2. py2neo.database
– Graph Databases¶
The py2neo.database
package contains classes and functions required to interact with a Neo4j server.
The most important of these is the Graph
class which represents a Neo4j graph database instance and provides access to a large portion of the most commonly used py2neo API.
To run a query against a local database is straightforward:
>>> from py2neo import Graph
>>> graph = Graph(password="password")
>>> graph.run("UNWIND range(1, 10) AS n RETURN n, n * n as n_sq").dump()
n n_sq
----------
1 1
2 4
3 9
4 16
5 25
6 36
7 49
8 64
9 81
10 100
Note
The previous version of py2neo allowed Cypher execution through Graph.cypher.execute()
.
This facility is now instead accessible via Graph.run()
and returns a lazily-evaluated Cursor
rather than an eagerly-evaluated RecordList
.
2.1. The Graph¶
- class py2neo.database.Graph(*uris, **settings)[source]¶
The Graph class represents a Neo4j graph database. Connection details are provided using URIs and/or individual settings. For any given Graph, the following protocol combinations are supported:
HTTP
HTTPS
Bolt + HTTP
Bolt/TLS + HTTPS
Note that either HTTP or HTTPS must be enabled to allow for discovery and for some legacy features to be supported.
The full set of settings supported are:
Keyword
Description
Type(s)
Default
bolt
Use Bolt* protocol (None means autodetect)
bool,
None
None
secure
Use a secure connection (Bolt/TLS + HTTPS)
bool
False
host
Database server host name
str
'localhost'
http_port
Port for HTTP traffic
int
7474
https_port
Port for HTTPS traffic
int
7473
bolt_port
Port for Bolt traffic
int
7687
user
User to authenticate as
str
'neo4j'
password
Password to use for authentication
str
no default
* The new Bolt binary protocol is the successor to HTTP and available in Neo4j 3.0 and above.
Each setting can be provided as a keyword argument or as part of an
http:
,https:
orbolt:
URI. Therefore, the examples below are equivalent:>>> from py2neo import Graph >>> graph_1 = Graph() >>> graph_2 = Graph(host="localhost") >>> graph_3 = Graph("http://localhost:7474/db/data/")
Once obtained, the Graph instance provides direct or indirect access to most of the functionality available within py2neo. If Bolt is available (Neo4j 3.0 and above) and Bolt auto-detection is enabled, this will be used for Cypher queries instead of HTTP.
- begin(autocommit=False)[source]¶
Begin a new
Transaction
.- Parameters:
autocommit – if
True
, the transaction will automatically commit after the first operation
- create(subgraph)[source]¶
Run a
Transaction.create()
operation within an autocommitTransaction
.- Parameters:
subgraph – a
Node
,Relationship
or otherSubgraph
- data(statement, parameters=None, **kwparameters)[source]¶
Run a
Transaction.run()
operation within an autocommitTransaction
and extract the data as a list of dictionaries.For example:
>>> from py2neo import Graph >>> graph = Graph(password="excalibur") >>> graph.data("MATCH (a:Person) RETURN a.name, a.born LIMIT 4") [{'a.born': 1964, 'a.name': 'Keanu Reeves'}, {'a.born': 1967, 'a.name': 'Carrie-Anne Moss'}, {'a.born': 1961, 'a.name': 'Laurence Fishburne'}, {'a.born': 1960, 'a.name': 'Hugo Weaving'}]
The extracted data can then be easily passed into an external data handler such as a pandas.DataFrame for subsequent processing:
>>> from pandas import DataFrame >>> DataFrame(graph.data("MATCH (a:Person) RETURN a.name, a.born LIMIT 4")) a.born a.name 0 1964 Keanu Reeves 1 1967 Carrie-Anne Moss 2 1961 Laurence Fishburne 3 1960 Hugo Weaving
See also
- Parameters:
statement – Cypher statement
parameters – dictionary of parameters
kwparameters – additional keyword parameters
- Returns:
the full query result
- Return type:
list of dict
- degree(subgraph)[source]¶
Run a
Transaction.degree()
operation within an autocommitTransaction
.- Parameters:
subgraph – a
Node
,Relationship
or otherSubgraph
object- Returns:
the total degree of all nodes in the subgraph
- delete(subgraph)[source]¶
Run a
Transaction.delete()
operation within an autocommitTransaction
. To delete only the relationships, use theseparate()
method.- Parameters:
subgraph – a
Node
,Relationship
or otherSubgraph
object
- delete_all()[source]¶
Delete all nodes and relationships from this
Graph
.Warning
This method will permanently remove all nodes and relationships from the graph and cannot be undone.
