fix: improve warning box contrast and add XLSX converter script
Warning summary boxes in the import wizard had white text on a light warning background, making them unreadable. Switch to a light-yellow background with dark text instead. Also adds convert_xlsx.py for converting the LvS member Excel spreadsheet into CSV files for ZIP bundle import, and documents the mandatory version bump rule in CLAUDE.md. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
This commit is contained in:
shahondin1624
@@ -56,6 +56,7 @@ These caused most bugs in this project. Every contributor must know them:
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- `make redeploy` = rebuild JS + copy into running container
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- After redeploy without version bump, restart container (`docker compose restart nextcloud`) and hard-refresh browser
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- Version bump (`appinfo/info.xml` + `webpack.config.js` DefinePlugin + `main.js` provide) + `occ upgrade` is the reliable way to bust all caches
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- **Always bump the version when redeploying UI changes.** Without a version bump, Nextcloud serves cached JS/CSS and changes won't reach the browser — even with hard-refresh. Bump all three locations together.
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## Gitea
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+1
-1
@@ -5,7 +5,7 @@
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<name>Mitgliederverwaltung</name>
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<summary>Mitgliederverwaltung für Pfadfindervereine</summary>
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<description><![CDATA[Verwaltung von Mitgliedern, Familien, Beiträgen, Lagern und mehr für Pfadfindervereine. Integriert sich in Nextcloud Kalender, Kontakte und Dateien.]]></description>
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<version>0.1.0</version>
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<version>0.1.2</version>
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<licence>agpl</licence>
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<author>shahondin1624</author>
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<namespace>Mitgliederverwaltung</namespace>
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+418
@@ -0,0 +1,418 @@
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#!/usr/bin/env python3
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"""
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Convert 'Mitglieder LvS 25.xlsx' into CSV files suitable for ZIP bundle import
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into the Mitgliederverwaltung Nextcloud plugin.
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Usage:
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python3 convert_xlsx.py "/path/to/Mitglieder LvS 25.xlsx" [output_dir]
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Output (in output_dir, default ./import_bundle):
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Stufen.csv, Familien.csv, Mitglieder.csv, Adressen.csv,
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Telefonnummern.csv, E-Mails.csv, import_bundle.zip
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"""
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import csv
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import os
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import re
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import sys
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import zipfile
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from collections import defaultdict
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from datetime import datetime
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import openpyxl
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# ---------------------------------------------------------------------------
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# Config
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# ---------------------------------------------------------------------------
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STUFEN_MAP = {
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"W": "Wölflinge",
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"P": "Pfadfinder",
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"R": "Rover",
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}
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STUFEN_META = {
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"Wölflinge": {"sort_order": 1, "age_min": 7, "age_max": 10, "color": "#ff9800"},
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"Pfadfinder": {"sort_order": 2, "age_min": 11, "age_max": 16, "color": "#4caf50"},
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"Rover": {"sort_order": 3, "age_min": 16, "age_max": 25, "color": "#2196f3"},
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}
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CSV_DELIMITER = ";"
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# ---------------------------------------------------------------------------
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# Helpers
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# ---------------------------------------------------------------------------
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def fmt_date(val):
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"""Convert an Excel date value to YYYY-MM-DD string."""
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if val is None:
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return ""
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if isinstance(val, datetime):
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return val.strftime("%Y-%m-%d")
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s = str(val).strip()
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if not s:
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return ""
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for fmt in ("%Y-%m-%d %H:%M:%S", "%Y-%m-%d", "%d.%m.%Y", "%d/%m/%Y"):
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try:
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return datetime.strptime(s, fmt).strftime("%Y-%m-%d")
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except ValueError:
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continue
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return s
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def parse_address(raw):
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"""
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Parse 'Straße Nr, PLZ Ort' into (strasse, plz, ort).
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Handles incomplete addresses gracefully.
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"""
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if not raw or str(raw).strip().lower() == "none":
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return "", "", ""
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raw = str(raw).strip()
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# Try: "Street, PLZ City"
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m = re.match(r"^(.+?),\s*(\d{5})\s+(.+)$", raw)
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if m:
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return m.group(1).strip(), m.group(2), m.group(3).strip()
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# Try: "Street, City" (no PLZ)
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m = re.match(r"^(.+?),\s*(.+)$", raw)
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if m:
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return m.group(1).strip(), "", m.group(2).strip()
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return raw, "", ""
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def clean(val):
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"""Stringify a cell value, stripping None."""
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if val is None:
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return ""
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return str(val).strip()
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def write_csv(path, headers, rows):
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"""Write a semicolon-delimited UTF-8 CSV with BOM."""
