344 lines
12 KiB
Python
344 lines
12 KiB
Python
"""Builds a JSON hierarchy tree from the Position column of an Excel Stk.-Liste.
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Usage:
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python jsonFromXlsx.py --filename Fortna --tab soll
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python jsonFromXlsx.py --filename Fortna --tab ist --output result.json
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python jsonFromXlsx.py --filename KA135776 --extract-ids
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python jsonFromXlsx.py --from-results --extract-ids
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"""
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import argparse
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import json
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import os
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import re
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import sys
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from collections import Counter
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from pathlib import Path
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import openpyxl
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SHEET_NAMES = {
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"soll": "Stk.-Liste SOLL",
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"ist": "Stk.-Liste IST",
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}
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# Column indices (0-based) in the header row
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COL_POSITION = 0
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COL_TEILENUMMER = 1
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COL_BEZEICHNUNG = 2
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HEADER_ROW = 3 # 1-based row number of the header
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def find_xlsx(examples_dir: str, pattern: str) -> Path:
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"""Find an .xlsx file in examples/ whose name contains the given pattern."""
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matches = []
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for f in Path(examples_dir).glob("*.xlsx"):
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if pattern.lower() in f.name.lower():
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matches.append(f)
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if not matches:
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print(f"FEHLER: Keine .xlsx-Datei mit Muster '{pattern}' in {examples_dir} gefunden.")
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sys.exit(1)
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if len(matches) > 1:
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print(f"Mehrere Dateien gefunden fuer Muster '{pattern}':")
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for m in sorted(matches):
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print(f" {m.name}")
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print(f"Verwende: {matches[0].name}")
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return sorted(matches)[0]
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def make_key(teilenummer: str, bezeichnung: str, is_unique: bool) -> str:
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"""Build a node key from Teilenummer, adding Bezeichnung if not unique."""
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if is_unique:
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return teilenummer
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combined = f"{teilenummer}-{bezeichnung}"
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return combined.replace(" ", "_")
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def unique_key(parent: dict, key: str) -> str:
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"""Return key with _1, _2, ... suffix if it already exists in parent."""
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if key not in parent:
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return key
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suffix = 1
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while f"{key}_{suffix}" in parent:
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suffix += 1
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return f"{key}_{suffix}"
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def build_tree(ws, sheet_type: str) -> dict:
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"""Read the worksheet and build a nested dict from Position paths.
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Keys are Teilenummer-based (with Bezeichnung if non-unique).
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Position paths are used only for hierarchy, not as keys.
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"""
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# First pass: collect all Teilenummern to determine uniqueness
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teil_counter: Counter = Counter()
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rows_data = []
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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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pos = row[COL_POSITION]
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teil = row[COL_TEILENUMMER]
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bez = row[COL_BEZEICHNUNG]
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if pos is None or teil is None:
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continue
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pos_str = str(pos).strip()
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if pos_str.lower() == "position":
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continue # skip header row
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teil_str = str(teil).strip()
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bez_str = str(bez).strip() if bez else ""
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teil_counter[teil_str] += 1
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rows_data.append((pos_str, teil_str, bez_str))
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unique_teile = {t for t, count in teil_counter.items() if count == 1}
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# Second pass: build tree with Teilenummer-based keys
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tree: dict = {}
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pos_to_node: dict[str, dict] = {} # maps position path -> dict node
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# Track metadata per node for leaf post-processing
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node_meta: dict[int, tuple[str, str]] = {} # id(child) -> (teil_str, bez_str)
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for pos_str, teil_str, bez_str in rows_data:
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key = make_key(teil_str, bez_str, teil_str in unique_teile)
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segments = pos_str.split("/")
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# Find parent dict
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if len(segments) == 1:
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parent = tree
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else:
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parent_pos = "/".join(segments[:-1])
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if parent_pos not in pos_to_node:
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# Parent row missing in data, create placeholder
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pos_to_node[parent_pos] = {}
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parent = pos_to_node[parent_pos]
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# Insert with unique key
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final_key = unique_key(parent, key)
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child: dict = {}
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parent[final_key] = child
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pos_to_node[pos_str] = child
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node_meta[id(child)] = (teil_str, bez_str)
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is_sivas = re.compile(r"^\d{9}$").match
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# Post-process: leaves (empty dicts) -> key=Teilenummer, value=Bezeichnung
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def simplify_leaves(node: dict) -> dict:
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result: dict = {}
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for key, value in node.items():
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if isinstance(value, dict) and len(value) == 0:
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# Leaf node: use only Teilenummer as key, Bezeichnung as value
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teil, bez = node_meta.get(id(value), ("", ""))
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if teil in result and is_sivas(teil):
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# Aggregate duplicate 9-digit Sivas numbers
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existing = result[teil]
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if isinstance(existing, str):
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result[teil] = {"anzahl": 2, "beschreibung": existing}
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else:
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existing["anzahl"] += 1
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else:
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leaf_key = unique_key(result, teil)
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result[leaf_key] = bez
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elif isinstance(value, dict):
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result[key] = simplify_leaves(value)
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else:
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result[key] = value
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return result
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return simplify_leaves(tree)
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RE_SIVAS = re.compile(r"^(\d{9})")
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def is_leaf_value(v) -> bool:
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"""True if v is a leaf entry (string or anzahl-dict)."""
