Introduction to py2neo

Introducing

py2neo

[email protected] py2neo.org@technige @py2neo

Me...

Where does py2neo fit in?

Neo4j

REST Server

(your app)

py2neo

GET /db/data/200 OK

Coming Up...

● Connecting & Creating● Property Containers● Indexes & Uniqueness● Cypher & Geoff● Installation● Future Plans

Connecting & Creating

Default Connections

>>> from py2neo import neo4j

>>> graph_db = neo4j.GraphDatabaseService()

default connection is made to <http://localhost:7474/db/data/>

Custom Connections

>>> from py2neo import neo4j

>>> uri = "http://otherserv:9999/db/data/"

>>> graph_db = neo4j.GraphDatabaseService(uri)

>>> graph_db.neo4j_version

(1, 8, u'M04', 1, u'g892e348')

A few simple methods...

>>> graph_db.get_node(0)

Node('http://localhost:7474/db/data/node/0')

>>> graph_db.get_reference_node()


>>> graph_db.get_node_count()

1

>>> graph_db.get_relationship_count()

0

Sample data: a family tree

All characters appearing in this work are fictitious. Any resemblance to real persons, living or dead, is purely coincidental.

Phil (1921) Liz (1926)

Anne (1950)Chaz (1948) Andy (1960) Ed (1964)

m(1947)

create

nodes = graph_db.create(

{"name": "Phil", "born": 1921},

{"name": "Liz", "born": 1926},

{"name": "Chaz", "born": 1948},

{"name": "Anne", "born": 1950},

{"name": "Andy", "born": 1960},

{"name": "Ed", "born": 1964},

)

Phil Liz

Chaz Anne

Andy Ed

list of nodes

create

rels = graph_db.create(

(phil, "MARRIED", liz),

(chaz, "FATHER", phil),

(chaz, "MOTHER", liz),

)

Phil Liz

Chaz

MARRIED

MOTHER FATHER

node must already exist

list of relationships

create

family = graph_db.create(

{"name": "Phil", "born": 1921}, {"name": "Liz", "born": 1926},

{"name": "Chaz", "born": 1948}, {"name": "Anne", "born": 1950},

{"name": "Andy", "born": 1960}, {"name": "Ed", "born": 1964},

(0, "MARRIED", 1, {"year": 1947, "place": "London"}),

(2, "FATHER", 0), (3, "FATHER", 0),

(4, "FATHER", 0), (5, "FATHER", 0),

(2, "MOTHER", 1), (3, "MOTHER", 1),

(4, "MOTHER", 1), (5, "MOTHER", 1),

)

create

family = graph_db.create(

{"name": "Phil", "born": 1921}, {"name": "Liz", "born": 1926},

{"name": "Chaz", "born": 1948}, {"name": "Anne", "born": 1950},

{"name": "Andy", "born": 1960}, {"name": "Ed", "born": 1964},

(0, "MARRIED", 1, {"year": 1947, "place": "London"}),

(2, "FATHER", 0), (3, "FATHER", 0),

(4, "FATHER", 0), (5, "FATHER", 0),

(2, "MOTHER", 1), (3, "MOTHER", 1),

(4, "MOTHER", 1), (5, "MOTHER", 1),

)

nodes, rels = family[0:6], family[6:]

phil, liz, chaz, anne, andy, ed = nodes

list of nodes and relationships

node defined in same batch

relationship properties

Property Containers

neo4j.PropertyContainer

Node Relationship

PropertyContainer

PropertyContainers implement many of the

container methods defined by the Python standard

<http://docs.python.org/reference/datamodel.html#emulating-container-types>

neo4j.PropertyContainer

# update properties

liz["star_sign"] = "Taurus"

# query properties

for node in nodes:

name = node["name"]

if "star_sign" in node:

print name + " is a node["star_sign"]

else:

print name + " doesn't believe in horoscopes"

set property

get property

test property containment

neo4j.Node

Node Relationship

PropertyContainer

Relationships and Related Nodes

parental_rels = liz.get_relationships(

neo4j.Direction.INCOMING, "MOTHER"

)

parental_rels = liz.get_relationships_with(

chaz, neo4j.Direction.INCOMING, "MOTHER"

)

children = liz.get_related_nodes(

neo4j.Direction.INCOMING, "MOTHER"

)

Liz

Chaz

Anne

Liz

Chaz

Anne

Liz

Chaz

Anne

Relationships and Related Nodes

>>> liz.has_relationship(neo4j.Direction.BOTH, "MARRIED")

True

>>> anne.is_related_to(phil, neo4j.Direction.OUTGOING, "FATHER")

True

>>> ed.is_related_to(andy, neo4j.Direction.BOTH, "BROTHER")

False

could also specify multiple types

neo4j.Relationship

Node Relationship

PropertyContainer

neo4j.Relationship

>>> rels[0].start_node


>>> rels[0].end_node


>>> rels[0].type

'MARRIED'

More sample data: a second tree

George (1895) Betty (1900)

Liz (1926) Maggie (1930)

m

Phil (1921) Liz (1926)

Anne (1950)Chaz (1948) Andy (1960) Ed (1964)

m(1947)


Liz (1926) Maggie (1930)

m

Phil (1921) Liz (1926)

Anne (1950)Chaz (1948) Andy (1960) Ed (1964)

m(1947)


Liz (1926) Maggie (1930)

m

same person

How can we avoid duplicate nodes?

Indexes

Indexing the first family...

