python 实现查询Neo4j多节点的多层关系
需求：查询出满足3人及3案有关系的集合
#-*-coding:utf-8-*-
frompy2neoimportGraph
importpsycopg2
#二维数组查找
deffind(target,array):
fori,valinenumerate(array):
forj,tempinenumerate(val):
iftemp==target:
returnTrue;
returnFalse
graph=Graph(host="192.168.3.186://7474",auth=("neo4j","wabjtam123"))
data=graph.run('matchdata=(p:anjian)-[:参与*2..5]-(u:anjian)withp,collect(distinctu.AJBH)asajbhsmatch(p:anjian)-[:参与*1..5]-(c:xyr)withp,ajbhs,collect(distinctc.XYRBH)asxyrbh_list,(ajbhs+p.AJBH)asajbh_listwheresize(xyrbh_list)>2andsize(ajbh_list)>2returnp.AJBHasajbh,ajbh_list,xyrbh_list')
aj=[]
xyr_result=[]
aj_result=[]
fornodeindata:
ajbh=node.get('ajbh')
ajbh_list=node.get('ajbh_list')
xyrbh_list=node.get('xyrbh_list')
ajbh_list.append(ajbh)
ajbh_list=list(set(node.get('ajbh_list')))
xyrbh_list=list(set(node.get('xyrbh_list')))
flag=True
iflen(aj_result)>0:
fori,valinenumerate(ajbh_list):
f=find(val,aj_result)
iff:
flag=False
break;
ifflag:
iflen(ajbh_list)>2andlen(xyrbh_list)>2:
aj.append(ajbh)
aj_result.append(ajbh_list)
xyr_result.append(xyrbh_list)
print('MATCHp=(:anjian{AJBH:"'+ajbh+'"})-[*]-()RETURNpLIMIT25')
name=str(len(xyrbh_list))+"人"+str(len(ajbh_list))+"案"
print(name)
print(len(aj_result))
print(aj)
print('----------------------------')
print(aj_result)
conn=psycopg2.connect(database="zfgfh",user="postgres",password="postgres",host="192.168.3.202",port="5432")
cursor=conn.cursor()
forajbhinaj_result:
fortempinajbh:
insert_sql="insertintotest.gm(\"ajbh\")values('%s')"
insert_sql=insert_sql%temp
print(insert_sql)
#插入
cursor.execute(insert_sql)
#提交
conn.commit()
cursor.close()#关闭Cursor
conn.close()#关闭数据库
6人3案 4人5案 3人6案 11人3案 3人13案 6人46案 8人4案 5人4案 7人4案 28人17案 4人4案 3人8案 4人4案 8人3案 6人6案 5人4案 4人6案 19人77案 4人22案 4人14案 4人5案 9人5案 12人8案 4人3案 17人4案 5人7案 18人30案 7人11案 3人22案 20人12案 30 ['A2301260500002019020002','A2301096000002018040010','A2301246400002018060001','A2301270500002018040003','A2301085100002018100001','A2301062020012018100099','A2301830517002018090003','A2301290501002019040001','A2301240500002018080001','A2301260200002018090006','A2301821414022018011647','A2301000514012018090001','A2301245100002018050014','A2301004908002018110004','A2301295500002018110005','A2301270300002018090005','A2301848900002018070017','A2301210504002018080011','A2301004902002018110002','A2301810500002018110038','A2301025103002018120002','A2301290500002019020003','A2301096000002018060043','A2301260200002018060002','A2301810500002018090002','A2301815100002018060014','A2301820506002018070006','A2301037200002018100154','A2301849000002018090001','A2301280200002018110002'] ---------------------------- ['A2301260500002019030006','A2301260500002019030007','A2301260500002019020002'] ['A2301095200002018060039','A2301096000002018050002','A2301096000002018060009','A2301095200002018070016','A2301096000002018040010'] ['A2301246400002018050003','A2301245200002018060007','A2301236400002018060005','A2301245200002018060003','A2301246400002018060002','A2301246400002018060001'] ['A2301270500002018040003','A2301270500002018040004','A2301270500002018040005'] ['A2301080506002018120002','A2301080506002018120001','A2301080506002018120011','A2301080506002018120004','A2301080506002018120010','A2301080506002018120013','A2301080506002018120005','A2301085100002018100001','A2301080506002018120012','A2301080506002018120007','A2301080506002018120006','A2301080506002018120003','A2301080506002018120009'] 