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if isinstance(v, str):
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return True
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if isinstance(v, dict) and "anzahl" in v:
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return True
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return False
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def extract_ids_from_tree(tree: dict) -> dict[str, str]:
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"""Collect 9-digit Sivas numbers one level above leaves.
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Returns dict of nummer -> bezeichnung.
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"""
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ids: dict[str, str] = {}
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def walk(node: dict):
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for key, value in node.items():
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if not isinstance(value, dict) or "anzahl" in value:
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continue # leaf, skip
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# Check if all children are leaves
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all_leaves = all(is_leaf_value(v) for v in value.values())
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m = RE_SIVAS.match(key)
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if all_leaves and value and m:
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nummer = m.group(1)
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# Bezeichnung from key: part after "nummer-", underscores back to spaces
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if "-" in key[9:]:
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bez = key[10:].replace("_", " ")
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elif len(key) > 9:
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bez = key[10:].replace("_", " ")
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else:
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bez = nummer
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ids[nummer] = bez
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else:
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walk(value)
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walk(tree)
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return ids
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def process_file(xlsx_path: Path, sheet_name: str, tab: str, results_dir: Path,
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out_path: Path | None = None) -> bool:
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"""Process a single xlsx file. Returns True on success."""
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print(f"Lade: {xlsx_path.name}")
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print(f"Sheet: {sheet_name}")
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wb = openpyxl.load_workbook(str(xlsx_path), data_only=True)
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if sheet_name not in wb.sheetnames:
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print(f" SKIP: Sheet '{sheet_name}' nicht vorhanden.")
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return False
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ws = wb[sheet_name]
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tree = build_tree(ws, tab)
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if out_path is None:
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stem = xlsx_path.stem.replace(" ", "_")
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out_path = results_dir / f"{stem}_{tab}.json"
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with open(out_path, "w", encoding="utf-8") as f:
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json.dump(tree, f, indent=2, ensure_ascii=False)
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print(f" Ausgabe: {out_path}")
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return True
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def main():
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parser = argparse.ArgumentParser(
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description="Erzeugt eine JSON-Baumstruktur aus der Positionsspalte einer Excel-Stueckliste."
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)
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parser.add_argument(
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"--filename",
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default=None,
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help="Suchmuster fuer die .xlsx-Datei im examples/-Ordner (z.B. 'Fortna')",
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)
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parser.add_argument(
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"--tab",
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choices=["soll", "ist"],
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default="soll",
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help="Welches Tabellenblatt gelesen wird: 'soll' oder 'ist' (default: soll)",
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)
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parser.add_argument(
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"--output",
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default=None,
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help="Ausgabedatei (default: <filename>_<tab>.json im results/-Ordner)",
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)
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parser.add_argument(
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"--all",
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action="store_true",
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dest="process_all",
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help="Alle .xlsx-Dateien im examples/-Ordner in _ist und _soll JSON konvertieren",
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)
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parser.add_argument(
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"--extract-ids",
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action="store_true",
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dest="extract_ids",
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help="9-stellige Sivas-Nummern eine Ebene ueber den Blaettern extrahieren",
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)
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parser.add_argument(
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"--from-results",
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action="store_true",
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dest="from_results",
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help="JSON-Dateien aus results/ lesen statt aus .xlsx zu erzeugen",
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)
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args = parser.parse_args()
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if not args.process_all and not args.filename and not args.from_results:
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parser.error("Entweder --filename, --all oder --from-results muss angegeben werden.")