- evaluate(statement, parameters=None, **kwparameters)[source]¶
Run a
Transaction.evaluate()
operation within an autocommitTransaction
.- Parameters:
statement – Cypher statement
parameters – dictionary of parameters
- Returns:
first value from the first record returned or
None
.
- exists(subgraph)[source]¶
Run a
Transaction.exists()
operation within an autocommitTransaction
.- Parameters:
subgraph – a
Node
,Relationship
or otherSubgraph
object- Returns:
- find(**kwargs)¶
Yield all nodes with a given label, optionally filtering by property key and value.
- Parameters:
label – node label to match
property_key – property key to match
property_value – property value to match; if a tuple or set is provided, any of these values may be matched
limit – maximum number of nodes to match
- find_one(**kwargs)¶
Find a single node by label and optional property. This method is intended to be used with a unique constraint and does not fail if more than one matching node is found.
- Parameters:
label – node label to match
property_key – property key to match
property_value – property value to match; if a tuple or set is provided, any of these values may be matched
- match(start_node=None, rel_type=None, end_node=None, bidirectional=False, limit=None)[source]¶
Match and return all relationships with specific criteria.
For example, to find all of Alice’s friends:
for rel in graph.match(start_node=alice, rel_type="FRIEND"): print(rel.end_node()["name"])
- Parameters:
start_node – start node of relationships to match (
None
means any node)rel_type – type of relationships to match (
None
means any type)end_node – end node of relationships to match (
None
means any node)bidirectional –
True
if reversed relationships should also be includedlimit – maximum number of relationships to match (
None
means unlimited)
- match_one(start_node=None, rel_type=None, end_node=None, bidirectional=False)[source]¶
Match and return one relationship with specific criteria.
- Parameters:
start_node – start node of relationships to match (
None
means any node)rel_type – type of relationships to match (
None
means any type)end_node – end node of relationships to match (
None
means any node)bidirectional –
True
if reversed relationships should also be included
- merge(subgraph, label=None, *property_keys)[source]¶
Run a
Transaction.merge()
operation within an autocommitTransaction
.- Parameters:
subgraph – a
Node
,Relationship
or otherSubgraph
objectlabel – label on which to match any existing nodes
property_keys – property keys on which to match any existing nodes
- node(id_)[source]¶
Fetch a node by ID. This method creates an object representing the remote node with the ID specified but fetches no data from the server. For this reason, there is no guarantee that the entity returned actually exists.
- Parameters:
id –
- property node_labels¶
The set of node labels currently defined within the graph.
- open_browser()[source]¶
Open a page in the default system web browser pointing at the Neo4j browser application for this graph.
- pull(subgraph)[source]¶
Pull data to one or more entities from their remote counterparts.
- Parameters:
subgraph – the collection of nodes and relationships to pull
- push(subgraph)[source]¶
Push data from one or more entities to their remote counterparts.
- Parameters:
subgraph – the collection of nodes and relationships to push
- property relationship_types¶
The set of relationship types currently defined within the graph.
- run(statement, parameters=None, **kwparameters)[source]¶
Run a
Transaction.run()
operation within an autocommitTransaction
.- Parameters:
statement – Cypher statement
parameters – dictionary of parameters
- Returns:
- separate(subgraph)[source]¶
Run a
Transaction.separate()
operation within an autocommitTransaction
.- Parameters:
subgraph – a
Node
,Relationship
or otherSubgraph
- class py2neo.database.Schema(uri)[source]¶
The schema resource attached to a Graph instance.
- create_index(label, property_key)[source]¶
Create a schema index for a label and property key combination.
- create_uniqueness_constraint(label, property_key)[source]¶
Create a uniqueness constraint for a label.
2.2. Transactions¶
- class py2neo.database.Transaction(autocommit=False)[source]¶
A transaction is a transient resource that allows multiple Cypher statements to be executed within a single server transaction.
- create(subgraph)[source]¶
Create remote nodes and relationships that correspond to those in a local subgraph. Any entities in subgraph that are already bound to remote entities will remain unchanged, those which are not will become bound to their newly-created counterparts.
