import pandas as pd
from py2neo import Graph, Node, Relationship, NodeMatcher
# 读取Excel文件
df = pd.read_excel('./excels/santi.xlsx')
# 取前610行作为图谱数据
# df = df.iloc[:706, :]
# 连接Neo4j服务
graph = Graph(host="localhost://7474", auth=("neo4j", "jc147369"))
# 创建节点
nodes = set(df['S'].tolist() + df['O'].tolist())
for node in nodes:
node = Node("Node", name=node)
graph.create(node)
print('create nodes successfully!')
# 创建关系
matcher = NodeMatcher(graph)
for i in range(df.shape[0]):
S = df.iloc[i, :]['S'] # S节点
O = df.iloc[i, :]['O'] # O节点
s_node = matcher.match("Node", name=S).first()
o_node = matcher.match("Node", name=O).first()
# 创建关系
P = df.iloc[i, :]['P']
relationship = Relationship(s_node, P, o_node)
filepaths = getfiles()
for i in filepaths:
# f2 = open(i.replace(".xml", ".json"), 'w') # 将xml转换为json并保存到本地
# f2.write(xmlToJson(i))
# f2.close()
dir = xmltodict.parse(open(i, "r").read(), encoding='utf-8') # 将xml转换为字典
lis = [] # 用于暂时存储单行数据的list
lis.append(dir['WMS_Capabilities']['Service']['Title']) # 数据第一列：服务的标题
fNode = Node("WMS",
name=dir['WMS_Capabilities']['Service']['Title']) # 创建服务实体节点
myGraph.create(fNode) # 实体节点导入图谱
a = dir['WMS_Capabilities']['Capability']['Layer']
while type(a) != list and "Layer" in a.keys():
a = a['Layer']
if type(a) == list:
for List in a:
if "Title" in List.keys():
lis.append(List["Title"])
node_1 = Node('Title', content=List["Title"]) # 创建属性节点
Rel_1 = Relationship(fNode, "keyword",
node_1) # 创建实体节点与属性节点的关系
myGraph.create(node_1) # 属性节点导入图谱
myGraph.create(Rel_1) # 实体属性关系导入图谱
else:
def add_task(self, name, category):
task = Node('TodoTask', name=name)
cat = Node('TodoCategory', category=category)
rel = Relationship(task, 'CONCERN', cat)
graph.create(rel)
print(rel)
def get_query(text):
dates = []
tid = []
my_dict = {}
tx = graph.begin()
count = 0
for i in text:
dates.append(text[i]['datetime'])
tid.append(i)
my_dict[i] = text[i]['datetime']
dates, tid = zip(*sorted(zip(dates, tid)))
for i in range(len(tid)):
count += 1
ttid = tid[i]
if (count % 100 == 0):
print(count, time.time() - start_time)
tid_label = Node("tid",
tid=ttid,
lang=text[ttid]["lang"],
location=text[ttid]["location"],
date=text[ttid]["date"],
datetime=text[ttid]["datetime"],
quote_count=text[ttid]["quote_count"],
reply_count=text[ttid]["reply_count"],
like_count=text[ttid]["like_count"],
verified=text[ttid]["verified"],
sentiment=text[ttid]["sentiment"],
type=text[ttid]["type"],
tweet_text=text[ttid]["tweet_text"])
author_label = Node(
"author", author_id=text[ttid]
["author_id"]) #,author_sname=text[ttid]["author_screen_name"]);
author_name_label = Node("author_name",
author_name=text[ttid]["author"])
author_sname_label = Node(
"author_sname", author_sname=text[ttid]["author_screen_name"])
# # image_label=Node("image",image_url=text[ttid]["author_profile_image"])
# # date_label=Node("date",date=text[ttid]["date"],datetime=text[ttid]["datetime"])
# # location_label=Node("location",location=text[ttid]["location"])
# # lang_label=Node("lang",lang=text[ttid]["lang"])
# # lang_relation=Relationship(tid,"was tweeted in language",lang_label)
# # location_tid_relationship=Relationship(tid,'was tweeted from',location_label)
# # date_tid_relationship=Relationship(tid,"was tweeted on",date_label)
# # author_image_relationship=Relationship(author_label,"has image",image_label)
author_relationship = Relationship(tid_label, "has_author",
