fix:dms api
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gongwenxin
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@ -738,7 +738,7 @@ class InputParser:
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# Create Endpoint (POST)
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create_path = f"/api/dms/{dms_instance_code}/v1/{name}"
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create_request_body_schema = {"type": "object", "properties": {"version": {"type": "string", "example": version}, "act": {"type": "integer", "example": 0}, "data": {"type": "array", "items": model}}, "required": ["data"]}
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create_request_body_schema = {"type": "object", "properties": {"version": {"type": "string", "example": version}, "act": {"type": "integer", "example": -1}, "data": {"type": "array", "items": model}}, "required": ["data"]}
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endpoints.append(DMSEndpoint(path=create_path, method='post', title=f"Create {name}", request_body={'content': {'application/json': {'schema': create_request_body_schema}}}, responses=success_response, test_mode='scenario_only', operation_id=f"create_{name}", category_name=category_name, raw_record=item, model_pk_name=pk_name, identity_id_list=identity_id_list))
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# List Endpoint (POST) - 🔧 添加pageNo和pageSize查询参数
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@ -748,7 +748,22 @@ class InputParser:
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{'name': 'pageNo', 'in': 'query', 'required': False, 'description': '页码(从1开始)', 'schema': {'type': 'integer', 'default': 1}},
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{'name': 'pageSize', 'in': 'query', 'required': False, 'description': '分页大小(最大值200)', 'schema': {'type': 'integer', 'default': 1000}}
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]
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endpoints.append(DMSEndpoint(path=list_path, method='post', title=f"List {name}", request_body={'content': {'application/json': {'schema': {}}}}, responses={'200': {'description': 'Successful Operation', 'content': {'application/json': {'schema': list_response_schema}}}}, parameters=list_parameters, test_mode='standalone', operation_id=f"list_{name}", category_name=category_name, raw_record=item, model_pk_name=pk_name, identity_id_list=identity_id_list))
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# List请求体Schema（包含version字段，但不包含act字段）
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list_request_body_schema = {
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"type": "object",
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"properties": {
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"version": {"type": "string", "example": version},
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"isSearchCount": {"type": "boolean", "example": True},
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"query": {
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"type": "object",
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"properties": {
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"fields": {"type": "array", "items": {"type": "string"}},
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"filter": {"type": "object"}
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}
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}
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}
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}
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endpoints.append(DMSEndpoint(path=list_path, method='post', title=f"List {name}", request_body={'content': {'application/json': {'schema': list_request_body_schema}}}, responses={'200': {'description': 'Successful Operation', 'content': {'application/json': {'schema': list_response_schema}}}}, parameters=list_parameters, test_mode='standalone', operation_id=f"list_{name}", category_name=category_name, raw_record=item, model_pk_name=pk_name, identity_id_list=identity_id_list))
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# Read Endpoint (GET) - 🔧 只为单主键模型生成查询详情接口
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if isinstance(identity_id_list, list) and len(identity_id_list) > 1:
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@ -764,7 +779,8 @@ class InputParser:
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# Update Endpoint (PUT)
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update_path = f"/api/dms/{dms_instance_code}/v1/{name}"
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endpoints.append(DMSEndpoint(path=update_path, method='put', title=f"Update {name}", request_body={'content': {'application/json': {'schema': create_request_body_schema}}}, responses=success_response, test_mode='scenario_only', operation_id=f"update_{name}", category_name=category_name, raw_record=item, model_pk_name=pk_name, identity_id_list=identity_id_list))
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update_request_body_schema = {"type": "object", "properties": {"version": {"type": "string", "example": version}, "act": {"type": "integer", "example": -1}, "data": {"type": "array", "items": model}}, "required": ["data"]}
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endpoints.append(DMSEndpoint(path=update_path, method='put', title=f"Update {name}", request_body={'content': {'application/json': {'schema': update_request_body_schema}}}, responses=success_response, test_mode='scenario_only', operation_id=f"update_{name}", category_name=category_name, raw_record=item, model_pk_name=pk_name, identity_id_list=identity_id_list))
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# Delete Endpoint (DELETE)
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delete_path = f"/api/dms/{dms_instance_code}/v1/{name}"
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@ -800,6 +816,7 @@ class InputParser:
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delete_request_body_schema = {
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"type": "object",
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"properties": {
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"version": {"type": "string", "example": version},
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"data": {
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"type": "array",
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"items": {"type": "string"}
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@ -82,6 +82,9 @@ class DataGenerator:
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llm_data = self._generate_with_llm(schema, llm_service, context_name, operation_id)
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if llm_data is not None:
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self.logger.debug(f"{log_prefix}LLM successfully generated data for{context_log}")
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# 🔑 关键修复：LLM生成的数据也需要井数据增强
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if self.well_data_manager and isinstance(llm_data, dict):
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llm_data = self.well_data_manager.enhance_data_with_well_values(llm_data)
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return llm_data
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except Exception as e:
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self.logger.debug(f"{log_prefix}LLM generation failed for{context_log}: {e}, falling back to traditional generation")
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165
test_well_data_integration.py
Normal file
165
test_well_data_integration.py
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@ -0,0 +1,165 @@
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#!/usr/bin/env python3
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"""
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测试井数据集成和DMS请求体格式的脚本
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"""
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import sys
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import logging
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import json
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from ddms_compliance_suite.utils.data_generator import DataGenerator
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from ddms_compliance_suite.utils.well_data_manager import WellDataManager
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def test_well_data_integration():
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"""测试井数据集成功能"""
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# 设置日志
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logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
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logger = logging.getLogger(__name__)
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logger.info("开始测试井数据集成功能...")
