from datetime import datetime, timedelta
from django.core.management.base import BaseCommand
from pandas._libs.tslibs.timestamps import Timestamp
import pandas as pd
from resumes.models import ResumeBasic
import re
import traceback


class Command(BaseCommand):
    help = "导入会计类简历（支持 --keyword 和 --source 参数）"

    def add_arguments(self, parser):
        parser.add_argument('--file', required=True, help='Excel 文件路径')
        parser.add_argument('--keyword', default='', help='crawl_keywords 值')
        parser.add_argument('--source', type=int, default=1, help='source_id 值')

    def handle(self, *args, **options):
        filepath = options['file']
        default_keyword = options['keyword']
        default_source = options['source']
        df = pd.read_excel(filepath)

        rename_map = {
            '姓名': 'name', '性别': 'gender', '年龄': 'age', '求职区域': 'job_location', '生日': 'birthday',
            '学校': 'school', '期望职务': 'expected_position',
            '手机': 'phone', '婚姻': 'marital_status', '身高': 'height', '体重': 'weight', '电话': 'phone',
            '学历': 'education', '毕业学校': 'school', '工作经验': 'work_years',
            '现居住地': 'current_location', '工作地点': 'job_location', '到岗时间': 'available_time',
            '最后活跃时间': 'update_time', '最高学历': 'education', '婚姻状态': 'marital_status',
            '民族': 'ethnicity', '工作职能': 'job_function', '意向岗位': 'intended_position',
            '从事行业': 'industry', '期望薪资': 'expected_salary', '求职类型': 'job_property',
            '现居地': 'current_location',
            '求职状态': 'job_status', '工作1经历': 'work_1_experience', '工作1时间': 'work_1_time',
            '工作1内容': 'work_1_description',
            '工作2经历': 'work_2_experience', '工作2时间': 'work_2_time', '工作2内容': 'work_2_description',
            '工作3经历': 'work_3_experience', '工作3时间': 'work_3_time', '工作3内容': 'work_3_description',
            '工作4经历': 'work_4_experience', '工作4时间': 'work_4_time', '工作4内容': 'work_4_description',
        }
        df.rename(columns={k: v for k, v in rename_map.items() if k in df.columns}, inplace=True)

        df['source_id'] = default_source
        df['crawl_keywords'] = default_keyword

        def val(v, field=None):
            if v is None or pd.isna(v):
                if field == 'update_time':
                    return datetime(2019, 12, 12)
                return None
            if field == 'update_time':
                if isinstance(v, Timestamp):
                    return v.to_pydatetime()
                if isinstance(v, str):
                    try:
                        return pd.to_datetime(v).to_pydatetime()
                    except Exception:
                        return datetime(2019, 12, 12)
                if isinstance(v, datetime):
                    return v
                return datetime(2019, 12, 12)
            if isinstance(v, Timestamp):
                return v.to_pydatetime()
            return v

        success_count = 0
        fail_count = 0
        errors = []

        for i, row in df.iterrows():
            try:
                resume_id = val(row.get('resume_id'))

                # 自动从年龄字段中提取整数（如 "38岁" → 38）
                raw_age = row.get('age')
                try:
                    extracted_age = int(re.search(r'\d+', str(raw_age)).group()) if raw_age else None
                except:
                    extracted_age = None

                defaults = {
                    'name': val(row.get('name')),
                    'gender': val(row.get('gender')),
                    'age': extracted_age,
                    'phone': val(row.get('phone')),
                    'marital_status': val(row.get('marital_status')),
                    'height': val(row.get('height')),
                    'weight': val(row.get('weight')),
                    'education': val(row.get('education')),
                    'school': val(row.get('school')),
                    'work_years': val(row.get('work_years')),
                    'current_location': val(row.get('current_location')),
                    'job_location': val(row.get('job_location')),
                    'available_time': val(row.get('available_time')),
                    'update_time': val(row['update_time'], field='update_time'),
                    'ethnicity': val(row.get('ethnicity')),
                    'job_function': val(row.get('job_function')),
                    'intended_position': val(row.get('intended_position')),
                    'industry': val(row.get('industry')),
                    'expected_salary': val(row.get('expected_salary')),
                    'job_property': val(row.get('job_property')),
                    'job_status': val(row.get('job_status')),
                    'source_id': val(row.get('source_id')),
                    'crawl_keywords': val(row.get('crawl_keywords')),
                    'birthday': val(row.get('birthday')),
                    'expected_position': val(row.get('expected_position')),
                    'work_1_experience': val(row.get('work_1_experience')),
                    'work_1_time': val(row.get('work_1_time')),
                    'work_1_description': val(row.get('work_1_description')),
                    'work_2_experience': val(row.get('work_2_experience')),
                    'work_2_time': val(row.get('work_2_time')),
                    'work_2_description': val(row.get('work_2_description')),
                    'work_3_experience': val(row.get('work_3_experience')),
                    'work_3_time': val(row.get('work_3_time')),
                    'work_3_description': val(row.get('work_3_description')),
                    'work_4_experience': val(row.get('work_4_experience')),
                    'work_4_time': val(row.get('work_4_time')),
                    'work_4_description': val(row.get('work_4_description')),
                }

                # 安全方式：get_or_create + 逐字段 set
                obj, _ = ResumeBasic.objects.get_or_create(resume_id=resume_id)

                for k, v in defaults.items():
                    try:
                        setattr(obj, k, v)
                    except Exception as field_error:
                        print(f"[字段设置错误] {k} = {v!r} ({type(v)}) → {field_error}")
                        raise

                obj.save()
                success_count += 1

            except Exception as e:
                fail_count += 1
                errors.append((i + 2, str(e)))
                print(f"\n❌ 第 {i + 2} 行出错：{e}")
                print(f"resume_id: {repr(resume_id)} ({type(resume_id).__name__})")
                for k, v in defaults.items():
                    print(f"{k:<20} | {repr(v):<30} | {type(v).__name__}")
                traceback.print_exc()

        self.stdout.write(self.style.SUCCESS(f"导入完成！总数：{len(df)}，成功：{success_count}，失败：{fail_count}"))
        if errors:
            self.stdout.write(self.style.WARNING("失败记录如下："))
            for line_no, msg in errors:
                self.stdout.write(f"  第 {line_no} 行出错：{msg}")