#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
CSV生成和Django ORM导入脚本
"""

import csv
import os
from pathlib import Path
from datetime import date
from faker import Faker
from loguru import logger

# 初始化faker
fake = Faker('zh_CN')

# 项目根目录
BASE_DIR = Path(__file__).resolve().parent

# 设置Django环境
os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'diary_family.settings')
import django
django.setup()

# 导入Django模型
from core.models import ReadingType, InsightRecord, ReadingRecord

# 生成ReadingType CSV
@logger.catch
def generate_reading_type_csv():
    """生成阅读记录类型CSV文件"""
    csv_path = BASE_DIR / 'reading_type.csv'
    
    # 定义字段名，与数据库表字段一一对应
    fields = ['name']
    
    # 生成模拟数据
    data = [
        ['书籍'],
        ['文章'],
        ['论文'],
        ['报告'],
        ['其他']
    ]
    
    # 写入CSV文件
    with open(csv_path, 'w', newline='', encoding='utf-8') as f:
        writer = csv.writer(f)
        writer.writerow(fields)
        writer.writerows(data)
    
    logger.info(f"生成ReadingType CSV文件成功: {csv_path}")
    return csv_path

# 生成InsightRecord CSV
@logger.catch
def generate_insight_record_csv():
    """生成感悟记录CSV文件"""
    csv_path = BASE_DIR / 'insight_record.csv'
    
    # 定义字段名，与数据库表字段一一对应
    fields = ['date', 'content']
    
    # 生成模拟数据
    data = []
    for _ in range(10):
        record_date = fake.date_between(start_date='-30d', end_date='today')
        content = fake.paragraph(nb_sentences=3, variable_nb_sentences=True)
        data.append([record_date, content])
    
    # 写入CSV文件
    with open(csv_path, 'w', newline='', encoding='utf-8') as f:
        writer = csv.writer(f)
        writer.writerow(fields)
        writer.writerows(data)
    
    logger.info(f"生成InsightRecord CSV文件成功: {csv_path}")
    return csv_path

# 生成ReadingRecord CSV
@logger.catch
def generate_reading_record_csv():
    """生成阅读记录CSV文件"""
    csv_path = BASE_DIR / 'reading_record.csv'
    
    # 定义字段名，与数据库表字段一一对应
    fields = ['date', 'type_id', 'title', 'source', 'progress', 'note']
    
    # 生成模拟数据
    data = []
    for _ in range(15):
        record_date = fake.date_between(start_date='-30d', end_date='today')
        type_id = fake.random_int(min=1, max=5)  # 对应ReadingType的id
        title = fake.sentence(nb_words=5, variable_nb_words=True)
        source = fake.company()
        progress = fake.random_element(['已完成', '进行中', '未开始'])
        note = fake.paragraph(nb_sentences=2, variable_nb_sentences=True)
        data.append([record_date, type_id, title, source, progress, note])
    
    # 写入CSV文件
    with open(csv_path, 'w', newline='', encoding='utf-8') as f:
        writer = csv.writer(f)
        writer.writerow(fields)
        writer.writerows(data)
    
    logger.info(f"生成ReadingRecord CSV文件成功: {csv_path}")
    return csv_path

# 导入ReadingType CSV到Django模型
@logger.catch
def import_reading_type_csv(csv_path):
    """将阅读记录类型CSV导入到Django模型"""
    try:
        logger.info(f"开始导入 {csv_path} 到ReadingType模型")
        
        # 清空现有数据
        ReadingType.objects.all().delete()
        logger.info("已清空现有ReadingType数据")
        
        # 读取CSV文件并导入数据
        with open(csv_path, 'r', encoding='utf-8') as f:
            # 跳过表头
            next(f)
            
            # 读取CSV数据并创建模型实例
            reader = csv.reader(f)
            reading_types = []
            for row in reader:
                name = row[0]
                reading_types.append(ReadingType(name=name))
            
            # 批量创建
            ReadingType.objects.bulk_create(reading_types)
            
        logger.info(f"导入成功，共插入 {len(reading_types)} 条记录")
        
    except Exception as e:
        logger.error(f"导入失败: {e}")

# 导入InsightRecord CSV到Django模型
@logger.catch
def import_insight_record_csv(csv_path):
    """将感悟记录CSV导入到Django模型"""
    try:
        logger.info(f"开始导入 {csv_path} 到InsightRecord模型")
        
        # 读取CSV文件并导入数据
        with open(csv_path, 'r', encoding='utf-8') as f:
            # 跳过表头
            next(f)
            
            # 读取CSV数据并创建模型实例
            reader = csv.reader(f)
            insight_records = []
            for row in reader:
                record_date = row[0]
                content = row[1]
                insight_records.append(InsightRecord(date=record_date, content=content))
            
            # 批量创建
            InsightRecord.objects.bulk_create(insight_records)
            
        logger.info(f"导入成功，共插入 {len(insight_records)} 条记录")
        
    except Exception as e:
        logger.error(f"导入失败: {e}")

# 导入ReadingRecord CSV到Django模型
@logger.catch
def import_reading_record_csv(csv_path):
    """将阅读记录CSV导入到Django模型"""
    try:
        logger.info(f"开始导入 {csv_path} 到ReadingRecord模型")
        
        # 读取CSV文件并导入数据
        with open(csv_path, 'r', encoding='utf-8') as f:
            # 跳过表头
            next(f)
            
            # 读取CSV数据并创建模型实例
            reader = csv.reader(f)
            reading_records = []
            for row in reader:
                record_date = row[0]
                type_id = int(row[1])
                title = row[2]
                source = row[3]
                progress = row[4]
                note = row[5]
                
                # 确保type_id存在
                if ReadingType.objects.filter(id=type_id).exists():
                    reading_records.append(ReadingRecord(
                        date=record_date,
                        type_id=type_id,
                        title=title,
                        source=source,
                        progress=progress,
                        note=note
                    ))
                else:
                    logger.warning(f"跳过记录: 类型ID {type_id} 不存在")
            
            # 批量创建
            ReadingRecord.objects.bulk_create(reading_records)
            
        logger.info(f"导入成功，共插入 {len(reading_records)} 条记录")
        
    except Exception as e:
        logger.error(f"导入失败: {e}")

# 主函数
@logger.catch
def main():
    """主函数"""
    logger.info("开始执行CSV生成和导入脚本")
    
    # 生成CSV文件
    reading_type_csv = generate_reading_type_csv()
    insight_record_csv = generate_insight_record_csv()
    reading_record_csv = generate_reading_record_csv()
    
    # 导入CSV到Django模型
    import_reading_type_csv(reading_type_csv)
    import_insight_record_csv(insight_record_csv)
    import_reading_record_csv(reading_record_csv)
    
    logger.info("脚本执行完成")

if __name__ == "__main__":
    main()