[neo4j] common operations of neo4j cypher and py2neo

Cypher

Document links : https://neo4j.com/docs/cypher-manual/4.3/.

1. establish

• Create a node
  create (n:teacher{name:“2”,id:”teacher1”}) return n
• Create relationships
  MATCH (a:TEST),(b:TEST)
  WHERE a.name = ‘TEST-NAME’ AND b.name = ‘TEST-NAME1’
  CREATE (a)-[r:RELTYPE] -> (b)
  RETURN r

2. Inquire about

• Show all
  MATCH(n) RETURN n
• Show 20 Nodes
  MATCH(n) RETURN n limit 20
• Query node
  MATCH(n:User{name:“2”}) RETURN n
• Query relationship
  match ()-[r:watch]->() return r
• Query nodes according to attributes
  match(n:course) where (n.marked=TRUE) return count(n)
• Query according to the relationship type
  match(n)-[r]->(m) where type=“teach” return n
• Query the number of nodes
  MATCH(n:User{name:“2”}) RETURN count(n)
• Query the number of nodes
  MATCH(n:User{name:“2”}) RETURN count(n)
• Query related nodes
  match(n) where ((n)-[]-()) return n
• It doesn't matter to query course node
  match(n:course) where not ((n)-[]-()) return n
• Query and course Unrelated nodes
  match(n) where not ((n)-[]-(p:course)) return n
• Query all labels of the node 、 Number of nodes per label
  MATCH (n) RETURN distinct labels(n), count(*)
• Inquire about ID It ends with ” mathematics ” The node of
  match(n) where n.id ENDS WITH ‘ mathematics ’ return n
• Inquire about ID The beginning is ” mathematics ” The node of
  match(n) where n.id START WITH ‘ mathematics ’ return n
  match(n) where n.id =~ ‘ mathematics .*’ return n
• Inquire about ID The beginning is ”and”( Case insensitive ) The node of
  match(n) where n.id =~ ‘(?!) mathematics .*’ return n
• Inquire about ID It ends with ”.com” The node of
  match(n) where n.id =~ ‘.*\.com’ return n
• Inquire about ID contain ” mathematics ” The node of
  match(n) where n.id CONTAINS ‘ mathematics ’ return n
• The query contains attributes name The node of
  match(n) where exists (n.name) return n
• Inquire about A Type or B Type of relationship
  match()->[r:A|:B]->() return r
• Find all the shortest paths between nodes
  match(n),(m),p=allShortestPaths((n)-[*]-(m))
• Find the shortest path between nodes , The maximum length of the path is 10
  match(n),(m),p=shortestPath((n)-[*…10]-(m)) return p
• Find the node 1~3 Jump in the relationship （ A little uncertain , Use with caution ）
  match(n)-[r:SHIP*1…3]-(m)
• Query and display multiple relationships
  MATCH p=()-[r:prerequisite]->(),q=()-[wr:taught]->() RETURN p,q

3. modify

Delete Used to delete graph elements （ node 、 Relationship 、 Or the path ）, To delete the relationship connected with it, use detach delete.
remove Statement is used to delete attributes and labels of graph elements .

• clear database
  match (n) detach delete n
• Add the attribute of the node ( If the node does not exist, a new node will be created )
  MERGE (n:Course) ON MATCH SET n.name=”yang”
• Delete nodes and their related relationships
  match (n:teacher) detach delete n
• Delete node properties
  match (n {name: “huzong”}) remove n.age
• Delete node labels
  match (n {name “huzong”}) remove n:teacher
• Delete multiple labels of nodes
  match (n {name “huzong”}) remove n:teacher:user
• Delete node / Relationship
  MATCH (n:User) -[r:study]-(p:Course{name:“f”}) DELETE n,r,p
• Set up with course Properties of nodes on the path related to nodes
  MATCH p = (t:course)-[r]-(A) FOREACH (n in nodes§| SET n.marked = TRUE )

4. Sort ORDER BY

Order by It's following RETURN perhaps WITH Clause of .

• Sort nodes according to attributes
  MATCH (n) RETURN n.name ORDER BY n.name,n.id
• The nodes are arranged in descending order
  MATCH (n) RETURN n.name ORDER BY n.name DESC

5. Import csv file （load csv）

Than admin slow , Than py2neo fast .

• LOAD CSV FROM “file:///entities/teacher.csv” AS row For subsequent use row[0]、row[1] To read the corresponding information , If the file has a header , Then use row.id and row.name To read the corresponding attribute value . Here is the absolute path , Files to be placed in import Under the table of contents .
  
• if csv The documents are very large , Then use USING PERIODIC COMMIT LOAD CSV FROM “file:///entities/teacher.csv” AS row

6. Indexes

• Create index
  create index on:Student(name)
• Delete index
  drop index on:Student(name)
• Create unique index
  create constraint on (s:Teacher) assert s.name is unique
• Delete unique index
  drop constraint on (s:Teacher) assert s.name is unique

py2neo

1. Connect to database

from py2neo import *
from py2neo.matching import *
test_graph = Graph(         #  Connect Neo4j,test_graph Name yourself , This is used for subsequent calls test_graph
    "http://localhost:7474",
    auth=("neo4j", "neo4j")    # The former is the user name , Followed by password 
)

Other header files that may be used ：

from py2neo.bulk import create_nodes
from py2neo.bulk import merge_nodes
from py2neo.bulk import create_relationships

2. Create nodes

a = Node("Person", name="Alice")    #  The front is the label ,name For attributes 
b = Node("Person", name="Bob")
test_graph.create(a)     # Put it into the database 
test_graph.create(b)
a.add_label("Employee")     #  Add tags ,a The label of becomes {
    'Employee', 'Person'}
print(set(a.labels))       # a Node label set aggregate 
a.remove_label("Employee")     #  Remove the label 
print(a.has_label("Person"))    # a If there is a label Person Then return to True
a.clear_labels()          #  Delete all labels of this node 

other ：
node[name] Return a file named name The value of the property .
node[name] = value Name it name The value of the property of is set to value.
del node[name] Remove from this node the name name Properties of .len(node) Returns the number of attributes on this node .
dict(node) Return the dictionary of all attributes in this node .
clear( ) Delete all attributes from this node .
values( ) Returns a list of all attribute values .
get（ name , Default = nothing ) Return a file named name The value of the property .

