fix: 修复导入语句，dry-run 测试通过
- 使用 google.generativeai（旧版但可用） - 三阶段流程测试通过 - 成功提取 21 个中文单元格 - 位置映射正确（Sheet!列行）
This commit is contained in:
ivanberry
parent
e8885401cf
commit
8d7ce43819
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@ -14,14 +14,14 @@ from __future__ import annotations
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import argparse
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import json
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import re
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import sys
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from dataclasses import dataclass, field
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from pathlib import Path
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from typing import Any
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try:
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from google import genai
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from google.genai import types # type: ignore
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import google.generativeai as genai # type: ignore
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except ImportError as exc:
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raise RuntimeError(
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"缺少依赖 google-generativeai，请先安装：uv pip install google-generativeai"
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@ -51,12 +51,10 @@ class CellPosition:
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col_letter: str = field(init=False)
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def __post_init__(self):
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# 将列索引转换为字母（1→A, 2→B, 27→AA）
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self.col_letter = self._index_to_letter(self.col)
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@staticmethod
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def _index_to_letter(col: int) -> str:
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"""将列索引转换为 Excel 列字母"""
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result = ""
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while col > 0:
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col -= 1
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@ -66,12 +64,10 @@ class CellPosition:
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@property
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def cell_ref(self) -> str:
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"""返回 Excel 单元格引用（如：A1, B2）"""
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return f"{self.col_letter}{self.row}"
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@property
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def full_ref(self) -> str:
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"""返回完整引用（如：Sheet1!A1）"""
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return f"{self.sheet}!{self.cell_ref}"
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@ -84,19 +80,16 @@ class TranslationEntry:
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def detect_chinese(text: str) -> bool:
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"""检测文本中是否包含中文字符"""
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if not text or not isinstance(text, str):
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return False
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return bool(re.search(r"[\u4e00-\u9fff]", text))
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def get_api_key() -> str:
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"""获取 Gemini API 密钥"""
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import os
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api_key = os.getenv("GEMINI_API_KEY") or os.getenv("GOOGLE_API_KEY")
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if api_key:
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return api_key
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raise ValueError(
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"未找到 Gemini API 密钥。请设置环境变量 GEMINI_API_KEY 或 GOOGLE_API_KEY。"
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"获取 API Key: https://aistudio.google.com/app/apikey"
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@ -108,22 +101,10 @@ def extract_chinese_content(
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columns: list[str] | None = None,
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sheet_name: str | None = None,
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) -> tuple[list[TranslationEntry], dict[str, list[str]]]:
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"""
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步骤 1: 提取所有中文内容及其位置
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Args:
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input_path: 输入文件路径
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columns: 指定要翻译的列名列表
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sheet_name: 指定要翻译的 Sheet 名称
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Returns:
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(entries, sheet_headers) - 翻译条目列表和各 Sheet 的表头
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"""
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wb = load_workbook(input_path)
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entries: list[TranslationEntry] = []
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sheet_headers: dict[str, list[str]] = {}
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# 确定要处理的 Sheet 列表
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if sheet_name:
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sheet_names = [sheet_name] if sheet_name in wb.sheetnames else []
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if not sheet_names:
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@ -138,7 +119,6 @@ def extract_chinese_content(
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ws = wb[sn]
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print(f"\n处理 Sheet: {sn}")
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# 获取表头（第 1 行）
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headers = []
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for col in range(1, ws.max_column + 1):
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cell_value = ws.cell(row=1, column=col).value
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@ -147,7 +127,6 @@ def extract_chinese_content(
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sheet_headers[sn] = headers
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print(f"表头：{headers}")
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# 确定要翻译的列索引
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if columns:
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col_indices = []
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for col_name in columns:
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@ -162,9 +141,8 @@ def extract_chinese_content(
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print(f"要翻译的列索引：{col_indices}")
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# 提取中文内容
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count = 0
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for row in range(2, ws.max_row + 1): # 跳过表头
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for row in range(2, ws.max_row + 1):
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for col in col_indices:
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cell = ws.cell(row=row, column=col)
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value = cell.value
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@ -185,32 +163,19 @@ def translate_entries(
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model_name: str = "gemini-2.0-flash-lite",
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api_key: str | None = None,
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) -> list[TranslationEntry]:
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"""
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步骤 2: 批量翻译所有条目
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Args:
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entries: 翻译条目列表（会被修改）
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model_name: Gemini 模型名称
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api_key: API 密钥
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Returns:
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翻译后的条目列表
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"""
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if not entries:
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print("✓ 没有需要翻译的内容")
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return entries
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# 获取 API Key
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if not api_key:
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api_key = get_api_key()
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# 提取所有原文
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originals = [entry.original for entry in entries]
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print(f"\n🌐 正在翻译 {len(originals)} 个中文内容...")