author_label)
author_s_relationship = Relationship(tid_label, "has_s_author",
author_sname_label)
author_name_relationshipo = Relationship(author_label, "has_name",
author_name_label)
glob_dictionary[ttid] = tid_label
tx.merge(tid_label)
tx.merge(author_label)
tx.merge(author_relationship)
tx.merge(author_name_relationshipo)
tx.merge(author_s_relationship)
# # tx.merge(lang_relation)
# # tx.merge(location_tid_relationship)
# # tx.merge(date_tid_relationship)
# # tx.merge(author_image_relationship)
# # print("here")
# # try:
# # tx.merge(author_relationship)
# # except:
# # print(author_label)
# # exit();
# # print("here")
if (text[ttid]["quoted_source_id"] != None):
quoted_dict[ttid] = text[ttid]["quoted_source_id"]
if (text[ttid]["retweet_source_id"] != None):
retweet_source_dict[ttid] = text[ttid]["retweet_source_id"]
if (text[ttid]["replyto_source_id"] != None):
replyto_source_dict[ttid] = text[ttid]["replyto_source_id"]
if (text[ttid]["hashtags"] != None):
for hasht_val in text[ttid]["hashtags"]:
hashtag_label = Node("hashtag", hashtag=hasht_val)
hashtag_relationship = Relationship(tid_label, "has_hashtag",
hashtag_label)
tx.merge(hashtag_label)
tx.merge(hashtag_relationship)
# if(text[ttid]["url_list"]!=None):
# for url_val in text[ttid]["url_list"]:
# url_label=Node("url",url=url_val)
# url_relationship=Relationship(tid_label,"has url_list",url_label)
# tx.merge(url_label)
# tx.merge(url_relationship)
if (text[ttid]["keywords_processed_list"] != None):
for key_val in text[ttid]["keywords_processed_list"]:
keywords_label = Node("keywords", keyword=key_val)
keywords_label_relationship = Relationship(
tid_label, "has_keyword", keywords_label)
tx.merge(keywords_label)
tx.merge(keywords_label_relationship)
if (text[ttid]["mentions"] != None):
for mention_val in text[ttid]["mentions"]:
mentions_label = Node("mentions", mentions=mention_val)
mentions_label_relationship = Relationship(
tid_label, "has_mention", mentions_label)
tx.merge(mentions_label)
tx.merge(mentions_label_relationship)
tx.commit()
def month(self, year, month):
path = Path(self.root, "YEAR", Node("Year", year=year),
"MONTH", Node("Month", year=year, month=month))
self.graph.create_unique(path)
return path.end_node
sql = "MATCH (n:`疾病`{名称:'%s'}) set n.治疗周期='%s'" % (b['名称'],
a['治疗周期'])
graph.run(sql)
# 医保/传染性暂不更新
else: # 如果不存在该疾病节点，则新建节点
# 创建疾病节点
node_jb = Node('疾病',
'寻医问药',
病因=b['病因'],
别称=b['别称'],
英文名=b['英文名'],
温馨提示=b['温馨提示'],
患病比例=b['患病比例'],
定义=b['定义'],
名称=b['名称'],
治疗费用=b['治疗费用'],
多发人群=b['多发人群'],
患病比例值=b['患病比例值'],
医保=b['医保'],
传染性=b['传染性'],
治疗周期=b['治疗周期'],
治愈率=b['治愈率'],
治愈率值=b['治愈率值'])
graph.merge(node_jb)
#更新科室
for ks in b['科室']:
if ks != '暂无数据':
sql = "MATCH (n:`科室`{名称:'%s'}) RETURN n.名称" % (ks)
m = graph.run(sql).data()
# override config file if ever
neo_db = {
'host': options.neohost or config_neo_db['host'],
'port': options.neoport or str(config_neo_db['port']),
'username': options.neousername or config_neo_db['username'],
'password': options.neopassword or config_neo_db['password']
}
n = CMgDB(neo_db)
file = open(options.jsonfile, 'r')
jsondata = json.load(file)
file.close()
for ip in jsondata:
neo_ip = Node('Ip', name=ip)
n.graph.merge(neo_ip)
neo_vlan = n.graph.run('match (v:Vlan) where v.id="' +
jsondata[ip]['vlan'] +
'" return v limit 1').evaluate()
if neo_vlan == None:
neo_vlan = Node('Vlan',
