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353 new member field breaks create joined timeseries on existing datasets #355

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353 new member field breaks create joined timeseries on existing datasets #355

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ac6f8f5
adds `add_missing_columns` arg to _validate()
mgdenno Dec 18, 2024
1bb0e14
updates change log and version to 0.4.6
mgdenno Dec 18, 2024
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22 changes: 20 additions & 2 deletions src/teehr/evaluation/tables/base_table.py
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Original file line number Diff line number Diff line change
Expand Up @@ -10,6 +10,7 @@
from teehr.utils.utils import to_path_or_s3path, path_to_spark
from teehr.models.filters import FilterBaseModel
import logging
from pyspark.sql.functions import lit, col

logger = logging.getLogger(__name__)

Expand Down Expand Up @@ -145,7 +146,12 @@ def _get_schema(self, type: str = "pyspark"):

return self.schema_func()

def _validate(self, df: ps.DataFrame, strict: bool = True) -> ps.DataFrame:
def _validate(
self,
df: ps.DataFrame,
strict: bool = True,
add_missing_columns: bool = False
) -> ps.DataFrame:
"""Validate a DataFrame against the table schema.

Parameters
Expand All @@ -156,13 +162,25 @@ def _validate(self, df: ps.DataFrame, strict: bool = True) -> ps.DataFrame:
If True, any extra columns will be dropped before validation.
If False, will be validated as-is.
The default is True.

Returns
-------
validated_df : ps.DataFrame
The validated DataFrame.
"""
schema = self._get_schema()

logger.info(f"Validating DataFrame with {schema.columns}.")

schema_cols = schema.columns.keys()

# Add missing columns
if add_missing_columns:
for col_name in schema_cols:
if col_name not in df.columns:
df = df.withColumn(col_name, lit(None))
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just to make sure I understand, here we're adding an empty column(s) (column names that exist in the schema but not dataframe), then in line 186 it coerces the empty column(s) to the correct data type as defined by the schema?


if strict:
schema_cols = schema.columns.keys()
df = df.select(*schema_cols)

validated_df = schema.validate(df)
Expand Down