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# Resolve paths relative to project root
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project_root = Path(os.environ.get("PROJECT", Path(__file__).resolve().parent.parent))
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examples_dir = project_root / "examples"
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results_dir = project_root / "results"
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results_dir.mkdir(exist_ok=True)
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# Default tab to "ist" when --extract-ids without explicit --tab
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tab = args.tab
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if args.extract_ids and args.tab == "soll" and "--tab" not in sys.argv:
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tab = "ist"
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if args.from_results:
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# Read existing JSON files from results/
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pattern = f"*_{tab}.json"
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json_files = sorted(results_dir.glob(pattern))
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if args.filename:
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json_files = [f for f in json_files if args.filename.lower() in f.name.lower()]
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if not json_files:
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print(f"FEHLER: Keine JSON-Dateien mit Muster '{pattern}' in {results_dir} gefunden.")
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sys.exit(1)
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print(f"Lese {len(json_files)} JSON-Dateien aus {results_dir}\n")
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for json_path in json_files:
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with open(json_path, encoding="utf-8") as f:
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tree = json.load(f)
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# Derive project name from filename: strip _ist/_soll.json suffix
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project_name = json_path.stem
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for suffix in ("_ist", "_soll"):
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if project_name.endswith(suffix):
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project_name = project_name[: -len(suffix)]
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break
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if args.extract_ids:
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ids = extract_ids_from_tree(tree)
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ids_path = results_dir / f"{project_name}_ids_{tab}.txt"
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with open(ids_path, "w", encoding="utf-8") as f:
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for nummer, bez in sorted(ids.items()):
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f.write(f"{nummer}: {bez}\n")
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print(f" {json_path.name} -> {ids_path.name} ({len(ids)} IDs)")
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elif args.process_all:
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xlsx_files = sorted(f for f in Path(examples_dir).glob("*.xlsx")
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if not f.name.startswith("~$"))
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print(f"Verarbeite {len(xlsx_files)} Dateien aus {examples_dir}\n")
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ok, skip = 0, 0
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for xlsx_path in xlsx_files:
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for t in ("soll", "ist"):
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sheet_name = SHEET_NAMES[t]
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if process_file(xlsx_path, sheet_name, t, results_dir):
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ok += 1
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else:
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skip += 1
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print()
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print(f"Fertig: {ok} JSON erzeugt, {skip} uebersprungen.")
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else:
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xlsx_path = find_xlsx(str(examples_dir), args.filename)
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sheet_name = SHEET_NAMES[tab]
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out_path = None
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if args.output:
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out_path = Path(args.output)
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if not out_path.is_absolute():
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out_path = results_dir / out_path
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json_out = None
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if args.extract_ids:
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stem = xlsx_path.stem.replace(" ", "_")
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json_out = results_dir / f"{stem}_{tab}.json"
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if not process_file(xlsx_path, sheet_name, tab, results_dir, out_path):
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sys.exit(1)
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if args.extract_ids:
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# Read back the generated JSON
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read_path = out_path or json_out or results_dir / f"{xlsx_path.stem.replace(' ', '_')}_{tab}.json"
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with open(read_path, encoding="utf-8") as f:
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tree = json.load(f)
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ids = extract_ids_from_tree(tree)
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project_name = xlsx_path.stem.replace(" ", "_")
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ids_path = results_dir / f"{project_name}_ids_{tab}.txt"
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with open(ids_path, "w", encoding="utf-8") as f:
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for nummer, bez in sorted(ids.items()):
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f.write(f"{nummer}: {bez}\n")
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print(f" IDs: {ids_path} ({len(ids)} IDs)")
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if __name__ == "__main__":
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main()
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