name=jsondata[ip]['vlan'],
id=jsondata[ip]['vlan'])
n.graph.merge(neo_vlan)
neo_nic = Node('Nic', name=jsondata[ip]['mac'])
if options.create:
n.graph.create(neo_nic)
else:
n.graph.merge(neo_nic)
n.link_nodes(neo_ip, neo_vlan, neo_nic)
def test_can_create_node(graph):
a = Node("Person", name="Alice")
with graph.begin() as tx:
tx.create(a)
assert a.graph == graph
assert a.identity is not None
from ip_renew import *
from bs4 import BeautifulSoup
import re
from py2neo import authenticate, Graph, Path, Node, Relationship
import requests
from py2neo import authenticate, Graph, Path, Node, Relationship
#from dbconnect import *
authenticate("localhost:7474", "neo4j", "password")
graph = Graph("http://localhost:7474/db/data")
labels = graph.node_labels
website_name = "exploit-db"
website_node = Node("Website", name=website_name)
graph.merge(website_node)
user_agent = 'Mozilla/5.0 (Windows; U; Windows NT 5.1; en-US; rv:1.9.0.7) Gecko/2009021910 Firefox/3.0.7'
headers = {'User-Agent': user_agent}
#authenticate("localhost:9066", "neo4j","password")
#graph = Graph("http://localhost:7474/db/data")
#website = "Oday-test"
#website_node = Node("Website", name=website)
#graph.create(website_node)
#website = "Oday-test"
#website_node = Node("Website", name=website)
#graph.create(website_node)
totalconcept = list(set(totalconcept))
conceptnode = concept.find({"_id": {
"$in": totalconcept
}}, {
"_id": 1,
"one_of_name": 1,
"definition": 1,
"semtype": 1
})
conceptnode = list(conceptnode)
for i in range(len(conceptnode)):
row = conceptnode[i]
if "definition" not in row:
tempnode = Node('&'.join(row["semtype"]),
name=row["_id"],
oneofname=row["one_of_name"])
else:
tempnode = Node('&'.join(row["semtype"]),
name=row["_id"],
definition=('|'.join(row["definition"])),
oneofname=row["one_of_name"])
g.create(tempnode)
if i % 1000 == 0:
print(i)
del (conceptnode)
def create_relationship(totalconcept):
count = 0
conceptnode = concept.find({"_id": {
password = str(os.environ.get('NEO4J_PASSWORD'))
user = '******'
# authenticate("localhost:7474", user, password)
g = Graph("http://localhost:7474/db/data/", password=password)
posts_file = '/home/srallaba/projects/dissertation/emnlp2020.tdd'
papers_file = 'data/papers.csv'
nodestuff_file = 'nodes.emnlp2020'
tx = g.begin()
g.delete_all()
# Create a node for the conference
conference = Node("Conferences", name='EMNLP 2020')
tx.create(conference)
tx.commit()
tx = g.begin()
# Populate nodes
nodes_dict = {}
f = open(nodestuff_file)
for line in f:
line = line.split('\n')[0].split(',')
if len(line) < 2:
continue
key, val1, val2 = line[0], line[1], line[2]
node = Node(val1, name=val2)
nodes_dict[key] = node
tx.create(node)
def add_fb_friends(self, friends):
user = self.find()
for friend in friends:
rel = Relationship(user, 'FRIEND', Node('User', name=friend['name'], id=friend['id']))
graph.merge(rel)
def add_fb_likes(self, likes):
user = self.find()
for like in likes:
rel = Relationship(user, 'LIKE', Node('Likes', name=like['name'], id=like['id']), created_time=like['created_time'])
graph.merge(rel)
if __name__ == '__main__':
data = ProcessXML('Ara2009.xml')
graph = Graph('bolt://palsson.di.uminho.pt:6092', auth=('neo4j', '123'))
compartments = data.getCompartments()
species = data.getSpecies()
reactions = data.getReactions()
dicReact = data.getReactionDict()