For example:
>>> from py2neo import Graph, Node, Relationship >>> g = Graph() >>> tx = g.begin() >>> a = Node("Person", name="Alice") >>> tx.create(a) >>> b = Node("Person", name="Bob") >>> ab = Relationship(a, "KNOWS", b) >>> tx.create(ab) >>> tx.commit() >>> g.exists(ab) True
- Parameters:
subgraph – a
Node
,Relationship
or other creatable object
- degree(subgraph)[source]¶
Return the total number of relationships attached to all nodes in a subgraph.
- Parameters:
subgraph – a
Node
,Relationship
or otherSubgraph
- Returns:
the total number of distinct relationships
- delete(subgraph)[source]¶
Delete the remote nodes and relationships that correspond to those in a local subgraph. To delete only the relationships, use the
separate()
method.- Parameters:
subgraph – a
Node
,Relationship
or otherSubgraph
- evaluate(statement, parameters=None, **kwparameters)[source]¶
Execute a single Cypher statement and return the value from the first column of the first record.
- Parameters:
statement – Cypher statement
parameters – dictionary of parameters
- Returns:
single return value or
None
- exists(subgraph)[source]¶
Determine whether one or more graph entities all exist within the database. Note that if any nodes or relationships in subgraph are not bound to remote counterparts, this method will return
False
.- Parameters:
subgraph – a
Node
,Relationship
or otherSubgraph
- Returns:
True
if all entities exist remotely,False
otherwise
- merge(subgraph, primary_label=None, primary_key=None)[source]¶
Merge nodes and relationships from a local subgraph into the database. Each node and relationship is merged independently, with nodes merged first and relationships merged second.
For each node, the merge is carried out by comparing that node with a potential remote equivalent on the basis of a label and property value. If no remote match is found, a new node is created. The label and property to use for comparison are determined by primary_label and primary_key but may be overridden for individual nodes by the presence of __primarylabel__ and __primarykey__ attributes on the node itself. Note that multiple property keys may be specified by using a tuple.
For each relationship, the merge is carried out by comparing that relationship with a potential remote equivalent on the basis of matching start and end nodes plus relationship type. If no remote match is found, a new relationship is created.
- Parameters:
subgraph – a
Node
,Relationship
or otherSubgraph
objectprimary_label – label on which to match any existing nodes
primary_key – property key(s) on which to match any existing nodes
- run(statement, parameters=None, **kwparameters)[source]¶
Send a Cypher statement to the server for execution and return a
Cursor
for navigating its result.- Parameters:
statement – Cypher statement
parameters – dictionary of parameters
- Returns:
Cursor
object
- separate(subgraph)[source]¶
Delete the remote relationships that correspond to those in a local subgraph. This leaves any nodes untouched.
- Parameters:
subgraph – a
Node
,Relationship
or otherSubgraph
2.3. Cursors¶
- class py2neo.database.Cursor(source)[source]¶
A Cursor is a navigator for a stream of records.
A cursor can be thought of as a window onto an underlying data stream. All cursors in py2neo are “forward-only”, meaning that navigation starts before the first record and may proceed only in a forward direction.
It is not generally necessary for application code to instantiate a cursor directly as one will be returned by any Cypher execution method. However, cursor creation requires only a
DataSource
object which contains the logic for how to access the source data that the cursor navigates.Many simple cursor use cases require only the
forward()
method and thecurrent
attribute. To navigate through all available records, a while loop can be used:while cursor.forward(): print(cursor.current()["name"])
If only the first record is of interest, a similar if structure will do the job:
if cursor.forward(): print(cursor.current()["name"])
To combine forward and current into a single step, use
next
:print(cursor.next()["name"])
Cursors are also iterable, so can be used in a loop:
for record in cursor: print(record["name"])
For queries that are expected to return only a single value within a single record, use the
evaluate()
method. This will return the first value from the next record orNone
if neither the field nor the record are present:print(cursor.evaluate())
- data()[source]¶
Consume and extract the entire result as a list of dictionaries. This method generates a self-contained set of result data using only Python-native data types.