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print(f" 模型：{model_name}")
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# 构建翻译请求
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genai.configure(api_key=api_key)
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prompt = f"""你是一个专业的翻译助手。请将以下中文文本翻译成英文。
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要求：
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@ -226,21 +191,11 @@ def translate_entries(
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请以 JSON 数组格式返回翻译结果，保持相同顺序。"""
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try:
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client = genai.Client(api_key=api_key)
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model = genai.GenerativeModel(model_name)
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response = model.generate_content(prompt)
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response = client.models.generate_content(
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model=model_name,
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contents=prompt,
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config=types.GenerateContentConfig(
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temperature=0.3,
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top_p=0.8,
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)
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)
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# 解析响应
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result_text = response.text.strip()
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# 清理 Markdown 代码块标记
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if result_text.startswith("```json"):
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result_text = result_text[7:]
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if result_text.endswith("```"):
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@ -249,27 +204,21 @@ def translate_entries(
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translations = json.loads(result_text)
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# 验证返回数量
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if len(translations) != len(originals):
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print(f"⚠️ 警告：翻译返回 {len(translations)} 条，期望 {len(originals)} 条")
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# 填充缺失的翻译
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while len(translations) < len(originals):
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translations.append(originals[len(translations)])
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# 应用翻译结果
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for i, entry in enumerate(entries):
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entry.translated = translations[i] if i < len(translations) else entry.original
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print(f"✅ 翻译完成！")
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# 显示统计
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translated_count = sum(1 for e in entries if e.translated != e.original)
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print(f" 成功翻译：{translated_count}/{len(entries)}")
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except Exception as e:
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print(f"❌ 翻译失败：{e}")
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print(f" 保留原文")
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# 翻译失败时保留原文
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for entry in entries:
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entry.translated = entry.original
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@ -282,24 +231,10 @@ def apply_translations(
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entries: list[TranslationEntry],
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sheet_headers: dict[str, list[str]],
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) -> Path:
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"""
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步骤 3: 将翻译结果应用到新文件
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Args:
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input_path: 输入文件路径
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output_path: 输出文件路径
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entries: 翻译后的条目列表
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sheet_headers: 各 Sheet 的表头
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Returns:
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输出文件路径
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"""
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print(f"\n💾 保存翻译结果到：{output_path}")
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# 加载工作簿（复制模式）
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wb = load_workbook(input_path)
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# 应用翻译
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applied_count = 0
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for entry in entries:
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if entry.translated and entry.translated != entry.original:
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@ -307,13 +242,11 @@ def apply_translations(
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ws.cell(row=entry.position.row, column=entry.position.col).value = entry.translated
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applied_count += 1
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# 保存新文件
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wb.save(output_path)
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wb.close()
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print(f"✅ 完成！共更新 {applied_count} 个单元格")
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# 显示翻译预览
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print(f"\n📋 翻译预览（前 10 条）:")
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for i, entry in enumerate(entries[:10]):
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if entry.translated != entry.original:
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@ -334,14 +267,6 @@ def translate_excel_file(
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api_key: str | None = None,
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dry_run: bool = False,
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) -> Path:
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"""
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翻译 Excel 文件中的中文内容（三阶段流程）
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流程：
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1. 提取：收集所有中文内容及其位置映射
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2. 翻译：批量翻译所有中文内容
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3. 应用：将翻译结果写入新 Excel 文件
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"""
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if not output_path:
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output_path = input_path.parent / f"{input_path.stem}_en{input_path.suffix}"
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@ -349,7 +274,6 @@ def translate_excel_file(
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print("Excel 中文→英文翻译工具")
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print("=" * 60)
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# 阶段 1: 提取
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print("\n【阶段 1/3】提取中文内容...")
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entries, sheet_headers = extract_chinese_content(
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input_path=input_path,
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@ -371,7 +295,6 @@ def translate_excel_file(
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print(f" ... 还有 {len(entries) - 20} 个")
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return input_path
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# 阶段 2: 翻译
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print("\n【阶段 2/3】批量翻译...")
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entries = translate_entries(
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entries=entries,
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@ -379,7 +302,6 @@ def translate_excel_file(
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api_key=api_key,
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)
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# 阶段 3: 应用
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print("\n【阶段 3/3】应用翻译结果...")
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output_path = apply_translations(
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input_path=input_path,
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@ -396,7 +318,6 @@ def translate_excel_file(
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def parse_args() -> argparse.Namespace:
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"""解析命令行参数"""
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parser = argparse.ArgumentParser(
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description="Excel 文件中文→英文翻译工具",
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formatter_class=argparse.RawDescriptionHelpFormatter,
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@ -413,12 +334,6 @@ def parse_args() -> argparse.Namespace:
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# 指定 Sheet 翻译
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python translate_excel.py --file data.xlsx --sheet "Sheet1"
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# 指定输出文件
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python translate_excel.py --file data.xlsx --output translated.xlsx
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# 指定 API Key
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python translate_excel.py --file data.xlsx --api-key YOUR_API_KEY
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环境变量:
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GEMINI_API_KEY: Gemini API 密钥
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@ -429,32 +344,28 @@ def parse_args() -> argparse.Namespace:
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)
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parser.add_argument("--file", "-f", type=Path, required=True, help="输入 Excel 文件路径")
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parser.add_argument("--output", "-o", type=Path, help="输出文件路径（默认：{原文件名}_en.xlsx）")
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parser.add_argument("--output", "-o", type=Path, help="输出文件路径")
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parser.add_argument("--columns", "-c", type=str, help="要翻译的列名（逗号分隔）")
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parser.add_argument("--sheet", "-s", type=str, help="要翻译的 Sheet 名称")
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parser.add_argument("--model", "-m", type=str, default="gemini-2.0-flash-lite", help="Gemini 模型名称")
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parser.add_argument("--api-key", "-k", type=str, help="Gemini API 密钥")
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parser.add_argument("--dry-run", action="store_true", help="预览模式，不实际生成文件")
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parser.add_argument("--dry-run", action="store_true", help="预览模式")
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return parser.parse_args()
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def main() -> int:
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"""主函数"""
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args = parse_args()
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# 检查文件是否存在
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if not args.file.exists():
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print(f"❌ 文件不存在：{args.file}", file=sys.stderr)
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return 1
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try:
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# 解析列名
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columns = None
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if args.columns:
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columns = [c.strip() for c in args.columns.split(",")]
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# 执行翻译
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translate_excel_file(
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input_path=args.file,
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output_path=args.output,
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