From bca5425908365ac621e712e3e647421b639e9f05 Mon Sep 17 00:00:00 2001
From: technik <kai.brenner@stadtfilter.ch>
Date: Sat, 7 Feb 2026 12:48:19 +0100
Subject: [PATCH] modified for use with cet and cest files

---
 suisa-convert-acr-v4.py | 32 +++++++++++++++++++-------------
 1 file changed, 19 insertions(+), 13 deletions(-)

diff --git a/suisa-convert-acr-v4.py b/suisa-convert-acr-v4.py
index 3c90ad8..571e5d6 100644
--- a/suisa-convert-acr-v4.py
+++ b/suisa-convert-acr-v4.py
@@ -1,10 +1,4 @@
 #!/usr/bin/env python3
-# Format ACRCloud CSV/XLSX reports (Radio Stadtfilter) in das SUISA Layout
-# mit korrekter Spaltenreihenfolge, automatischer Spaltenbreite,
-# Fonts/Ausrichtung und sauberem Zeitformat.
-# Usage:   python format_radio_report.py <input.xlsx> [-o <output.xlsx>]
-# Abhängigkeiten:
-# pip install pandas openpyxl
 
 from __future__ import annotations
 
@@ -35,13 +29,19 @@ SOURCE_MAP = {
 
 RIGHT_ALIGN_COLS = {"Sendedatum", "Sendedauer", "Sendezeit"}
 
+
+possible_cols = [
+    "Timestamp(UTC+01:00)",
+    "Timestamp(UTC+02:00)",
+    ]
+
 # ---------------------------------------------------------------------------
 # Hilfsfunktionen
 # ---------------------------------------------------------------------------
 
 def _fmt_duration(seconds: Optional[float | int]) -> str:
     """Wandelt Sekunden (float|int|NaN) in **HH:MM:SS** um.
-    Excel interpretiert dann korrekt. Für Kurzzeiten → 00:MM:SS"""
+    Excel interpretiert dann korrekt. Fuer Kurzzeiten  00:MM:SS"""
     if seconds is None or pd.isna(seconds):
         seconds = 0
     total = int(round(float(seconds)))
@@ -51,6 +51,7 @@ def _fmt_duration(seconds: Optional[float | int]) -> str:
 
 
 def _build_dataframe(src: Path) -> pd.DataFrame:
+
     try:
         df_orig = pd.read_excel(src)
     except FileNotFoundError:
@@ -62,8 +63,13 @@ def _build_dataframe(src: Path) -> pd.DataFrame:
     for tgt, src_col in SOURCE_MAP.items():
         df_new[tgt] = df_orig.get(src_col, "")
 
-    # Datum/Zeit
-    ts = pd.to_datetime(df_orig.get("Timestamp(UTC+01:00)"), errors="coerce")
+    # Datum/Zeiti
+    ts_col = next(col for col in possible_cols if col in df_orig.columns)
+    ts = pd.to_datetime(
+    pd.Series(df_orig[ts_col]),
+    errors="coerce"
+    )
+
     df_new["Sendedatum"] = ts.dt.strftime("%Y%m%d")
     df_new["Sendezeit"] = ts.dt.strftime("%H:%M:%S")
 
@@ -124,15 +130,15 @@ def format_report(input_path: Path, output_path: Path) -> None:
     df = _build_dataframe(input_path)
     df.to_excel(output_path, index=False)
     _autofit_and_align(output_path)
-    print(f"Formatiertes Reporting gespeichert → {output_path}")
+    print(f"Formatiertes Reporting gespeichert_{output_path}")
 
 # ---------------------------------------------------------------------------
 # CLI Entry
 # ---------------------------------------------------------------------------
 if __name__ == "__main__":
-    parser = argparse.ArgumentParser(description="Format ACRCloud XLSX für SUISA")
-    parser.add_argument("input", help="Pfad zur Original‑XLSX (ohne/mit .xlsx)")
-    parser.add_argument("-o", "--output", help="Pfad der Ziel‑XLSX")
+    parser = argparse.ArgumentParser(description="Format ACRCloud XLSX fuer SUISA")
+    parser.add_argument("input", help="Pfad zur Original XLSX (ohne/mit .xlsx)")
+    parser.add_argument("-o", "--output", help="Pfad der ZielXLSX")
     args = parser.parse_args()
 
     in_path = Path(args.input)