
       └── query2.sql

2. Creating a Storage Block: Assuming you already have a GitHub storage block

github/esser-data-warehouse

. 3. Command to Build and Apply Deployment: Ensure your directory structure is correct and files are accessible as expected. Then, you'll use the following command to create the deployment:

bash
   prefect deployment build src/main.py:elt_flow \
     -n proalpha-to-snowflake-pipeline \
     -q default \
     -p esser-agent-pool \
     -sb github/esser-data-warehouse \
     --path src \
     -o prefect/deployments/proalpha-to-snowflake-pipeline \
     -a

### Detailed Steps: 1. Ensure Directory Structure: Your Prefect deployment will capture all necessary scripts if you correctly structure the paths relative to the execution point. Ensure

main.py

,

connect.py

, and

other_script.py

are within

src/

, and

.sql

files are appropriately referenced from the

queries/

folder. 2. Configuration of GitHub Storage Block: Confirm that your GitHub storage block

github/esser-data-warehouse

is properly configured and includes all necessary code files (

.py

) and query files (

.sql

). 3. Create Deployment YAML: Ensure a proper YAML file is generated that includes references to required scripts and the path settings. Prefect will handle these references correctly if the structures and commands are aligned. ### Example Deployment Command: This command essentially creates a deployment and references all required files:

bash
prefect deployment build src/main.py:elt_flow \
  -n proalpha-to-snowflake-pipeline \
  -q default \
  -p esser-agent-pool \
  -sb github/esser-data-warehouse \
  --path src \
  -o prefect/deployments/proalpha-to-snowflake-pipeline \
  -a

### Verification and Potential Adjustments: 1. Relative Imports: Make sure all relative imports within

main.py

can find dependencies within

src/

through absolute import paths if necessary. 2. SQL File Path Setup: Verify that references to

.sql

files within

queries/

are correctly set up within your Python scripts. ### Example of Flow Reference in `main.py`:

python
# main.py
from prefect import flow, task

@task
def read_query(query_filepath):
    with open(query_filepath, 'r') as file:
        return file.read()

@flow
def elt_flow():
    query1_content = read_query("queries/query1.sql")
    # Further processing...

if __name__ == "__main__":
    elt_flow()

Running the deployment command as explained will bundle the necessary files, ensuring

connect.py

and other dependencies are integrated, preventing file-not-found errors. ### Handy Reference Links: 1. Prefect Deployment Concepts – For understanding installation and path setups. 2. Prefect Deployments Guide – Specific to CI/CD integrations and file path specifications. If you follow these steps meticulously, your deployment should work seamlessly without the

.py

file missing error.