导入玉田招聘网站成功 更改模型类工作时间为串

resumes/management/commands/import_accounting_resumes.py

@@ -12,7 +12,7 @@ class Command(BaseCommand):
 
     def add_arguments(self, parser):
         parser.add_argument('--file', required=True, help='Excel 文件路径')
-        parser.add_argument('--keyword', default='会计', help='crawl_keywords 值')
+        parser.add_argument('--keyword', default='', help='crawl_keywords 值')
         parser.add_argument('--source', type=int, default=2, help='source_id 值')
 
     def handle(self, *args, **options):

resumes/management/commands/import_nursing_resumes.py

@@ -0,0 +1,147 @@
+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}")
+

resumes/models.py

@@ -30,19 +30,19 @@ class ResumeBasic(models.Model):
                                   help_text="求职状态")
 
     work_1_experience = models.TextField(null=True, blank=True, verbose_name="工作1经历", help_text="工作1经历")
-    work_1_time = models.DateTimeField(null=True, blank=True, verbose_name="工作1时间", help_text="工作1时间")
+    work_1_time = models.CharField(max_length=255, null=True, blank=True, verbose_name="工作1时间", help_text="工作1时间")
     work_1_description = models.TextField(null=True, blank=True, verbose_name="工作1内容", help_text="工作1内容")
 
     work_2_experience = models.TextField(null=True, blank=True, verbose_name="工作2经历", help_text="工作2经历")
-    work_2_time = models.DateTimeField(null=True, blank=True, verbose_name="工作2时间", help_text="工作2时间")
+    work_2_time = models.CharField(max_length=255, null=True, blank=True, verbose_name="工作2时间", help_text="工作2时间")
     work_2_description = models.TextField(null=True, blank=True, verbose_name="工作2内容", help_text="工作2内容")
 
     work_3_experience = models.TextField(null=True, blank=True, verbose_name="工作3经历", help_text="工作3经历")
-    work_3_time = models.DateTimeField(null=True, blank=True, verbose_name="工作3时间", help_text="工作3时间")
+    work_3_time = models.CharField(max_length=255, null=True, blank=True, verbose_name="工作3时间", help_text="工作3时间")
     work_3_description = models.TextField(null=True, blank=True, verbose_name="工作3内容", help_text="工作3内容")
 
     work_4_experience = models.TextField(null=True, blank=True, verbose_name="工作4经历", help_text="工作4经历")
-    work_4_time = models.DateTimeField(null=True, blank=True, verbose_name="工作4时间", help_text="工作4时间")
+    work_4_time = models.CharField(max_length=255, null=True, blank=True, verbose_name="工作4时间", help_text="工作4时间")
     work_4_description = models.TextField(null=True, blank=True, verbose_name="工作4内容", help_text="工作4内容")
 
     height = models.IntegerField(null=True, blank=True, verbose_name="身高", help_text="身高")