panel_app/convert_to_excel_panel.py

import io
import time
from typing import Iterable, Sequence

import pandas as pd


def write_dfs_to_excel(
    dfs: Sequence[pd.DataFrame],
    sheet_names: Sequence[str],
    index: bool = True,
    profile: dict | None = None,
) -> bytes:
    """Simple Excel export for Panel.

    Writes the given DataFrames to an in-memory XLSX file and returns the bytes.
    No Streamlit dependency and no heavy formatting, to keep Panel exports fast
    and avoid Streamlit runtime warnings.
    """
    bytes_io = io.BytesIO()
    t0 = time.perf_counter() if profile is not None else 0.0
    with pd.ExcelWriter(bytes_io, engine="xlsxwriter") as writer:
        for df, name in zip(dfs, sheet_names):
            # Ensure we always write a valid DataFrame, even if None was passed
            safe_df = df if isinstance(df, pd.DataFrame) else pd.DataFrame()
            t_sheet0 = time.perf_counter() if profile is not None else 0.0
            safe_df.to_excel(writer, sheet_name=str(name), index=index)
            t_sheet1 = time.perf_counter() if profile is not None else 0.0

            if profile is not None:
                sheets = profile.get("excel_sheets")
                if not isinstance(sheets, list):
                    sheets = []
                    profile["excel_sheets"] = sheets
                try:
                    rows = int(len(safe_df))
                except Exception:  # noqa: BLE001
                    rows = 0
                try:
                    cols = int(safe_df.shape[1])
                except Exception:  # noqa: BLE001
                    cols = 0
                sheets.append(
                    {
                        "name": str(name),
                        "rows": rows,
                        "cols": cols,
                        "seconds": float(t_sheet1 - t_sheet0),
                    }
                )

    if profile is not None:
        profile["excel_total_seconds"] = float(time.perf_counter() - t0)

    return bytes_io.getvalue()