266 lines
9.7 KiB
Python
266 lines
9.7 KiB
Python
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#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""导入高中英语词汇到数据库"""
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import pandas as pd
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import mysql.connector
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from datetime import datetime
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import json
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# 数据库配置
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db_config = {
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'host': 'localhost',
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'port': 3306,
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'user': 'root',
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'password': 'JKjk20011115',
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'database': 'ai_english_learning',
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'charset': 'utf8mb4'
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}
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# 词汇书ID
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BOOK_ID = 'senior_high_3500'
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def clean_text(text):
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"""清理文本，处理nan和空值"""
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if pd.isna(text) or str(text).strip() == '' or str(text).strip() == 'nan':
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return None
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return str(text).strip()
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def extract_part_of_speech(translation):
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"""从中文翻译中提取词性"""
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if not translation:
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return 'noun'
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pos_map = {
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'v.': 'verb',
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'n.': 'noun',
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'adj.': 'adjective',
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'adv.': 'adverb',
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'prep.': 'preposition',
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'conj.': 'conjunction',
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'pron.': 'pronoun',
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'interj.': 'interjection'
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}
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for abbr, full in pos_map.items():
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if abbr in translation or abbr.replace('.', '') in translation:
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return full
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# 中文词性判断
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if '动' in translation:
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return 'verb'
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elif '形' in translation or '容' in translation:
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return 'adjective'
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elif '副' in translation:
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return 'adverb'
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elif '介' in translation:
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return 'preposition'
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elif '连' in translation:
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return 'conjunction'
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return 'noun'
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def import_words_from_excel(file_path):
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"""从Excel导入单词"""
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try:
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print(f"📖 正在读取文件: {file_path}")
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df = pd.read_excel(file_path)
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print(f"📊 文件列名: {df.columns.tolist()}")
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print(f"📊 总行数: {len(df)}")
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conn = mysql.connector.connect(**db_config)
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cursor = conn.cursor()
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# 清理旧数据
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print("\n清理旧数据...")
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cursor.execute("DELETE FROM ai_vocabulary_book_words WHERE book_id = %s", (BOOK_ID,))
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cursor.execute("""
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DELETE v FROM ai_vocabulary v
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LEFT JOIN ai_vocabulary_book_words bw ON bw.vocabulary_id = v.id
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WHERE bw.id IS NULL
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""")
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conn.commit()
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# SQL语句
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insert_vocab_sql = """
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INSERT INTO ai_vocabulary
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(word, phonetic_us, phonetic_uk, phonetic, level, frequency, is_active,
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word_root, synonyms, antonyms, derivatives, collocations, created_at, updated_at)
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VALUES (%s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s, %s)
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"""
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insert_definition_sql = """
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INSERT INTO ai_vocabulary_definitions
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(vocabulary_id, part_of_speech, definition_en, definition_cn, sort_order, created_at)
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VALUES (%s, %s, %s, %s, %s, %s)
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"""
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insert_example_sql = """
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INSERT INTO ai_vocabulary_examples
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(vocabulary_id, sentence_en, sentence_cn, sort_order, created_at)
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VALUES (%s, %s, %s, %s, %s)
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"""
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insert_book_word_sql = """
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INSERT INTO ai_vocabulary_book_words
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(book_id, vocabulary_id, sort_order, created_at)
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VALUES (%s, %s, %s, %s)
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"""
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success_count = 0
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error_count = 0
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for index, row in df.iterrows():
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try:
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word = clean_text(row.get('Word'))
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if not word:
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continue
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# 检查单词是否已存在
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cursor.execute("SELECT id FROM ai_vocabulary WHERE word = %s", (word,))
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existing = cursor.fetchone()
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if existing:
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# 单词已存在，使用现有ID
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vocab_id = existing[0]
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else:
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# 单词不存在，插入新记录
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# 音标
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phonetic_us = clean_text(row.get('美式音标'))
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phonetic_uk = clean_text(row.get('英式音标'))
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phonetic = phonetic_us or phonetic_uk
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# 释义