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['A2301830517002018090003','A2301830517002018090005','A2301830517002018090006','A2301830517002018090004'] ['A2301290501002019040001','A2301290501002019040002','A2301290501002019030002','A2301290501002019040004'] ['A2301240500002018080001','A2301240500002018080004','A2301240500002018080003','A2301240500002018080002'] ['A2301260200002018100006','A2301260200002018090002','A2301260200002018100013','A2301260200002018100008','A2301260200002018090006','A2301260200002018100003','A2301260200002018100001','A2301260200002018100010','A2301260200002018100005','A2301260200002018100012','A2301260200002018100002','A2301260200002018090004','A2301260200002018100011','A2301260200002018090003','A2301260200002018100014','A2301260200002018090005','A2301260200002018100007'] ['A2323037100002018120006','A2301827600002018090005','A2301821414022018011647','A2301820209332018024067'] ['A2301000514012018090001','A2301230500002018060001','A2301000514012018110004','A2301230300002018110005','A2301230500002018050005','A2301000514012019010001','A2301000514012018090002','A2301000514012018100001'] ['A2301245100002018050014','A2301245100002018070018','A2301286100002018050005','A2301286100002018060002'] ['A2303016200002018100001','A2301004908002018110004','A2301004908002018110006'] ['A2301295500002018110008','A2301295500002018110006','A2301295500002018110003','A2301295500002018110007','A2301295500002018110005','A2301002104002018100007'] ['A2301270300002018100004','A2301270300002018100002','A2301270300002018100001','A2301270300002018090005'] ['A2301848900002018070017','A2301845700002018070027','A2301840502002018070002','A2301848800002018070024','A2301840502002018070003','A2301840502002018070001'] 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['A2301004906002019010005','A2301004902002018120001','A2301004902002018100006','A2301004908002018110002','A2301004902002018110002','A2301004906002019010003','A2301004904002019010003','A2301004908002019010002','A2301004902002018110003','A2301004908002019010004','A2301004908002018110001','A2301004905002019010008','A2301004904002018100004','A2301004908002019010005','A2301004904002019010004','A2301004909002019010001','A2301004905002019010007','A2301004908002019010003','A2301004904002019010002','A2301004908002018100002','A2301004902002018110001','A2301004906002019010004'] ['A2301810500002018120044','A2301810500002018110039','A2301810500002018110041','A2301810500002018120034','A2301810500002018120055','A2301810500002018120052','A2301810500002018120053','A2301810500002018120032','A2301810500002018110038','A2301810500002018120054','A2301810500002018120035','A2301810500002018110040','A2301810500002018120033','A2301810500002018120056'] ['A2301025103002019010002','A2301025103002018120002','A2301025103002018120004','A2301025103002018120005','A2301025103002019010001'] ['A2301290500002019020004','A2301293014052013074923','A2301292809352016111088','A2301290500002019020003','A2301290500002019030001'] ['A2301090506002018090006','A2301096000002018060044','A2301090506002018090002','A2301090506002018090004','A2301096000002018060045','A2301090506002018090005','A2301090506002018090003','A2301096000002018060043'] ['A2301260200002018070019','A2301260200002018060002','A2301260200002018070001'] ['A2301810500002018100008','A2301810500002018090002','A2301810500002018070015','A2301810500002018100006'] ['A2301815100002018060014','A2301847300002018070003','A2301837900002018060010','A2301847300002018070002','A2301835600002018060007','A2301815500002018050010','A2301817900002018060001'] 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以上这篇python实现查询Neo4j多节点的多层关系就是小编分享给大家的全部内容了，希望能给大家一个参考，也希望大家多多支持毛票票。
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