''' nodeC = Node("Compartment", id='C', name='Cytosol', model='Arabidopsis')
graph.create(nodeC)
nodeM = Node("Compartment", id='M', name='Mitochondrion', model='Arabidopsis')
graph.create(nodeM)
nodeE = Node("Compartment", id='E', name='Extracellular', model='Arabidopsis')
graph.create(nodeE)'''
matcher = NodeMatcher(graph)
nodeModel = Node('Model', id='Arabidopsis', name='Arabidopsis')
for spec in species.keys():
try:
if '_mit' in species[spec][0]:
id = species[spec][0].replace('_mit', '')
nodeSpec = matcher.match('Species').where(
'_.id="' + id + '"').where('_.compartment="' + 'M' + '"')
relation = Relationship(nodeModel, 'CONTAINS',
nodeSpec.first())
graph.create(relation)
elif 'x_' in species[spec][0]:
id = species[spec][0].replace('x_', '')
nodeSpec = matcher.match('Species').where(
'_.id="' + id + '"').where('_.compartment="' + 'E' + '"')
relation = Relationship(nodeModel, 'CONTAINS',
logging = logging.getLogger(__name__)
graph = Graph("http://192.168.1.100:7474", username="******", password='******')
graph.delete_all()
# graph.merge()
'''
1 —— 创建node，函数第一个参数是节点类型，第二个参数是value值
'''
# a = Node('PersonTest', name='张三',key='s')
# b = Node('PersonTest', name='张三',key='s')
# # r = Relationship(a, 'KNOWNS', b)
# s = a | b #| r
# graph.create(s)
tx = graph.begin()
a = Node('PersonTest', name='张三', key='s')
b = Node('PersonTest', name='张三1', key='s1', age=33)
tx.merge(a, 'PersonTest', 'name')
tx.merge(b, 'PersonTest', 'name')
tx.commit()
# a['地点']=['sf','sff']
# graph.push(a)
# graph.
json = {
'中文名称': ['北京故宫博物院'],
'历经朝代': ['明朝，清朝'],
'地点': ['中国北京'],
'外文名称': ['The Palace Museum'],
'建议游玩时长': ['3-4小时'],
elif layer.name != "IP" and layer.name != "Padding":
yield layer.name
counter += 1
# Reading PCAP file and accessing graph
packets = rdpcap("smallFlows.pcap")
g = Graph(password="******")
# Creating nodes, their relationships
# and adding them to the graph
for packet in packets:
layers = []
try:
a = Node("Host", name=packet.getlayer(IP).src)
b = Node("Host", name=packet.getlayer(IP).dst)
except AttributeError:
a = Node("Host", name=packet.getlayer(ARP).psrc)
b = Node("Host", name=packet.getlayer(ARP).pdst)
for layer in get_layers(packet):
layers.append(layer)
protocols = ':'.join(layers)
relation = Relationship.type(':'.join(
OrderedDict.fromkeys(protocols.split(':'))))
g.merge(relation(a, b), "Host", "name")
def filter(tailUrl):
url = 'https://en.wikipedia.org/wiki/' + tailUrl
if not re.search('\.(jpg|JPG)$', url):
if not ':' in t.get('href') and not '%' in t.get('href'):
return 1
headUrl = 'https://en.wikipedia.org/wiki/'
num = 1
k = 1
tailUrl = "Moon"
while True:
for n in range(1, 99):
textList = getHtml(tailUrl)
node1 = Node(label="FatherWord", name=tailUrl)
neo_graph.create(node1)
index = 0
try:
urlDict = {}
for t in textList:
if filter(tailUrl):
node2 = Node(label="SonWord", name=t.get_text())
neo_graph.create(node1)
node1TOnode2 = Relationship(node1, 'Include', node2)
neo_graph.create(node1TOnode2)
urlDict[index] = t.get_text()
index += 1
print('\r\n')
k += 1
tailUrl = urlDict[random.randint(2, 8)]
def push_in(graph, label, dname, ename=None, cname=None):
node = Node(label, ename=ename, cname=cname, xname=dname)
graph.merge(node)
def insert_neo(lable,name,pname):
c_node = Node(lable, name=name)
p_node = Node(lable, name=pname)
rel = Relationship(c_node, "ISA", p_node)
g.merge(rel)
# -*- coding: utf-8 -*-
"""...
