1e490c23c2
renamed: exel_datein/2024/06/Tagesbericht Beispiel.xlsx -> exel_datein/2024/06/13.xlsx new file: exel_datein/2024/09/4.xlsx
37 lines
1.4 KiB
Python
37 lines
1.4 KiB
Python
import pandas as pd
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import json
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import os
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import re
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root_dir = "exel_datein"
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# Passe das Pattern an: Jahr/Monat/Tag
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date_pattern = re.compile(r'(\d{4})[\\/](\d{2})[\\/](\d{1,2})')
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all_notes = []
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for dirpath, _, filenames in os.walk(root_dir):
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for filename in filenames:
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if filename.lower().endswith(('.xlsx', '.xls')):
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excel_path = os.path.join(dirpath, filename)
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# Versuche, Jahr, Monat und Tag aus dem Pfad zu extrahieren
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match = date_pattern.search(excel_path)
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if match:
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jahr, monat, tag = match.groups()
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else:
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jahr = monat = tag = "unbekannt"
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try:
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df = pd.read_excel(excel_path, sheet_name=0, usecols=[0, 1], names=["Kunde", "Info"])
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df = df.dropna(subset=["Kunde", "Info"])
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for _, row in df.iterrows():
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# Format: Kunde: Info (Jahr: xxxx, Monat: xx, Tag: xx)
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note = f"{row['Kunde']}: {row['Info']} (Jahr: {jahr}, Monat: {monat}, Tag: {tag})"
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all_notes.append(note)
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print(f"Verarbeitet: {excel_path}")
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except Exception as e:
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print(f"Fehler bei {excel_path}: {e}")
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# Alles als JSON speichern
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with open("background_data.json", "w", encoding="utf-8") as f:
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json.dump(all_notes, f, ensure_ascii=False, indent=2)
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print("Alle Daten erfolgreich als background_data.json gespeichert.") |