refactor: display key fields in error reports as individual columns

src/dve/core_engine/backends/utilities.py

@@ -176,3 +176,8 @@ def get_polars_type_from_annotation(type_annotation: Any) -> PolarsType:
         if polars_type:
             return polars_type
     raise ValueError(f"No equivalent DuckDB type for {type_annotation!r}")
+
+
+def pl_row_count(df: pl.DataFrame) -> int:  # type: ignore
+    """Return row count from a polars DataFrame object."""
+    return df.select(pl.len()).to_dicts()[0]["len"]  # type: ignore

src/dve/pipeline/pipeline.py

@@ -34,7 +34,7 @@
 from dve.parser.file_handling.service import _get_implementation
 from dve.pipeline.utils import SubmissionStatus, deadletter_file, load_config, load_reader
 from dve.reporting.error_report import ERROR_SCHEMA, calculate_aggregates
-from dve.reporting.utils import dump_feedback_errors, dump_processing_errors
+from dve.reporting.utils import dump_feedback_errors, dump_processing_errors, extract_and_pivot_keys
 
 PERMISSIBLE_EXCEPTIONS: tuple[type[Exception]] = (
     FileNotFoundError,  # type: ignore
@@ -718,6 +718,7 @@ def _get_error_dataframes(self, submission_id: str):
                     .otherwise(pl.lit("Warning"))  # type: ignore
                     .alias("error_type")
                 )
+                df = extract_and_pivot_keys(df)
                 df = df.select(
                     pl.col("Entity").alias("Table"),  # type: ignore
                     pl.col("error_type").alias("Type"),  # type: ignore
@@ -729,7 +730,7 @@ def _get_error_dataframes(self, submission_id: str):
                     pl.col("Category"),  # type: ignore
                 )
                 df = df.select(
-                    pl.col(column).cast(ERROR_SCHEMA[column])  # type: ignore
+                    pl.col(column).cast(ERROR_SCHEMA.get(column, pl.Utf8()))  # type: ignore
                     for column in df.columns
                 )
                 df = df.sort("Type", descending=False)  # type: ignore

src/dve/reporting/utils.py

@@ -3,7 +3,10 @@
 import json
 from typing import Optional
 
+import polars as pl
+
 import dve.parser.file_handling as fh
+from dve.core_engine.backends.utilities import pl_row_count
 from dve.core_engine.exceptions import CriticalProcessingError
 from dve.core_engine.type_hints import URI, Messages
 from dve.reporting.error_report import conditional_cast
@@ -80,3 +83,56 @@ def dump_processing_errors(
             f,
             default=str,
         )
+
+
+def extract_and_pivot_keys(
+    df: pl.DataFrame, key_field: str = "Key"   # type: ignore
+) -> pl.DataFrame:  # type: ignore
+    """
+    Extract key pair values from a key fields column (str) and pivot the keys into new columns.
+
+    Where no keys exist for a given field, the unmodified dataframe will be returned and instances
+    of a mixture of actual keys and non valid values (null, None & "") a new column will not be
+    generated.
+
+    Args:
+        df (pl.DataFrame): dataframe to manipulate
+        key_field (str): name of column to extract key, value pairs from
+
+    Returns:
+        pl.DataFrame: Polars DataFrame with pivoted keys
+    """
+    original_columns = df.columns
+    index_columns = [c for c in original_columns if c != key_field]
+
+    if pl_row_count(
+        df.select(key_field)
+        .filter(
+            (pl.col(key_field).str.lengths() > 0)  # type: ignore
+            & ~(pl.col(key_field).eq("None"))  # type: ignore
+        )
+    ) == 0:
+        return df
+
+    return (
+        df
+        .with_columns(pl.col(key_field).str.extract_all(r"(\w+): (\w+)"))  # type: ignore
+        .explode(key_field)
+        .with_columns(
+            pl.col(key_field).str.split_exact(":", 1)  # type: ignore
+            .struct.rename_fields(["pivot_key", "pivot_values"])
+            .alias("ids")
+        )
+        .unnest("ids")
+        .select(
+            *[pl.col(c) for c in original_columns],  # type: ignore
+            (pl.col("pivot_key") + pl.lit("_Identifier")).alias("pivot_key"),  # type: ignore
+            (pl.col("pivot_values").str.strip(" ")).alias("pivot_values"),  # type: ignore
+        )
+        .pivot(
+            values="pivot_values",
+            index=index_columns,
+            columns="pivot_key"
+        )
+        .drop(["null"])
+    )

tests/test_error_reporting/test_utils.py

@@ -0,0 +1,43 @@
+"""Test objects in dve.reporting.utility"""
+# pylint: disable=missing-function-docstring
+
+import polars as pl
+
+from dve.core_engine.backends.utilities import pl_row_count
+from dve.reporting.utils import extract_and_pivot_keys
+
+
+def test_extract_and_pivot_keys():
+    df = pl.DataFrame({
+        "entity": ["test1", "test2", "test3", "test4"],
+        "FailureType": ["submission1", "submission2", "submission3", "submission4"],
+        "id": [
+            "Key1: Value1 -- Key2: Value2 -- Key3: Value3",
+            "Key1: Value1 -- Key2: Value2",
+            "",
+            None,
+        ]
+    })
+    result_df = extract_and_pivot_keys(df, key_field="id")
+    expected_df = pl.DataFrame({
+        "entity": ["test1", "test2", "test3", "test4"],
+        "FailureType": ["submission1", "submission2", "submission3", "submission4"],
+        "Key1_Identifier": ["Value1", "Value1", None, None],
+        "Key2_Identifier": ["Value2", "Value2", None, None],
+        "Key3_Identifier": ["Value3", None, None, None],
+    })
+
+    assert pl_row_count(result_df) == pl_row_count(df)
+    assert result_df.equals(expected_df)
+
+
+def test_extract_and_pivot_keys_with_empty_key_field():
+    df = pl.DataFrame({
+        "entity": ["test1", "test2", "test3"],
+        "FailureType": ["submission1", "submission2", "submission3"],
+        "Key": ["", "None", None]
+    })
+    result_df = extract_and_pivot_keys(df)
+
+    assert pl_row_count(result_df) == pl_row_count(df)
+    assert result_df.equals(df)

tests/test_pipeline/pipeline_helpers.py

@@ -403,7 +403,3 @@ def error_data_after_business_rules() -> Iterator[Tuple[SubmissionInfo, str]]:
             json.dump(error_data, f)
 
         yield submitted_file_info, tdir
-
-
-def pl_row_count(df: pl.DataFrame) -> int:
-    return df.select(pl.len()).to_dicts()[0]["len"]

tests/test_pipeline/test_duckdb_pipeline.py

@@ -15,6 +15,7 @@
 from duckdb import DuckDBPyConnection
 
 from dve.core_engine.backends.base.auditing import FilterCriteria
+from dve.core_engine.backends.utilities import pl_row_count
 from dve.core_engine.backends.implementations.duckdb.auditing import DDBAuditingManager
 from dve.core_engine.backends.implementations.duckdb.reference_data import DuckDBRefDataLoader
 from dve.core_engine.models import ProcessingStatusRecord, SubmissionInfo, SubmissionStatisticsRecord
@@ -26,7 +27,6 @@
 from ..fixtures import temp_ddb_conn  # pylint: disable=unused-import
 from .pipeline_helpers import (  # pylint: disable=unused-import
     PLANETS_RULES_PATH,
-    pl_row_count,
     planet_data_after_file_transformation,
     planet_test_files,
     planets_data_after_business_rules,