>>> from py2neo import Graph >>> graph = Graph(password="excalibur") >>> graph.run("MATCH (a:Person) RETURN a.name, a.born LIMIT 4").data() [{'a.born': 1964, 'a.name': 'Keanu Reeves'}, {'a.born': 1967, 'a.name': 'Carrie-Anne Moss'}, {'a.born': 1961, 'a.name': 'Laurence Fishburne'}, {'a.born': 1960, 'a.name': 'Hugo Weaving'}]
The extracted data can then be easily passed into an external data handler such as a pandas.DataFrame for subsequent processing:
>>> from pandas import DataFrame >>> DataFrame(graph.run("MATCH (a:Person) RETURN a.name, a.born LIMIT 4").data()) a.born a.name 0 1964 Keanu Reeves 1 1967 Carrie-Anne Moss 2 1961 Laurence Fishburne 3 1960 Hugo Weaving
Similarly, to output the result data as a JSON-formatted string:
>>> import json >>> json.dumps(graph.run("UNWIND range(1, 3) AS n RETURN n").data()) '[{"n": 1}, {"n": 2}, {"n": 3}]'
- Returns:
the full query result
- Return type:
list of dict
- dump(out=<_io.TextIOWrapper name='<stdout>' mode='w' encoding='utf-8'>)[source]¶
Consume all records from this cursor and write in tabular form to the console.
- Parameters:
out – the channel to which output should be dumped
- evaluate(field=0)[source]¶
Return the value of the first field from the next record (or the value of another field if explicitly specified).
This method attempts to move the cursor one step forward and, if successful, selects and returns an individual value from the new current record. By default, this value will be taken from the first value in that record but this can be overridden with the field argument, which can represent either a positional index or a textual key.
If the cursor cannot be moved forward or if the record contains no values,
None
will be returned instead.This method is particularly useful when it is known that a Cypher query returns only a single value.
- Parameters:
field – field to select value from (optional)
- Returns:
value of the field or
None
Example
>>> from py2neo import Graph >>> g = Graph() >>> g.run("MATCH (a) WHERE a.email={x} RETURN a.name", x="bob@acme.com").evaluate() 'Bob Robertson'
- forward(amount=1)[source]¶
Attempt to move the cursor one position forward (or by another amount if explicitly specified). The cursor will move position by up to, but never more than, the amount specified. If not enough scope for movement remains, only that remainder will be consumed. The total amount moved is returned.
- Parameters:
amount – the amount to move the cursor
- Returns:
the amount that the cursor was able to move
- class py2neo.database.Record[source]¶
A
Record
holds a collection of result values that are both indexed by position and keyed by name. A Record instance can therefore be seen as a combination of a tuple and a Mapping.- record[index]
- record[key]
Return the value of record with the specified key or index.
- len(record)
Return the number of fields in record.
- dict(record)
Return a dict representation of record.
2.4. The DBMS¶
- class py2neo.database.DBMS(*uris, **settings)[source]¶
Accessor for the entire database management system belonging to a Neo4j server installation. This corresponds to the root URI in the HTTP API.
An explicit URI can be passed to the constructor:
>>> from py2neo import DBMS >>> my_dbms = DBMS("http://myserver:7474/")
Alternatively, the default value of
http://localhost:7474/
is used:>>> default_dbms = DBMS() >>> default_dbms <DBMS uri='http://localhost:7474/'>
- property config¶
Return a dictionary of the configuration parameters used to configure Neo4j.
- property database_name¶
Return the name of the active Neo4j database.
- property graph¶
The default graph database exposed by this database management system.
- Return type:
- property kernel_start_time¶
Return the time from which this Neo4j instance was in operational mode.
- property kernel_version¶
Return the version of Neo4j.
- property primitive_counts¶
Return a dictionary of estimates of the numbers of different kinds of Neo4j primitives.
- property store_creation_time¶
Return the time when this Neo4j graph store was created.
- property store_directory¶
Return the location of the Neo4j store.
- property store_file_sizes¶
Return a dictionary of file sizes for each file in the Neo4j graph store.
- property store_id¶
Return an identifier that, together with store creation time, uniquely identifies this Neo4j graph store.
- property supports_auth¶
Returns
True
if auth is supported by this version of Neo4j,False
otherwise.
- property supports_bolt¶
Returns
True
if Bolt is supported by this version of Neo4j,False
otherwise.
- property supports_detach_delete¶
Returns
True
if Cypher DETACH DELETE is supported by this version of Neo4j,False
otherwise.
2.5. Security¶
- class py2neo.database.auth.ServerAddress(*uris, **settings)[source]¶
A DBMS or graph database address.
- py2neo.database.auth.authenticate(host_port, user, password)[source]¶
Set HTTP basic authentication values for specified host_port for use with both Neo4j 2.2 built-in authentication as well as if a database server is behind (for example) an Apache proxy. The code below shows a simple example:
from py2neo import authenticate, Graph # set up authentication parameters authenticate("camelot:7474", "arthur", "excalibur") # connect to authenticated graph database graph = Graph("http://camelot:7474/db/data/")
Note: a host_port can be either a server name or a server name and port number but must match exactly that used within the Graph URI.