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translation_cn = clean_text(row.get('中文含义'))
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translation_en = clean_text(row.get('英文翻译（对应中文含义）'))
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if not translation_cn:
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print(f"⚠️ 跳过 {word}：缺少中文含义")
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continue
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if not translation_en:
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translation_en = word
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part_of_speech = extract_part_of_speech(translation_cn)
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# 例句
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example_en = clean_text(row.get('例句'))
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example_cn = clean_text(row.get('例句中文翻译'))
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# 词根
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word_root = clean_text(row.get('词根'))
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# 同义词
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synonyms_text = clean_text(row.get('同义词（含义）'))
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synonyms_json = '[]'
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if synonyms_text:
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syn_list = [syn.strip() for syn in synonyms_text.split('；') if syn.strip()]
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synonyms_json = json.dumps(syn_list, ensure_ascii=False)
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# 反义词
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antonyms_text = clean_text(row.get('反义词（含义）'))
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antonyms_json = '[]'
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if antonyms_text:
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ant_list = [ant.strip() for ant in antonyms_text.split('；') if ant.strip()]
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antonyms_json = json.dumps(ant_list, ensure_ascii=False)
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# 派生词
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derivatives_text = clean_text(row.get('派生词（含义）'))
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derivatives_json = '[]'
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if derivatives_text:
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der_list = [der.strip() for der in derivatives_text.split('；') if der.strip()]
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derivatives_json = json.dumps(der_list, ensure_ascii=False)
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# 词组搭配
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phrases_text = clean_text(row.get('词组搭配（中文含义）'))
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collocations_json = '[]'
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if phrases_text:
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col_list = [phrase.strip() for phrase in phrases_text.split('；') if phrase.strip()]
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collocations_json = json.dumps(col_list, ensure_ascii=False)
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# 插入词汇
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now = datetime.now()
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cursor.execute(insert_vocab_sql, (
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word, phonetic_us, phonetic_uk, phonetic,
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'intermediate', # 高中难度
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index + 1, True,
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word_root, synonyms_json, antonyms_json,
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derivatives_json, collocations_json,
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now, now
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))
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vocab_id = cursor.lastrowid
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# 插入释义
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cursor.execute(insert_definition_sql, (
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vocab_id, part_of_speech, translation_en,
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translation_cn, 0, now
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))
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# 插入例句
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if example_en and example_cn:
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examples_en = example_en.split('；')
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examples_cn = example_cn.split('；')
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for i, (ex_en, ex_cn) in enumerate(zip(examples_en, examples_cn)):
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ex_en = ex_en.strip()
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ex_cn = ex_cn.strip()
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if ex_en and ex_cn:
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cursor.execute(insert_example_sql, (
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vocab_id, ex_en, ex_cn, i, now
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))
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# 关联到词汇书（无论单词是否已存在，都要关联）
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now = datetime.now()
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try:
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cursor.execute(insert_book_word_sql, (
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BOOK_ID, vocab_id, index, now
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))
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except Exception as link_error:
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# 如果关联已存在，跳过
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if '1062' not in str(link_error): # 不是重复键错误
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raise
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success_count += 1
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if success_count % 100 == 0:
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print(f"✅ 已处理 {success_count} 个单词...")
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conn.commit()
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except Exception as e:
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error_count += 1
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print(f"❌ 导入第 {index + 1} 行失败: {e}")
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conn.commit()
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# 更新词汇书总数
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cursor.execute(
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"UPDATE ai_vocabulary_books SET total_words = %s WHERE id = %s",
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(success_count, BOOK_ID)
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)
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conn.commit()
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print(f"\n🎉 高中词汇导入完成!")
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print(f"✅ 成功: {success_count} 个单词")
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print(f"❌ 失败: {error_count} 个单词")
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# 验证
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cursor.execute(
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"SELECT COUNT(*) FROM ai_vocabulary_book_words WHERE book_id = %s",
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(BOOK_ID,)
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)
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print(f"📊 词汇书中共有 {cursor.fetchone()[0]} 个单词")
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except Exception as e:
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print(f"❌ 导入失败: {e}")
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import traceback
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traceback.print_exc()
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finally:
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if 'cursor' in locals():
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cursor.close()
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if 'conn' in locals():
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conn.close()
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if __name__ == '__main__':
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import_words_from_excel('data/高中英语词汇.xlsx')
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