Issue when parsing dbt models

Hey folks!

I’ve just run ‘dbt2looker’ in my local dbt repo folder, and I receive the following error:

❯ dbt2looker
12:11:54 ERROR  Cannot parse model with id: "model.smallpdf.brz_exchange_rates" - is the model file empty?
Failed

The model file itself (pictured below) is not empty, therefore I am not sure what the issue with parsing this model dbt2looker appears to have. It is not materialised as a table or view, it is utilised by dbt as ephemeral - is that of importance when parsing files in the project? I’ve also tried running dbt2looker on a limited subset of dbt models via a tag, the same error appears. Any help is greatly appreciated!

Other details:

• on dbt version dbt 1.0.0
• using dbt-redshift adapter dbt-redshift@1.0.0
• let me know if anything else is of importance!

[boludo00]

So yesterday I was modding the code and was able to get past the - is the model file empty? error.

Since the parser uses the manifest.json file, a node has its materialization in the config object:

"config": {
    "enabled": true,
    "alias": null,
    "schema": "staging",
    "database": null,
    "tags": [],
    "meta": {},
    "materialized": "ephemeral",
    "persist_docs": {},
    "quoting": {},
    "column_types": {},
    "full_refresh": null,
    "on_schema_change": "ignore",
    "bind": false,
    "post-hook": [],
    "pre-hook": []
},

If the DbtNode changes to:

class DbtNode(BaseModel):
    unique_id: str
    resource_type: str
    config: Dict[str, Any]

then the parse_models() method could be modified to:

def parse_models(raw_manifest: dict, tag=None) -> List[models.DbtModel]:
    manifest = models.DbtManifest(**raw_manifest)
    all_models: List[models.DbtModel] = [
        node
        for node in manifest.nodes.values()
        if node.resource_type == 'model' and node.config['materialized'] != 'ephemeral'
    ]

    # Empty model files have many missing parameters
    for model in all_models:
        if not hasattr(model, 'name'):
            logging.error('Cannot parse model with id: "%s" - is the model file empty?', model.unique_id)
            raise SystemExit('Failed')

    if tag is None:
        return all_models
    return [model for model in all_models if tags_match(tag, model)]

which should ensure the list of models only contains DbtModel instances. This might be overkill as a solution and maybe even not the intended effect but it solve those issues for me. Also make sure to dbt build any models that are resulting in that error before you run dbt docs generate.

[dduran28]

@lewisosborne I was running into the same issue, I bypassed it by deleting that ephemeral tag at the top and then re-running dbt docs generate and then the subsequent dbt2looker command. That gets me passed the initial error highlighted here.

I am running into a different error afterwards where I am seeing not supported for conversion from redshift to looker for all of my data types but maybe we can tackle that one separately.

Let me know if my initial suggestion gets you past the issue with the ephemeral model.