>>> people = graph_db.get_or_create_index(neo4j.Node, "People")

>>> for node in nodes:

... people.add("name", node["name"], node)

>>> people.get("name", "Liz")

[Node('http://localhost:7474/db/data/node/2')]

list of matching entities

...and the second

>>> new_props = [

... {"name": "George", "born": 1895},

... {"name": "Betty", "born": 1900},

... {"name": "Liz", "born": 1926},

... {"name": "Maggie", "born": 1930},

... ]

>>> george, betty, liz, maggie = [

... people.get_or_create("name", prop["name"], prop)

... for prop in new_props

... ]

>>> people.get("name", "Liz")

[Node('http://localhost:7474/db/data/node/2')]

same node as before

People

name Andy

name Anne

name Betty

name Chaz

name Ed

name George

name Liz

name Maggie

name Phil

A Quick Query

>>> people.query("name:*e*")

[Node('http://localhost:7474/db/data/node/4'),

Node('http://localhost:7474/db/data/node/7'),

Node('http://localhost:7474/db/data/node/8'),

Node('http://localhost:7474/db/data/node/9')]

Maggie

Anne

Betty

George

We've added the nodes... what about the relationships?

Cypher & Geoff

Cypher RELATE

START a=node(1), b=node(2)

RELATE (a)-[ab:KNOWS]->(b)

RETURN ab

Cypher RELATE

a b RELATE a b

a b RELATE a b

a b RELATE !

relate

new_rels = graph_db.relate(

(george, "MARRIED", betty),

(liz, "FATHER", george),

(maggie, "FATHER", george),

(liz, "MOTHER", betty),

(maggie, "MOTHER", betty),

)George Betty

Maggie

MARRIED

MOTHERFATHER

Liz

FATHER MOTHER

For relationships,

relate can be seen as an idempotent

alternative to create

cypher.execute

>>> from py2neo import cypher

>>> query = "START q=node(1) RETURN q"

>>> data, metadata = cypher.execute(graph_db, query)

>>> for row in data:

... q = row[0]

... print q

first column

cypher.execute

>>> from py2neo import cypher

>>> query = "START q=node(1) RETURN q"

>>> data, metadata = cypher.execute(graph_db, query)

>>> for row in data:

... q = row[0]

... print q

available only after all rows received

first column

cypher.execute

query = "START q=node(1) RETURN q"

def print_row(row):

q = row[0]

print row

cypher.execute(graph_db, query, row_handler=print_row)

executed once per row as each row is received

Command Line Cypherelgin@forge:~% cypher "start a=node(1) match (a)-[:MARRIED]->(b) return a, b"

+------------------------------------------------------------------+

| a | b |

+------------------------------------------------------------------+

| (1) {"name":"Phil","born":1921} | (2) {"name":"Liz","born":1926} |

+------------------------------------------------------------------+

elgin@forge:~% cypher -f csv "start a=node(1) match (a)-[ab:MARRIED]->(b) return a, ab, b"

"a","ab","b"

"(1)","(1)-[0:MARRIED]->(2)","(2)"

elgin@forge:~% cypher -f json "start a=node(1) match (a)-[ab:MARRIED]->(b) return a, ab, b"

[

{"a": "(1)", "ab": "(1)-[0:MARRIED]->(2)", "b": "(2)"}

]

elgin@forge:~% cypher -f geoff "start a=node(1) match (a)-[ab:MARRIED]->(b) return a, ab, b"

(1) {"name": "Phil", "born": 1921}

(2) {"name": "Liz", "born": 1926}

(1)-[0:MARRIED]->(2) {"year": 1947, "place": "London"}

Geoff is to graph dataas

CSV is to tabular data

<http://geoff.nigelsmall.net/>

elgin@forge:~% cypher -f geoff "start n=node(*), r=rel(*) return n, r"

(0) {}

(1) {"born": 1921, "name": "Phil", "family": "Windsor"}

(2) {"born": 1926, "star_sign": "Taurus", "family": "Windsor", "name": "Liz"}

(3) {"born": 1948, "name": "Chaz", "family": "Windsor"}

(4) {"born": 1950, "name": "Anne", "family": "Windsor"}

(5) {"born": 1960, "name": "Andy", "family": "Windsor"}

(6) {"born": 1964, "name": "Ed", "family": "Windsor"}

(7) {"born": 1895, "name": "George"}

(8) {"born": 1900, "name": "Betty"}

(9) {"born": 1930, "name": "Maggie"}

(1)-[0:MARRIED]->(2) {"place": "London", "year": 1947}

(3)-[1:FATHER]->(1) {}

(4)-[2:FATHER]->(1) {}

(5)-[3:FATHER]->(1) {}

(6)-[4:FATHER]->(1) {}

(3)-[5:MOTHER]->(2) {}

(4)-[6:MOTHER]->(2) {}

(5)-[7:MOTHER]->(2) {}

(6)-[8:MOTHER]->(2) {}

(7)-[9:MARRIED]->(8) {}

(2)-[10:FATHER]->(7) {}

(9)-[11:FATHER]->(7) {}

(2)-[12:MOTHER]->(8) {}

(9)-[13:MOTHER]->(8) {}

Neo4j Console

Installation

Requirements

● Python 2.6+ <http://python.org/>● Tornado 2.2.1 <http://www.tornadoweb.org/>● Neo4j 1.6+ <http://neo4j.org/>

Installation

<http://pypi.python.org/pypi/py2neo>

elgin@forge:~% sudo pip install py2neo

elgin@forge:~% sudo pip install --upgrade py2neo

Source Code

<https://github.com/nigelsmall/py2neo>

elgin@forge:~% git clone [email protected]:nigelsmall/py2neo.git

Future Plans

● Fast HTTP● Multi-threading support● Python 3● Command line tools● Property caching● Test harness for multiple Neo4j versions● New methods, e.g. get_paths_to

EOF

[email protected] py2neo.org@technige @py2neo

Technology

Introduction to py2neo