- Parameters:
host_port – the host and optional port requiring authentication (e.g. “bigserver”, “camelot:7474”)
user – the user name to authenticate as
password – the password
- py2neo.database.auth.keyring = {}¶
Authentication dictionary mapping server addresses to auth details
- py2neo.database.auth.register_server(*uris, **settings)[source]¶
Register server address details and return a
ServerAddress
instance.- Parameters:
uris –
settings –
- Returns:
2.6. Cypher Utilities¶
- class py2neo.database.selection.NodeSelector(graph)[source]¶
A
NodeSelector
can be used to locate nodes that fulfil a specific set of criteria. Typically, a single node can be identified passing a specific label and property key-value pair. However, any number of labels and any condition supported by the Cypher WHERE clause is allowed.For a simple selection by label and property:
>>> from py2neo import Graph, NodeSelector >>> graph = Graph() >>> selector = NodeSelector(graph) >>> selected = selector.select("Person", name="Keanu Reeves") >>> list(selected) [(f9726ea:Person {born:1964,name:"Keanu Reeves"})]
For a more comprehensive selection using Cypher expressions, the
NodeSelection.where()
method can be used for further refinement. Here, the underscore character can be used to refer to the node being filtered:>>> selected = selector.select("Person").where("_.name =~ 'J.*'", "1960 <= _.born < 1970") >>> list(selected) [(a03f6eb:Person {born:1967,name:"James Marshall"}), (e59993d:Person {born:1966,name:"John Cusack"}), (c44901e:Person {born:1960,name:"John Goodman"}), (b141775:Person {born:1965,name:"John C. Reilly"}), (e40244b:Person {born:1967,name:"Julia Roberts"})]
The underlying query is only evaluated when the selection undergoes iteration or when a specific evaluation method is called (such as
NodeSelection.first()
). This means that aNodeSelection
instance may be reused before and after a data changes for different results.- select(*labels, **properties)[source]¶
Describe a basic node selection using labels and property equality.
- Parameters:
labels – node labels to match
properties – set of property keys and values to match
- Returns:
NodeSelection
instance
- class py2neo.database.selection.NodeSelection(graph, labels=frozenset({}), conditions=(), order_by=(), skip=None, limit=None)[source]¶
An immutable set of node selection criteria.
- first()[source]¶
Evaluate the selection and return the first
Node
selected orNone
if no matching nodes are found.- Returns:
a single matching
Node
orNone
- limit(amount)[source]¶
Limit the selection to at most amount nodes.
- Parameters:
amount – maximum number of nodes to select
- Returns:
refined selection object
- order_by(*fields)[source]¶
Order by the fields or field expressions specified.
To refer to the current node within a field or field expression, use the underscore character
_
. For example:selection.order_by("_.name", "max(_.a, _.b)")
- Parameters:
fields – fields or field expressions to order by
- Returns:
refined selection object
- skip(amount)[source]¶
Skip the first amount nodes in the result.
- Parameters:
amount – number of nodes to skip
- Returns:
refined selection object
- where(*conditions, **properties)[source]¶
Create a new selection based on this selection. The criteria specified for refining the selection consist of conditions and properties. Conditions are individual Cypher expressions that would be found in a WHERE clause; properties are used as exact matches for property values.
To refer to the current node within a condition expression, use the underscore character
_
. For example:selection.where("_.name =~ 'J.*")
Simple property equalities can also be specified:
selection.where(born=1976)
- Parameters:
conditions – Cypher expressions to add to the selection WHERE clause
properties – exact property match keys and values
- Returns:
refined selection object
2.7. Debugging¶
- py2neo.watch(logger, level=None, out=None)[source]¶
Dump log messages to standard output.
To watch Bolt traffic:
>>> from py2neo import watch >>> watch("neo4j.bolt")
To watch HTTP traffic:
>>> from py2neo import watch >>> watch("neo4j.http")
- Parameters:
logger – logger name
level – logging level (default
INFO
)out – output channel (default
stdout
)
2.8. Errors & Warnings¶
- exception py2neo.database.status.ClientError(*args, **kwargs)[source]¶
The Client sent a bad request - changing the request might yield a successful outcome.
- exception py2neo.database.status.DatabaseError(*args, **kwargs)[source]¶
The database failed to service the request.