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with open(path, "w", newline="", encoding="utf-8-sig") as f:
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w = csv.writer(f, delimiter=CSV_DELIMITER)
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w.writerow(headers)
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w.writerows(rows)
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print(f" {os.path.basename(path)}: {len(rows)} rows")
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# ---------------------------------------------------------------------------
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# Readers
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# ---------------------------------------------------------------------------
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def read_mitglieder_stamm(ws):
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"""
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Parse the 'Mitglieder Stamm' sheet.
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Returns list of dicts with keys matching column semantics.
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"""
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members = []
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for row in ws.iter_rows(min_row=3, max_row=ws.max_row, values_only=True):
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nachname = clean(row[1])
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if not nachname:
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continue
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members.append({
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"nachname": nachname,
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"vorname": clean(row[2]),
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"geburtsdatum": fmt_date(row[3]),
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"stufe_code": clean(row[5]), # W / P / R
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"adresse_raw": clean(row[6]),
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"email": clean(row[7]),
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"telefon": clean(row[8]),
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"aktiv": clean(row[9]).lower() == "x",
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"beitrag": clean(row[10]),
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})
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return members
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def read_kontaktdaten(ws):
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"""
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Parse a 'Kontaktdaten …' sheet.
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Returns dict keyed by (nachname, vorname) → health info dict.
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"""
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info = {}
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# Find header row (contains "Name")
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header_row = None
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for r in range(1, min(10, ws.max_row + 1)):
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cell = ws.cell(r, 2).value
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if cell and str(cell).strip().lower() == "name":
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header_row = r
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break
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if header_row is None:
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return info
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for row in ws.iter_rows(min_row=header_row + 1, max_row=ws.max_row, values_only=True):
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nachname = clean(row[1])
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vorname = clean(row[2])
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if not nachname:
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continue
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allergien = clean(row[6])
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if allergien.upper() == "NEIN":
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allergien = ""
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krankheiten = clean(row[5])
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if krankheiten.upper() == "NEIN":
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krankheiten = ""
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medis = clean(row[7])
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if medis.upper() == "NEIN":
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medis = ""
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notes_parts = []
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schwimmer = clean(row[4])
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if schwimmer.upper() == "JA":
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notes_parts.append("Schwimmer: Ja")
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elif schwimmer:
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notes_parts.append(f"Schwimmer: {schwimmer}")
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if krankheiten:
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notes_parts.append(f"Krankheiten: {krankheiten}")
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if medis:
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notes_parts.append(f"Medikamente: {medis}")
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# Parent contact from right side of sheet (cols K-N, indices 11-13)
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parent_name = ""
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parent_phone = ""
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if len(row) > 12:
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parent_name = clean(row[12]) # col M: parent Vorname
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if len(row) > 13:
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parent_phone = clean(row[13]) # col N: parent Mobil
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info[(nachname, vorname)] = {
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"allergien": allergien,
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"notizen": "; ".join(notes_parts) if notes_parts else "",
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"parent_nachname": clean(row[11]) if len(row) > 11 else "",
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"parent_vorname": parent_name,
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"parent_phone": parent_phone,
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}
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return info
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def read_kontoliste(ws):
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"""
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Parse the 'Kontoliste' sheet.
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Returns list of dicts: kontoinhaber, betrag, iban.
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"""
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accounts = []
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for row in ws.iter_rows(min_row=2, max_row=ws.max_row, values_only=True):
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inhaber = clean(row[1])
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if not inhaber:
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continue
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accounts.append({
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"kontoinhaber": inhaber,
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"betrag": clean(row[2]),
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"iban": clean(row[3]),
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})
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return accounts
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# ---------------------------------------------------------------------------
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# Family grouping
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# ---------------------------------------------------------------------------
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def build_families(members, accounts):
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"""
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Group members into families by shared last name + address.
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Match to Kontoliste by last name.
