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ScyllaDB Python Driver is available under the Apache v2 License. ScyllaDB Python Driver is a fork of DataStax Python Driver. See Copyright here.
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You're viewing documentation for a deprecated version of Scylla Python Driver. Switch to the latest stable version.
Cassandra 2.1 introduced user-defined types (UDTs). You can create a
new type through CREATE TYPE
statements in CQL:
CREATE TYPE address (street text, zip int);
Version 2.1 of the Python driver adds support for user-defined types.
You can tell the Python driver to return columns of a specific UDT as
instances of a class or a dict by registering them with your Cluster
instance through Cluster.register_user_type()
:
cluster = Cluster(protocol_version=3)
session = cluster.connect()
session.set_keyspace('mykeyspace')
session.execute("CREATE TYPE address (street text, zipcode int)")
session.execute("CREATE TABLE users (id int PRIMARY KEY, location frozen<address>)")
# create a class to map to the "address" UDT
class Address(object):
def __init__(self, street, zipcode):
self.street = street
self.zipcode = zipcode
cluster.register_user_type('mykeyspace', 'address', Address)
# insert a row using an instance of Address
session.execute("INSERT INTO users (id, location) VALUES (%s, %s)",
(0, Address("123 Main St.", 78723)))
# results will include Address instances
results = session.execute("SELECT * FROM users")
row = results[0]
print(row.id, row.location.street, row.location.zipcode)
cluster = Cluster(protocol_version=3)
session = cluster.connect()
session.set_keyspace('mykeyspace')
session.execute("CREATE TYPE address (street text, zipcode int)")
session.execute("CREATE TABLE users (id int PRIMARY KEY, location frozen<address>)")
cluster.register_user_type('mykeyspace', 'address', dict)
# insert a row using a prepared statement and a tuple
insert_statement = session.prepare("INSERT INTO mykeyspace.users (id, location) VALUES (?, ?)")
session.execute(insert_statement, [0, ("123 Main St.", 78723)])
# results will include dict instances
results = session.execute("SELECT * FROM users")
row = results[0]
print(row.id, row.location['street'], row.location['zipcode'])
Although it is recommended to register your types with
Cluster.register_user_type()
, the driver gives you some options
for working with unregistered UDTS.
When you use prepared statements, the driver knows what data types to expect for each placeholder. This allows you to pass any object you want for a UDT, as long as it has attributes that match the field names for the UDT:
cluster = Cluster(protocol_version=3)
session = cluster.connect()
session.set_keyspace('mykeyspace')
session.execute("CREATE TYPE address (street text, zipcode int)")
session.execute("CREATE TABLE users (id int PRIMARY KEY, location frozen<address>)")
class Foo(object):
def __init__(self, street, zipcode, otherstuff):
self.street = street
self.zipcode = zipcode
self.otherstuff = otherstuff
insert_statement = session.prepare("INSERT INTO users (id, location) VALUES (?, ?)")
# since we're using a prepared statement, we don't *have* to register
# a class to map to the UDT to insert data. The object just needs to have
# "street" and "zipcode" attributes (which Foo does):
session.execute(insert_statement, [0, Foo("123 Main St.", 78723, "some other stuff")])
# when we query data, UDT columns that don't have a class registered
# will be returned as namedtuples:
results = session.execute("SELECT * FROM users")
first_row = results[0]
address = first_row.location
print(address) # prints "Address(street='123 Main St.', zipcode=78723)"
street = address.street
zipcode = address.street
As shown in the code example, inserting data for UDT columns without registering
a class works fine for prepared statements. However, you must register a
class to insert UDT columns with unprepared statements.* You can still query
UDT columns without registered classes using unprepared statements, they will
simply return namedtuple
instances (just like prepared statements do).
* this applies to parameterized unprepared statements, in which the driver will be formatting parameters – not statements with interpolated UDT literals.
Was this page helpful?
ScyllaDB Python Driver is available under the Apache v2 License. ScyllaDB Python Driver is a fork of DataStax Python Driver. See Copyright here.
cassandra
- Exceptions and Enumscassandra.cluster
- Clusters and Sessionscassandra.policies
- Load balancing and Failure Handling Policiescassandra.auth
- Authenticationcassandra.graph
- Graph Statements, Options, and Row Factoriescassandra.metadata
- Schema and Ring Topologycassandra.metrics
- Performance Metricscassandra.query
- Prepared Statements, Batch Statements, Tracing, and Row Factoriescassandra.pool
- Hosts and Connection Poolscassandra.protocol
- Protocol Featurescassandra.encoder
- Encoders for non-prepared Statementscassandra.decoder
- Data Return Formatscassandra.concurrent
- Utilities for Concurrent Statement Executioncassandra.connection
- Low Level Connection Infocassandra.util
- Utilitiescassandra.timestamps
- Timestamp Generationcassandra.io.asyncioreactor
- asyncio
Event Loopcassandra.io.asyncorereactor
- asyncore
Event Loopcassandra.io.eventletreactor
- eventlet
-compatible Connectioncassandra.io.libevreactor
- libev
Event Loopcassandra.io.geventreactor
- gevent
-compatible Event Loopcassandra.io.twistedreactor
- Twisted Event Loopcassandra.cqlengine.models
- Table models for object mappingcassandra.cqlengine.columns
- Column types for object mapping modelscassandra.cqlengine.query
- Query and filter model objectscassandra.cqlengine.connection
- Connection management for cqlenginecassandra.cqlengine.management
- Schema management for cqlenginecassandra.cqlengine.usertype
- Model classes for User Defined Typescassandra.datastax.graph
- Graph Statements, Options, and Row Factoriescassandra.datastax.graph.fluent
cassandra.datastax.graph.fluent.query
cassandra.datastax.graph.fluent.predicates