"""
from py2neo import Database, Graph
from py2neo import Node, Relationship
if __name__ == '__main__':
default_db = Database(uri='bolt://localhost:7687')
default_db.forget_all()
# conf = default_db.config()
# grap = default_db.default_graph()
auth = ('neo4j', 'alxfed')
data = Graph(auth=auth, secure=False) # host='bolt://localhost:7687', encrypted=False,
data.delete_all()
a = Node("Person", name="Alice", age=33)
a.remove_label('Person')
b = Node("Person", name="Bob", age=44)
KNOWS = Relationship.type("KNOWS")
data.merge(KNOWS(a, b), "Person", "name")
print('\ndone')
text = json.load(fp)
fp.close()
current_file_number += 1
print("progress is = ", current_file_number, "/", 113, "time=",
time.time() - start_time)
print(x)
get_query(text)
tx = graph.begin()
count = 0
for i in retweet_source_dict:
count += 1
if (count % 100 == 0):
print(count, time.time() - start_time)
if (retweet_source_dict[i] not in glob_dictionary):
tid_label = Node("tid", tid=retweet_source_dict[i])
else:
tid_label = glob_dictionary[retweet_source_dict[i]]
tx.merge(Relationship(glob_dictionary[i], "retweeted_from", tid_label))
tx.commit()
tx = graph.begin()
count = 0
for i in replyto_source_dict:
count += 1
if (count % 100 == 0):
print(count, time.time() - start_time)
if (replyto_source_dict[i] not in glob_dictionary):
tid_label = Node("tid", tid=replyto_source_id[i])
else:
tid_label = glob_dictionary[replyto_source_id[i]]
if k.get('@class') == 'LOVES' or k.get('@class') == 'BEGETS' or k.get('@class') == 'HASSIBLING':
reco_rel[k.get("@rid")] = k
## NOEUDS
# TABLE CREATURE
a = 0
crea = {}
for k in reco_crea.items() :
d = k[1]
if d.get("@class") == "Creature":
a += 1
crea[k[0]] = Node("Creature", rid = d.get("@rid"), searchname = d.get("searchname"), uniquename = d.get("uniquename"), gender = d.get("gender"), race = d.get("race"), gatewaylink = d.get("gatewaylink"), born = d.get("born"), altname = d.get("altname"), died = d.get("died"), significance = d.get("significance"), name = d.get("name"), location = d.get("location"), illustrator = d.get("illustrator"))
graph.create(crea[k[0]])
print("On a bien ",a," noeuds creature (",len(reco_crea)," creatures comptees plus haut)")
# TABLE LOCATION
a = 0
loc = {}
for k in reco_loc.items() :
d = k[1]
if d.get("@class") == "Location":
a += 1
loc[k[0]] = Node("Location", rid = d.get("@rid"), significance = d.get("significance"), area = d.get("area"), searchname = d.get("searchname"), uniquename = d.get("uniquename"), gatewaylink = d.get("gatewaylink"), name = d.get("name"), altname = d.get("altname"), type = d.get("type"), age = d.get("age"), canon = d.get("canon"), illustrator = d.get("illustrator"))
graph.create(loc[k[0]])
print("On a bien ",a," noeuds location (",len(reco_loc)," locations comptees plus haut)")
def year(self, year):
path = Path(self.root, "YEAR", Node("Year", year=year))
self.graph.create_unique(path)
return path.end_node
from py2neo import Graph, Node, Relationship, NodeSelector
a = Node('Person', name='yzk')
b = Node('Person', name='whf')
r = Relationship(a, 'konws', b, since=1999)
s = a | b | r
graph = Graph('http://52.83.213.55:7474',
user='******',
password='******')
# graph.create(s)
select = NodeSelector(graph)
per = select.select('Person').where(name='yzk').first()
# print(per)
def day(self, year, month, day):
path = Path(self.root, "YEAR", Node("Year", year=year),