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Returns:
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- families: list of {name, kontoinhaber, iban}
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- member→family_name mapping
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"""
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# Group by (nachname, address) to handle same last name at different addresses
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groups = defaultdict(list)
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for m in members:
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key = m["nachname"]
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groups[key].append(m)
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# Build account lookup: last name → account
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acct_by_name = {}
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for a in accounts:
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# Kontoinhaber is "Nachname Vorname" — extract last name
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parts = a["kontoinhaber"].replace(",", " ").split()
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if parts:
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acct_by_name[parts[0].lower()] = a
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families = []
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member_family = {} # (nachname, vorname) → family name
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for nachname, group in sorted(groups.items()):
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family_name = f"Familie {nachname}"
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acct = acct_by_name.get(nachname.lower(), {})
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families.append({
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"name": family_name,
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"kontoinhaber": acct.get("kontoinhaber", ""),
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"iban": acct.get("iban", ""),
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})
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for m in group:
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member_family[(m["nachname"], m["vorname"])] = family_name
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return families, member_family
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# ---------------------------------------------------------------------------
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# Main
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# ---------------------------------------------------------------------------
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def main():
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if len(sys.argv) < 2:
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print(__doc__)
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sys.exit(1)
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xlsx_path = sys.argv[1]
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out_dir = sys.argv[2] if len(sys.argv) > 2 else os.path.join(os.path.dirname(xlsx_path), "import_bundle")
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os.makedirs(out_dir, exist_ok=True)
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print(f"Reading {xlsx_path} ...")
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wb = openpyxl.load_workbook(xlsx_path, data_only=True)
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# --- Read source sheets ---
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members = read_mitglieder_stamm(wb["Mitglieder Stamm"])
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print(f" {len(members)} members from 'Mitglieder Stamm'")
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kontakt_info = {}
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for sheet_name in wb.sheetnames:
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if sheet_name.startswith("Kontaktdaten"):
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ki = read_kontaktdaten(wb[sheet_name])
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kontakt_info.update(ki)
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print(f" {len(ki)} entries from '{sheet_name}'")
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accounts = read_kontoliste(wb["Kontoliste"])
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print(f" {len(accounts)} accounts from 'Kontoliste'")
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families, member_family = build_families(members, accounts)
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print(f" {len(families)} families grouped")
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print(f"\nWriting CSVs to {out_dir} ...")
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# --- Stufen.csv ---
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stufen_rows = []
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for code, name in sorted(STUFEN_MAP.items(), key=lambda x: STUFEN_META[x[1]]["sort_order"]):
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meta = STUFEN_META[name]
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stufen_rows.append([
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name, meta["sort_order"], meta["age_min"], meta["age_max"], meta["color"]
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])
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write_csv(
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os.path.join(out_dir, "Stufen.csv"),
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["Name", "Sortierung", "Mindestalter", "Hoechstalter", "Farbe"],
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stufen_rows,
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)
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# --- Familien.csv ---
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fam_rows = []
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for f in families:
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fam_rows.append([f["name"], f["kontoinhaber"], f["iban"]])
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write_csv(
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os.path.join(out_dir, "Familien.csv"),
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["Name", "Kontoinhaber", "IBAN"],
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fam_rows,
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)
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# --- Mitglieder.csv ---
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mitglieder_rows = []
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for m in members:
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key = (m["nachname"], m["vorname"])
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ki = kontakt_info.get(key, {})
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stufe_name = STUFEN_MAP.get(m["stufe_code"], "")
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status = "aktiv" if m["aktiv"] else "inaktiv"
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family_name = member_family.get(key, "")
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mitglieder_rows.append([
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m["vorname"],
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m["nachname"],
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m["geburtsdatum"],
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"", # Geschlecht — not in source
