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Improve column-didn't-generate error message #95

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Improve column-didn't-generate error message #95

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32 changes: 21 additions & 11 deletions dbt2looker/generator.py
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Original file line number Diff line number Diff line change
Expand Up @@ -195,32 +195,42 @@ def normalise_spark_types(column_type: str) -> str:
return re.match(r'^[^\(]*', column_type).group(0)


def map_adapter_type_to_looker(adapter_type: models.SupportedDbtAdapters, column_type: str):
def map_adapter_type_to_looker(adapter_type: models.SupportedDbtAdapters, column_type: str, column_name: str = None):
normalised_column_type = (normalise_spark_types(column_type) if adapter_type == models.SupportedDbtAdapters.spark.value else column_type).upper()
looker_type = LOOKER_DTYPE_MAP[adapter_type].get(normalised_column_type)
if (column_type is not None) and (looker_type is None):
logging.warning(f'Column type {column_type} not supported for conversion from {adapter_type} to looker. No dimension will be created.')
if column_name:
warning_start = f'For column {column_name}, c'
else:
warning_start = 'C'
logging.warning(
warning_start
+ f'olumn type {column_type} is not supported for conversion from {adapter_type} to looker. '
+ 'No dimension will be created.'
)
return looker_type


def lookml_date_time_dimension_group(column: models.DbtModelColumn, adapter_type: models.SupportedDbtAdapters):
col_name = column.meta.dimension.name or column.name
return {
'name': column.meta.dimension.name or column.name,
'name': col_name,
'type': 'time',
'sql': column.meta.dimension.sql or f'${{TABLE}}.{column.name}',
'description': column.meta.dimension.description or column.description,
'datatype': map_adapter_type_to_looker(adapter_type, column.data_type),
'datatype': map_adapter_type_to_looker(adapter_type, column.data_type, col_name),
'timeframes': ['raw', 'time', 'hour', 'date', 'week', 'month', 'quarter', 'year']
}


def lookml_date_dimension_group(column: models.DbtModelColumn, adapter_type: models.SupportedDbtAdapters):
col_name = column.meta.dimension.name or column.name
return {
'name': column.meta.dimension.name or column.name,
'name': col_name,
'type': 'time',
'sql': column.meta.dimension.sql or f'${{TABLE}}.{column.name}',
'description': column.meta.dimension.description or column.description,
'datatype': map_adapter_type_to_looker(adapter_type, column.data_type),
'datatype': map_adapter_type_to_looker(adapter_type, column.data_type, col_name),
'timeframes': ['raw', 'date', 'week', 'month', 'quarter', 'year']
}

Expand All @@ -229,13 +239,13 @@ def lookml_dimension_groups_from_model(model: models.DbtModel, adapter_type: mod
date_times = [
lookml_date_time_dimension_group(column, adapter_type)
for column in model.columns.values()
if map_adapter_type_to_looker(adapter_type, column.data_type) in looker_date_time_types
if map_adapter_type_to_looker(adapter_type, column.data_type, column.name) in looker_date_time_types
]
dates = [
lookml_date_dimension_group(column, adapter_type)
for column in model.columns.values()
if column.meta.dimension.enabled
and map_adapter_type_to_looker(adapter_type, column.data_type) in looker_date_types
and map_adapter_type_to_looker(adapter_type, column.data_type, column.name) in looker_date_types
]
return date_times + dates

Expand All @@ -244,19 +254,19 @@ def lookml_dimensions_from_model(model: models.DbtModel, adapter_type: models.Su
return [
{
'name': column.meta.dimension.name or column.name,
'type': map_adapter_type_to_looker(adapter_type, column.data_type),
'type': map_adapter_type_to_looker(adapter_type, column.data_type, column.name),
'sql': column.meta.dimension.sql or f'${{TABLE}}.{column.name}',
'description': column.meta.dimension.description or column.description,
**(
{'value_format_name': column.meta.dimension.value_format_name.value}
if (column.meta.dimension.value_format_name
and map_adapter_type_to_looker(adapter_type, column.data_type) == 'number')
and map_adapter_type_to_looker(adapter_type, column.data_type, column.name) == 'number')
else {}
)
}
for column in model.columns.values()
if column.meta.dimension.enabled
and map_adapter_type_to_looker(adapter_type, column.data_type) in looker_scalar_types
and map_adapter_type_to_looker(adapter_type, column.data_type, column.name) in looker_scalar_types
]


Expand Down