110 lines
3.3 KiB
Python
110 lines
3.3 KiB
Python
from __future__ import annotations
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import os
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from pathlib import Path
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import pandas as pd
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# ---------------------------------------------
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# Cross-platform paths (Windows & Linux/Mac)
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# ---------------------------------------------
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def resolve_data_root() -> Path:
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"""
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Priority:
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1) Env var IDRAC_DATA_DIR (absolute/relative OK)
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2) nearest parent of this file that contains a 'data' folder
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3) ./data under current working directory
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"""
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env = os.getenv("IDRAC_DATA_DIR")
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if env:
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return Path(env).expanduser().resolve()
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here = Path(__file__).resolve()
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for p in [here] + list(here.parents):
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if (p / "data").is_dir():
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return (p / "data").resolve()
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return (Path.cwd() / "data").resolve()
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DATA_ROOT = resolve_data_root()
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SERVER_LIST_DIR = DATA_ROOT / "server_list"
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SERVER_LIST_FILE = SERVER_LIST_DIR / "server_list.txt"
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MAC_TXT_DIR = DATA_ROOT / "mac"
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OUTPUT_XLSX = DATA_ROOT / "idrac_info" / "mac_info.xlsx"
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# Ensure output directory exists
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OUTPUT_XLSX.parent.mkdir(parents=True, exist_ok=True)
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# ---------------------------------------------
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# Helpers
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# ---------------------------------------------
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def read_lines_any_encoding(path: Path) -> list[str]:
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"""Read a text file trying common encodings (handles Windows & UTF-8)."""
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encodings = ["utf-8-sig", "utf-8", "cp949", "euc-kr", "latin-1"]
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for enc in encodings:
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try:
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with path.open("r", encoding=enc, errors="strict") as f:
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return f.read().splitlines()
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except Exception:
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continue
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# last resort with replacement
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with path.open("r", encoding="utf-8", errors="replace") as f:
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return f.read().splitlines()
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# ---------------------------------------------
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# Load server list (file names without .txt)
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# ---------------------------------------------
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if not SERVER_LIST_FILE.is_file():
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raise FileNotFoundError(f"server_list.txt not found: {SERVER_LIST_FILE}")
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file_names = read_lines_any_encoding(SERVER_LIST_FILE)
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data_list: list[str] = []
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index_list: list[int | str] = []
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sequence_number = 1
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for name in file_names:
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# normalize and skip blanks
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base = (name or "").strip()
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if not base:
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continue
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txt_path = MAC_TXT_DIR / f"{base}.txt"
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if not txt_path.is_file():
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# if a file is missing, keep row aligned with an empty line
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data_list.append("")
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index_list.append("")
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continue
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lines = read_lines_any_encoding(txt_path)
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for line in lines:
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cleaned = (line or "").strip().upper()
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if cleaned:
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data_list.append(cleaned)
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if len(cleaned) == 7:
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index_list.append(sequence_number)
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sequence_number += 1
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else:
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index_list.append("") # keep column blank if not 7 chars
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else:
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data_list.append("")
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index_list.append("")
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print(f"Length of index_list: {len(index_list)}")
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print(f"Length of data_list: {len(data_list)}")
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# ---------------------------------------------
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# Save to Excel
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# ---------------------------------------------
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df = pd.DataFrame({
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"Index": index_list, # will be column A
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"Content": data_list, # will be column B
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})
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# header=False to start at column A without headers, index=False to omit row numbers
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df.to_excel(OUTPUT_XLSX, index=False, header=False)
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print(f"Saved: {OUTPUT_XLSX}")
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