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"mitglied", # Rolle
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stufe_name,
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"2025-01-01", # Eintritt — not in source, use reasonable default
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"", # Austritt
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status,
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ki.get("allergien", ""),
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ki.get("notizen", ""),
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"", # Zusaetzliche Notizen
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"", # KV-Typ
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"", # KV-Name
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family_name,
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m["beitrag"], # Eingefrorener Beitragssatz
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])
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write_csv(
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os.path.join(out_dir, "Mitglieder.csv"),
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[
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"Vorname", "Nachname", "Geburtsdatum", "Geschlecht", "Rolle",
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"Stufenname", "Eintritt", "Austritt", "Status", "Allergien",
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"Notizen", "Zusaetzliche Notizen", "KV-Typ", "KV-Name",
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"Familienname", "Eingefrorener Beitragssatz",
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],
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mitglieder_rows,
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)
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# --- Adressen.csv ---
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addr_rows = []
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for m in members:
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strasse, plz, ort = parse_address(m["adresse_raw"])
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if not strasse:
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continue
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mitgliedername = f"{m['vorname']} {m['nachname']}"
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addr_rows.append([
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mitgliedername, "Hauptadresse", strasse, plz, ort, "Deutschland", "Ja"
|
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])
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write_csv(
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os.path.join(out_dir, "Adressen.csv"),
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["Mitgliedername", "Label", "Strasse", "PLZ", "Ort", "Land", "Primaer"],
|
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addr_rows,
|
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)
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||||
|
||||
# --- Telefonnummern.csv ---
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phone_rows = []
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for m in members:
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# Member's own phone
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if m["telefon"]:
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mitgliedername = f"{m['vorname']} {m['nachname']}"
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phone_rows.append([mitgliedername, "Mobil", m["telefon"]])
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# Parent phones from Kontaktdaten sheets
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seen_parent_phones = set()
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for (nachname, vorname), ki in kontakt_info.items():
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||||
parent_phone = ki.get("parent_phone", "")
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if not parent_phone:
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||||
continue
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mitgliedername = f"{vorname} {nachname}"
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# Split "number oder number" into separate entries
|
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phones = [p.strip() for p in parent_phone.split("oder")]
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for i, phone in enumerate(phones):
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||||
if not phone:
|
||||
continue
|
||||
dedup_key = (mitgliedername, phone)
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if dedup_key in seen_parent_phones:
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||||
continue
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||||
seen_parent_phones.add(dedup_key)
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||||
label = f"Eltern {i+1}" if len(phones) > 1 else "Eltern"
|
||||
phone_rows.append([mitgliedername, label, phone])
|
||||
|
||||
write_csv(
|
||||
os.path.join(out_dir, "Telefonnummern.csv"),
|
||||
["Mitgliedername", "Label", "Nummer"],
|
||||
phone_rows,
|
||||
)
|
||||
|
||||
# --- E-Mails.csv ---
|
||||
email_rows = []
|
||||
for m in members:
|
||||
if m["email"]:
|
||||
mitgliedername = f"{m['vorname']} {m['nachname']}"
|
||||
email_rows.append([mitgliedername, "Privat", m["email"]])
|
||||
write_csv(
|
||||
os.path.join(out_dir, "E-Mails.csv"),
|
||||
["Mitgliedername", "Label", "E-Mail-Adresse"],
|
||||
email_rows,
|
||||
)
|
||||
|
||||
# --- Create ZIP bundle ---
|
||||
zip_path = os.path.join(out_dir, "import_bundle.zip")
|
||||
csv_files = [
|
||||
"Stufen.csv", "Familien.csv", "Mitglieder.csv",
|
||||
"Adressen.csv", "Telefonnummern.csv", "E-Mails.csv",
|
||||
]
|
||||
with zipfile.ZipFile(zip_path, "w", zipfile.ZIP_DEFLATED) as zf:
|
||||
for name in csv_files:
|
||||
fpath = os.path.join(out_dir, name)
|
||||
if os.path.exists(fpath):
|
||||
zf.write(fpath, name)
|
||||
print(f"\n import_bundle.zip created ({len(csv_files)} files)")
|
||||
|
||||
print(f"\nDone! Import via: Mitgliederverwaltung → Import → ZIP-Bundle hochladen")
|
||||
print(f" {zip_path}")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
+1
-1
@@ -31,7 +31,7 @@ app.use(router)
|
||||
// @nextcloud/vue v9 reads appName/appVersion via Vue's inject(),
|
||||
// not via webpack DefinePlugin globals.
|
||||
app.provide('appName', 'mitgliederverwaltung')
|
||||
app.provide('appVersion', '0.1.0')
|
||||
app.provide('appVersion', '0.1.2')
|
||||
|
||||
app.mount('#mitgliederverwaltung')
|
||||
|
||||
|
||||
@@ -947,17 +947,18 @@ async function onExecuteWithMerge() {
|
||||
}
|
||||
|
||||
.import-wizard__summary-item--success {
|
||||
background: var(--color-success);
|
||||
background: var(--color-success, #2d7b41);
|
||||
color: white;
|
||||
}
|
||||
|
||||
.import-wizard__summary-item--warning {
|
||||
background: var(--color-warning);
|
||||
color: white;
|
||||
background: #fef3cd;
|
||||
color: #664d03;
|
||||
border: 1px solid #e9d78a;
|
||||
}
|
||||
|
||||
.import-wizard__summary-item--error {
|
||||
background: var(--color-error);
|
||||
background: var(--color-error, #DB0606);
|
||||
color: white;
|
||||
}
|
||||
|
||||
|
||||
+1
-1
@@ -41,7 +41,7 @@ module.exports = {
|
||||
new VueLoaderPlugin(),
|
||||
new webpack.DefinePlugin({
|
||||
appName: JSON.stringify('mitgliederverwaltung'),
|
||||
appVersion: JSON.stringify('0.1.0'),
|
||||
appVersion: JSON.stringify('0.1.2'),
|
||||
}),
|
||||
new webpack.optimize.LimitChunkCountPlugin({
|
||||
maxChunks: 1,
|
||||
|
||||
Reference in New Issue
Block a user