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# # utils.py
# import io
# import pandas as pd
# def pick_existing_columns(all_cols: list[str], desired: list[str]) -> list[str]:
# seen = {c.lower(): c for c in all_cols}
# out = []
# for d in desired:
# key = d.lower()
# if key in seen:
# out.append(seen[key])
# return out or list(all_cols) # fall back to everything if none matched
# def slice_up_to_page(df: pd.DataFrame, page: int, page_size: int) -> pd.DataFrame:
# start = page * page_size
# end = start + page_size
# return df.iloc[:end].copy()
# def contains_any_column(df: pd.DataFrame, term: str) -> pd.Series:
# if not term:
# return pd.Series([True] * len(df), index=df.index)
# term = str(term).strip()
# if not term:
# return pd.Series([True] * len(df), index=df.index)
# # Combine columns as strings (fast-ish)
# joined = df.astype(str).apply(lambda col: col.str.contains(term, case=False, na=False))
# return joined.any(axis=1)
# def export_csv(df: pd.DataFrame) -> tuple[str, bytes]:
# buf = io.StringIO()
# df.to_csv(buf, index=False)
# name = "buildscout_export.csv"
# return name, buf.getvalue().encode("utf-8")
# utils.py
import io
import pandas as pd
def pick_existing_columns(all_cols, wanted):
s = set(all_cols)
return [c for c in wanted if c in s]
def export_csv(df: pd.DataFrame) -> io.BytesIO:
bio = io.BytesIO()
df.to_csv(bio, index=False)
bio.seek(0)
return bio
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