Added section to Python models doc to discuss third party packages following this the thread: https://dbt-labs.slack.com/archives/C05FWBP9X1U/p1730272033637189

[nataliefiann]

What are you changing in this pull request and why?

I have added a section to the Python models doc to discuss third party packages following this the thread: https://dbt-labs.slack.com/archives/C05FWBP9X1U/p1730272033637189

Checklist

• I have reviewed the Content style guide so my content adheres to these guidelines.
• The topic I'm writing about is for specific dbt version(s) and I have versioned it according to the version a whole page and/or version a block of content guidelines.
• I have added checklist item(s) to this list for anything anything that needs to happen before this PR is merged, such as "needs technical review" or "change base branch."
• The content in this PR requires a dbt release note, so I added one to the release notes page.

---

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[b-per]

Thanks! I think that overall this is the way we should show it and point to the relevant docs but I am just wondering if the example we show is the best one.

Most people will want to upload Python packages so that they can call their favorite functions. In this example we are currently loading a CSV file. It works but it is not going to be the reason why people will want to use the imports config and load it from a Snowflake stage.

[nataliefiann]

Hiya @mirnawong1 and @b-per

Thank you for reviewing this. It's much appreciated.

@b-per with ref to your feedback, I found the below example in the Snowflake doc which gives an example of installing a package with native code via importing from Stage. Would you recommend using this instead:

create or replace function native_module_test_zip()
returns string
language python
runtime_version=3.9
handler='compute'
imports=('@mystage/mycustompackage.zip')
as
$$
import os
import sys
def compute():
   from zipfile import ZipFile
   if os.path.exists('/tmp/mycustompackage'):
      shutil.rmtree('/tmp/mycustompackage')
   os.mkdir('/tmp/mycustompackage')
   zippath = os.path.join(sys._xoptions["snowflake_import_directory"], 'mycustompackage.zip')
   ZipFile(zippath).extractall('/tmp/mycustompackage')
   sys.path.insert(0, '/tmp/mycustompackage')
   #return os.listdir('/tmp/mycustompackage')
   import mycustompackage
   return mycustompackage.mycustompackage()
$$;

Kind Regards
Natalie

[b-per]

Yes, this looks much closer to what people might do! We just need to update it to make it a valid dbt model.

[nataliefiann]

Thanks @b-per

I did a little research and came upon this example:

{{ config(
    materialized = 'view'
) }}

create or replace function native_module_test_zip()
returns string
language python
runtime_version=3.9
handler='compute'
imports=('@mystage/mycustompackage.zip')
as
$$
import os
import sys
from zipfile import ZipFile
import shutil

def compute():
   if os.path.exists('/tmp/mycustompackage'):
      shutil.rmtree('/tmp/mycustompackage')
   os.mkdir('/tmp/mycustompackage')
   zippath = os.path.join(sys._xoptions["snowflake_import_directory"], 'mycustompackage.zip')
   ZipFile(zippath).extractall('/tmp/mycustompackage')
   sys.path.insert(0, '/tmp/mycustompackage')
   
   # Import and call the function from mycustompackage
   import mycustompackage
   return mycustompackage.mycustompackage()
$$;

Would that suffice?

Kind Regards

[b-per]

I don't think so, no. This is not a valid dbt Python model.

There are a few things to change. Our docs describe what a Python model needs to have (for example a def model())

[nataliefiann]

Querying example here: https://dbt-labs.slack.com/archives/C05FWBP9X1U/p1730894409078339

[nataliefiann]

Hiya @mirnawong1 @b-per

I'm currently querying this in ask-adapters-support. I found this example:

def model(dbt, session):
    # Configure the model
    dbt.config(
        materialized="table",
        imports=["@mystage/mycustompackage.zip"],  # Specify the external package location
    )
    
    # Example data transformation using the imported package
    # (Assuming `some_external_package` has a function we can call)
    data = {
        "name": ["Alice", "Bob", "Charlie"],
        "score": [85, 90, 88]
    }
    df = pd.DataFrame(data)

    # Process data with the external package
    df["adjusted_score"] = df["score"].apply(lambda x: some_external_package.adjust_score(x))
    
    # Return the DataFrame as the model output
    return df

Mike Alfare advised: "I think mycustompackage.zip might need to be some_external_package.py. To be honest, this is not something I have seen before, but reviewing our functional tests, it seems like this could work. I'll see if I can find someone more familiar with this particular feature."

I thought I'd share here incase you had any ideas.

Kind Regards
Natalie