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# 模拟井数据管理器（因为无法连接真实API）
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class MockWellDataManager:
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def __init__(self):
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self.well_data = [
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{"wellId": "HB00019975", "wellCommonName": "郑4-106"},
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{"wellId": "HB00019976", "wellCommonName": "郑4-107"}
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]
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self.wellbore_data = [
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{"wellboreId": "WEBHHB100083169", "wellboreCommonName": "郑4-106主井筒"},
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{"wellboreId": "WEBHHB100083170", "wellboreCommonName": "郑4-107主井筒"}
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]
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def is_well_related_field(self, field_name):
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return field_name in ['wellId', 'wellboreId', 'wellCommonName']
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def get_well_value_for_field(self, field_name):
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if field_name == 'wellId':
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return self.well_data[0]['wellId']
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elif field_name == 'wellboreId':
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return self.wellbore_data[0]['wellboreId']
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elif field_name == 'wellCommonName':
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return self.well_data[0]['wellCommonName']
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return None
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def enhance_data_with_well_values(self, data):
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if not isinstance(data, dict):
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return data
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enhanced_data = data.copy()
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for field_name, value in data.items():
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if self.is_well_related_field(field_name):
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real_value = self.get_well_value_for_field(field_name)
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if real_value is not None:
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enhanced_data[field_name] = real_value
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logger.info(f"🔄 替换字段 '{field_name}': {value} -> {real_value}")
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return enhanced_data
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# 创建模拟的井数据管理器
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mock_well_manager = MockWellDataManager()
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# 创建数据生成器
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data_generator = DataGenerator(logger_param=logger, well_data_manager=mock_well_manager)
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# 测试1: 测试DMS创建请求体格式
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logger.info("1. 测试DMS创建请求体格式...")
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create_schema = {
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"type": "object",
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"properties": {
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"version": {"type": "string", "example": "1.0.0"},
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"act": {"type": "integer", "example": -1},
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"data": {
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"type": "array",
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"items": {
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"type": "object",
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"properties": {
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"wellId": {"type": "string"},
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"wellboreId": {"type": "string"},
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"wellCommonName": {"type": "string"},
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"dataRegion": {"type": "string"},
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"bsflag": {"type": "integer"}
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}
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}
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}
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},
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"required": ["data"]
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}
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create_data = data_generator.generate_data_from_schema(create_schema, "create_request", "create_test")
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logger.info(f"创建请求体: {json.dumps(create_data, ensure_ascii=False, indent=2)}")
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# 验证创建请求体格式
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assert "version" in create_data, "创建请求体缺少version字段"
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assert "act" in create_data, "创建请求体缺少act字段"
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assert "data" in create_data, "创建请求体缺少data字段"
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assert create_data["act"] == -1, f"创建请求体act字段值错误，期望-1，实际{create_data['act']}"
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# 验证井数据是否被正确应用
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if create_data["data"] and len(create_data["data"]) > 0:
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first_item = create_data["data"][0]
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if "wellId" in first_item:
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assert first_item["wellId"] == "HB00019975", f"wellId未使用真实值，实际值: {first_item['wellId']}"
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logger.info("✅ wellId使用了真实值")
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if "wellCommonName" in first_item:
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assert first_item["wellCommonName"] == "郑4-106", f"wellCommonName未使用真实值，实际值: {first_item['wellCommonName']}"
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logger.info("✅ wellCommonName使用了真实值")
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# 测试2: 测试DMS删除请求体格式
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logger.info("2. 测试DMS删除请求体格式...")
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delete_schema = {
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"type": "object",
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"properties": {
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"version": {"type": "string", "example": "1.0.0"},
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"data": {
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"type": "array",
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"items": {"type": "string"}
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}
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},
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"required": ["data"]
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}
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delete_data = data_generator.generate_data_from_schema(delete_schema, "delete_request", "delete_test")
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logger.info(f"删除请求体: {json.dumps(delete_data, ensure_ascii=False, indent=2)}")
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# 验证删除请求体格式
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assert "version" in delete_data, "删除请求体缺少version字段"
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assert "data" in delete_data, "删除请求体缺少data字段"
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assert delete_data["version"] == "1.0.0", f"删除请求体version字段值错误，期望1.0.0，实际{delete_data['version']}"
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# 测试3: 测试查询请求体格式
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logger.info("3. 测试查询请求体格式...")
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list_schema = {
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"type": "object",
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"properties": {
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"version": {"type": "string", "example": "1.0.0"},
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"isSearchCount": {"type": "boolean", "example": True},
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"query": {
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"type": "object",
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"properties": {
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"fields": {"type": "array", "items": {"type": "string"}},
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"filter": {"type": "object"}
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}
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}
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}
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}
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list_data = data_generator.generate_data_from_schema(list_schema, "list_request", "list_test")
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logger.info(f"查询请求体: {json.dumps(list_data, ensure_ascii=False, indent=2)}")
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# 验证查询请求体格式
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assert "version" in list_data, "查询请求体缺少version字段"
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assert list_data["version"] == "1.0.0", f"查询请求体version字段值错误，期望1.0.0，实际{list_data['version']}"
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logger.info("🎉 所有测试通过！")
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return True
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if __name__ == "__main__":
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try:
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success = test_well_data_integration()
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sys.exit(0 if success else 1)
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except Exception as e:
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print(f"❌ 测试失败: {e}")
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import traceback
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traceback.print_exc()
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sys.exit(1)
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