"MONTH", Node("Month", year=year, month=month),
"DAY", Node("Day", year=year, month=month, day=day))
self.graph.create_unique(path)
return path.end_node
def get_or_create_user(conn, cursor, google_id, googleAPIResponse):
name = googleAPIResponse.get('name', None)
if 'image' in googleAPIResponse:
image = googleAPIResponse['image']
url = image.get('url', None)
if url is None:
imgurl = None
else:
indexVal = url.find("?sz")
if indexVal != -1:
imgurl = url[0:indexVal]
else:
imgurl = url
else:
imgurl = None
if name is None:
givenName = None
displayName = None
familyName = None
else:
givenName = name.get('givenName', None)
displayName = givenName
familyName = name.get('familyName', None)
emails = googleAPIResponse.get('emails', None)
if emails is None:
email = None
else:
email = emails[0]['value']
gender = googleAPIResponse.get('gender', None)
organizations = googleAPIResponse.get('organizations', None)
if organizations is None:
organization = None
else:
organization = organizations[0]['name']
cursor.execute('select id from users where google_id=%s', [google_id])
row = cursor.fetchone()
if row is None:
# create user
cursor.execute('insert into users (google_id, email) values (%s,%s)',
[google_id, email])
result = cursor.lastrowid
conn.commit()
user = Node("User",
sql_id=result,
google_id=google_id,
email=email,
givenName=givenName,
familyName=familyName,
displayName=displayName,
user_type="subscriber",
organization=organization,
creation_time=timestamp(),
modified_time=timestamp(),
dob="",
gender=gender,
status=0,
image_url=imgurl)
social_graph().create(user)
else:
result = row[0]
user = User(result).find()
# There might be cases where the Neo4J does not have the corressponding User node
if user is None:
missing_user_neo4j = Node("User",
sql_id=result,
google_id=google_id,
email=email,
givenName=givenName,
familyName=familyName,
displayName=displayName,
user_type="subscriber",
organization=organization,
creation_time=timestamp(),
modified_time=timestamp(),
dob="",
gender=gender,
image_url=imgurl,
status=0)
social_graph().create(missing_user_neo4j)
else:
displayName = user['displayName']
session['uid'] = result
session['email'] = email
session['img'] = imgurl
# During Login, The Image Url Is Updated In Neo4J DB To Avoid The Image Discrepancies From Google Account
if imgurl is not None:
update_profile_image_url(result, imgurl)
if displayName is None:
displayName = ""
session['displayName'] = displayName
return result
industries = pd.read_csv(__location__ + dir + 'industries.txt', sep='\t')
industries.index = [i.split('_')[1] for i in industries['CodeTxt']]
industry_nodes = set([
i[0] for i in graph.run(
"MATCH (a:Industry) RETURN a.exo_code ").to_ndarray()
])
for missing in set(industries.index) - industry_nodes:
print('creating', missing, 'industry')
match = industries.loc[missing]
graph.create(
Node("Industry",
exo_code=missing,
description=match['Name'],
exo_CodeNR=match['CodeNr']))
#################################
nodes = dict(([i, countries.where("_.alpha3 = '%s'" % i).first()]
for i in set(Aindex[:, 0])))
industrynodes = dict(
([i, industry.where("_.description = '%s'" % i).first()]
for i in set(Aindex[:, 1])))
nonzero = np.array(A.nonzero()).T
print 'please wait'
# do this in parallel
"Ion Battery",
"Microprocessor",
"Wiring Loom",
# "Dioxite",
"Gold",
# "Silver",
"Paraffinium",
