今天突然想起上次知识图谱系列埋了一个坑(【知识图谱】1、Neo4j环境搭建入门指南:从零开始玩转图数据库),说后续写一篇关于Python操作neo4j的示例。趁着周六有充足时间,这里写个demo补上。
本文demo还是以面试的求职者、岗位要求技能 为例。建2个实例对象
1、求职者具备的技能
2、岗位要求的技能
本文默认已经安装好 neo4j desktop数据库,直接先上代码
python
from fastapi import FastAPI, HTTPException, Request
from pydantic import BaseModel
from langchain_community.graphs import Neo4jGraph
import asyncio
from typing import List
import json
# Initialize FastAPI
app = FastAPI()
# Initialize Neo4j with timeout
try:
graph = Neo4jGraph(
url="bolt://localhost:7687",
username="neo4j",
password="password",
database="neo4j",
timeout=60 # 60 seconds timeout
)
except Exception as e:
print(f"Failed to connect to Neo4j: {e}")
graph = None
# Fallback in-memory storage
job_seekers = []
job_positions = []
# Define Pydantic models for request bodies
class JobSeekerModel(BaseModel):
name: str
skills: List[str]
class JobPositionModel(BaseModel):
title: str
required_skills: List[str]
# Add job seeker
@app.post("/add_job_seeker")
async def add_job_seeker(request: Request):
try:
# Parse JSON data from request body
data = await request.json()
print(data)
job_seeker = JobSeekerModel(**data)
except json.JSONDecodeError:
raise HTTPException(status_code=400, detail="Invalid JSON data")
except ValueError as e:
raise HTTPException(status_code=400, detail=str(e))
if graph:
try:
query = (
"CREATE (j:JobSeeker {name: $name}) "
"WITH j "
"UNWIND $skills AS skill "
"MERGE (s:Skill {name: skill}) "
"CREATE (j)-[:HAS_SKILL]->(s)"
)
await asyncio.wait_for(
asyncio.to_thread(graph.query, query, {"name": job_seeker.name, "skills": job_seeker.skills}),
timeout=5.0 # 5 seconds timeout
)
except asyncio.TimeoutError:
raise HTTPException(status_code=504, detail="Database operation timed out")
except Exception as e:
print(f"Neo4j error: {e}")
raise HTTPException(status_code=500, detail="Failed to add job seeker to Neo4j")
# Always add to in-memory storage as fallback
job_seekers.append({"name": job_seeker.name, "skills": job_seeker.skills})
return {"message": f"Added job seeker {job_seeker.name} with skills {', '.join(job_seeker.skills)}"}
# Add job position
@app.post("/add_job_position")
async def add_job_position(request: Request):
try:
# Parse JSON data from request body
data = await request.json()
print(data)
job_position = JobPositionModel(**data)
except json.JSONDecodeError:
raise HTTPException(status_code=400, detail="Invalid JSON data")
except ValueError as e:
raise HTTPException(status_code=400, detail=str(e))
if graph:
try:
query = (
"CREATE (j:JobPosition {title: $title}) "
"WITH j "
"UNWIND $required_skills AS skill "
"MERGE (s:Skill {name: skill}) "
"CREATE (j)-[:REQUIRES_SKILL]->(s)"
)
await asyncio.wait_for(
asyncio.to_thread(graph.query, query,
{"title": job_position.title, "required_skills": job_position.required_skills}),
timeout=5.0 # 5 seconds timeout
)
except asyncio.TimeoutError:
raise HTTPException(status_code=504, detail="Database operation timed out")
except Exception as e:
print(f"Neo4j error: {e}")
raise HTTPException(status_code=500, detail="Failed to add job position to Neo4j")
# Always add to in-memory storage as fallback
job_positions.append({"title": job_position.title, "required_skills": job_position.required_skills})
return {
"message": f"Added job position {job_position.title} requiring skills {', '.join(job_position.required_skills)}"}
# Run the app
if __name__ == "__main__":
import uvicorn
uvicorn.run(app, host="0.0.0.0", port=8001)
还是用AI解释下代码主要功能:
1、初始化FastAPI应用和Neo4j图数据库连接。
2、定义了两个Pydantic模型JobSeekerModel和JobPositionModel用于请求体验证。
3、提供两个POST接口:
/add_job_seeker:添加求职者信息到Neo4j(若连接成功)。
/add_job_position:添加职位信息到Neo4j(若连接成功)。
4、使用异步处理数据库操作,并设置超时时间以确保服务稳定性。
直接运行可能会提示APOC插件未安装,那就先安装plugins, APOC 点击install安装。我这个是安装的截图,当时忘记先截图了。
图片
写接口测试下可以用curl命令
1、添加求职者
curl -X POST http://localhost:8000/api/add_job_seeker
-H "Content-Type: application/json"
-d '{"name": "Alice Smith", "skills": ["Python", "JavaScript", "Machine Learning"]}'
2、添加职位:
curl -X POST http://localhost:8000/api/add_job_position
-H "Content-Type: application/json"
-d '{"title": "Senior Software Engineer", "required_skills": ["Python", "Docker", "Kubernetes"]}'
我们也可以用postman等工具测试
运行结果,由于我执行过,数据看着比较混乱
计划下一篇更新 neo4j图数据库结合大模型应用的例子