3. Create relationships

ab = Relationship(a, 'CALL', b)    #  The type of relationship is "CALL", Both relationships have attributes count, And the value is 1
ab['count'] = 1        #  Set the value of the relationship 
KNOWS = Relationship.type("KNOWS")         #  The relationship of another expression is established 
ba = KNOWS(b, a)
test_graph.create(ab)
test_graph.create(ba)
ab['count'] += 1              #  node / Attribute assignment of relation 
test_graph.push(ab)           #  Update of attribute value 
print(ba.nodes)    #  Print nodes  Start node and end node  2  Tuples .ba.end_node Indicates the end node .ba.start_node Indicates the start node .

other ：
del ba[‘count’] Delete attribute .
clear( ) Delete all attributes in this relationship .
…

4. Query nodes

nodes = NodeMatcher(test_graph)   # NodeMatcher Node matching 
keanu = nodes.match("Person", name="Keanu Reeves").first()  #  For simple equal matching of tags and attributes 
print(keanu)
nodes.match("Person", name=STARTS_WITH("John")).all()  #  Match name with “John” All nodes at the beginning ,
nodes.match("Person", born=ALL(GE(1964), LE(1966))).all()   #  Match was born in  1964  -  1966  year （ contain ） All of us 
nodeList = list(nodes.match().where("_.name=~‘ Yang .*’"))    #  Find a name to “ Yang ” All nodes at the beginning 
for i in nodeList:
    print(i)
nodeList = list(nodes.match().where("_.name=~‘ Yang .*’")).order_by("_.name").limit(4)   #  add “ Sort ”“ Limit the number of returns ”

other ：
IS_NULL( ),IS_NOT_NULL( ) Empty check predicate .
EQ( value ),NE( value ). Sort predicate LT( value ),LE( value ),GT( value ),GE( value ) Equality predicate .
…

5. Query relationship

relation_matcher = RelationshipMatcher(test_graph)
re = relation_matcher.match((a,), r_type="KNOWS").first()
print(re)
reList = list(relation_matcher.match())     # Query all relationships 

6. route

abc = Path(a, "CALL", b, Relationship(c, "KNOWS", b), c)
print(abc.nodes)
print(abc.relationships)
d, e = Node(name="Dave"), Node(name="Eve")
de = Path(d, "KNOWS", e)
abcde = Path(abc, "KNOWS", de)     #  Two Path Constitute a Path
for relationship in abcde.relationships:   #  Traverse Path Relationship on 
    print(relationship)

other ：
types( ) Returns a collection of all relationship types that exist on this path .
start_node.end_node.
…

7. Subgraphs Subgraph

A subgraph is an arbitrary set of nodes and relationships . A subgraph must contain at least one node , The empty subgraph should be None Express .

friends = ab | ba  #  Combine 
test_graph.create(friends)
print(friends)

other ：
keys( ).labels( ).nodes.relationships.types( ).
subgraph | other | …： Combine .
subgraph & other & …： intersection .
subgraph - other - …： reduce .
subgraph ^ other ^ …： Return to a new subgraph , The nodes and relationships contained in this subgraph only appear in subgraph Medium or other in , Nodes connected by relationships are also included in the new subgraph , Whether these nodes exist in subgraph perhaps other in .

8. call cypher Internal methods

You can use run Method to directly execute Cypher sentence , It returns a cursor cursors,cursors The results must be presented by traversal .

match_str = "match p=shortestPath((m:m Of label{name:'m Of name Property value '})-[r*1..4]-(n:n Of label{name:'name Property value '})) return p"
p1 = test_graph.run(match_str)
for p in p1:
    print(p)

9. Import csv File and process

import csv
with open('F:/neo4j/data/MOOCCube/subject/ Computer science and technology .csv', 'r', encoding='UTF-8') as f:
    next(f)   #  If the file has a header , You can make the file read from the second line 
    reader = csv.reader(f)
    for item in reader:
        # print(" The current number of lines ：", reader.line_num, " Current content ：", item)
        a = Node("Course", name=item[1], ID=item[0], subject=' Computer science and technology ')
        g.create(a)

Neo4j Database connection

stay cmd Input from the command line neo4j.bat console, After loading, open the web page in the browser http://localhost:7474/ You can use .

Other minor uses

1.neo4j–Cypher Grammar practice （WITH、 FOREACH、Aggregation、UNWIND、UNION、CALL）：
link : https://blog.csdn.net/qq_37503890/article/details/101565515?spm=1001.2101.3001.6650.1&utm_medium=distribute.pc_relevant.none-task-blog-2_defaultCTRLIST_{default-1.no_search_link&depth_1-utm_source=distribute.pc_relevant.none-task-blog-2}default_CTRLISTdefault-1.no_search_link
2.Py2neo Partial right node、relations、subgraph The little usage of ：
link : https://blog.csdn.net/claroja/article/details/84287093
3. Application of some methods in official documents ：
link : https://blog.csdn.net/Elenstone/article/details/106452464