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record count optimize #1472

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Merged
RamilCDISC merged 3 commits into from
Dec 12, 2025
Merged

record count optimize #1472

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6ce1eb4
record count refactor
SFJohnson24 Dec 8, 2025
98e8104
none check
SFJohnson24 Dec 9, 2025
bcf66e1
Merge branch 'main' into record_opt
RamilCDISC Dec 12, 2025
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17 changes: 5 additions & 12 deletions cdisc_rules_engine/operations/record_count.py
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Original file line number Diff line number Diff line change
Expand Up @@ -28,7 +28,7 @@ def _execute_operation(self) -> pd.Series:
if self.params.regex
else effective_grouping
)
if self.params.regex:
if self.params.regex and filtered is None:
group_df = self._get_regex_grouped_counts(
self.params.dataframe, grouping_for_operations
)
Expand Down Expand Up @@ -102,19 +102,12 @@ def _get_regex_grouped_counts(self, dataframe, grouping_columns):
grouped_counts[col] = grouped_counts[col].astype(
df_for_grouping[col].dtype
)
original_with_idx = dataframe[grouping_columns].copy()
original_with_idx["_idx"] = range(len(original_with_idx))
transformed_with_idx = df_for_grouping.copy()
transformed_with_idx["_idx"] = range(len(transformed_with_idx))
transformed_with_counts = transformed_with_idx.merge(
transformed_with_counts = df_for_grouping.merge(
grouped_counts, on=grouping_columns, how="left"
)
original_with_idx["size"] = transformed_with_counts["size"].values
result = (
original_with_idx.drop(columns=["_idx"])
.groupby(grouping_columns, as_index=False, dropna=False)
.first()
)
result = dataframe[grouping_columns].copy()
result["size"] = transformed_with_counts["size"].values
result = result.groupby(grouping_columns, as_index=False, dropna=False).first()
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@RamilCDISC RamilCDISC Dec 8, 2025

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The new logic breaks row alignments and i snot equivalent to the previous logic. This can cause silent bugs. Could you please mention if you think this is correct and that regex transformations will not reorder rows?

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@SFJohnson24 SFJohnson24 Dec 9, 2025

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@RamilCDISC why do you believe it will break row alignment? df_for_grouping is transformed by the apply_regex_to_grouping_columns but this performs only element-wise operations on selected columns. No rows are removed/added/reordered by this. The left merge keep all rows in the original order. I dont know where the row alignment not changing would be introduced

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@RamilCDISC RamilCDISC Dec 11, 2025

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Sorry I actually wanted to tag line 105. The merge operation can change the ordering. The previous code had 'idx' which could be used for reorder to original. This may not be a big issue. Please let me know your thoughts.

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@SFJohnson24 SFJohnson24 Dec 11, 2025 •
edited
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@RamilCDISC
https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.merge.html
"left: use only keys from left frame, similar to a SQL left outer join; preserve key order "

It is a left merge so the key order is preserved.

return result

def _apply_regex_to_grouping_columns(
Expand Down
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