"Pure Ferrite",
"Ionised Cobalt"
# "Chlorine",
# "Sodium Nitrate",
# "Ammonia",
# "Phosphorus"
]
system = Node("System", name="IvtJen", race="Vy'Keen")
graph.merge(system, "System", "name")
SELLS = Relationship.type("SELLS")
trading = Node("Economy Type", name="Trading")
mercantile = Node("Economy", name="Mercantile")
shipping = Node("Economy", name="Shipping")
rel = Relationship(mercantile, "IS_A_TYPE_OF", trading)
graph.merge(rel, "Economy", "name")
rel = Relationship(shipping, "IS_A_TYPE_OF", trading)
graph.merge(rel, "Economy", "name")
power_generation_type = Node("Economy Type", name="Power Generation")
power_generation = Node("Economy", name="Power Generation")
relation_syn.append([i,row['name']])
for i in rels:
if row[i] != '0':
for j in row[i].strip().split('|'):
relation[i].append([row['name'],withouttypefind(j)])
if typefind(j) not in conceptclass:
conceptclass[typefind(j)] = []
conceptclass[typefind(j)].append(withouttypefind(j))
#create node
for key in conceptclass:
conceptclass[key] = list(set(conceptclass[key]))
count = 0
for key in conceptclass:
for n in conceptclass[key]:
node = Node(key, name=n)
g.create(node)
count += 1
def create_relationship(edges, rel_type):
count = 0
# 去重处理
set_edges = []
for edge in edges:
set_edges.append('###'.join(edge))
for edge in list(set(set_edges)):
edge = edge.split('###')
p = edge[0]
q = edge[1]
query = 'match(p),(q) where p.name="%s"and q.name="%s" create (p)-[r:%s{name:"%s"}]->(q)' % (p, q, rel_type, rel_type)
#try:
def create_node(cls, workbook):
"""建立馆室节点"""
room_sheet = workbook.sheet_by_index(0)
for i in range(1, room_sheet.nrows):
row = room_sheet.row_values(i)
name = row[0]
if row[0].find("_") != -1:
name_arr = row[0].split("_")
if len(name_arr) >= 3:
name = name_arr[2]
room_node = Node(
cls.room,
type=cls.room,
name=name,
office_name=row[0],
variant_name=row[1],
position=row[2],
service=row[3],
open_date=row[4],
phone=row[5],
monday_open=row[6],
monday_borrow=row[7],
tuseday_open=row[8],
tuseday_borrow=row[9],
wednesday_open=row[10],
wednesday_borrow=row[11],
thursday_open=row[12],
thursday_borrow=row[13],
friday_open=row[14],
friday_borrow=row[15],
saturday_open=row[16],
saturday_borrow=row[17],
sunday_open=row[18],
sunday_borrow=row[19],
#area=row[20],floor=row[21],
certification=row[22])
cls.graph.create(room_node)
"""建立馆区节点"""
building_sheet = workbook.sheet_by_index(1)
for i in range(1, building_sheet.nrows):
row = building_sheet.row_values(i)
name = row[0]
#print(name)
building_node = Node(cls.building,
type=cls.building,
name=name,
office_name=row[0],
variant_name=row[1])
cls.graph.create(building_node)
"""建立楼层节点"""
floor_sheet = workbook.sheet_by_index(3)
for i in range(1, floor_sheet.nrows):
row = floor_sheet.row_values(i)
name = row[0]
#print(name)
floor_node = Node(
cls.floor,
type=cls.floor,
name=name,
office_name=row[0],
variant_name=row[1],
#area=row[2],
upstair=row[3],
downstair=row[4])
cls.graph.create(floor_node)
"""建立资源节点"""
resource_sheet = workbook.sheet_by_index(2)
for i in range(1, resource_sheet.nrows):
row = resource_sheet.row_values(i)
name = row[0]
if row[0].find("_") != -1:
name = row[0].split("_")[1]
# print(name)
resource_node = Node(
cls.resource,
type=cls.resource,
name=name,
office_name=row[0],
variant_name=row[1],
describe=row[2],
count=row[3],
#room=row[4],
belong=row[5])
cls.graph.create(resource_node)
