Work with schema

Get started with schema

For an overview of Pulsar schema and language-specific code examples, see Schema - Overview and Schema - Get Started.

Work with Python schema

Working with Python schema has slight differences from using other languages. This section introduces the specific reference and examples for using Python clients to work with schema.

Supported schema types

You can use different built-in schema types in Pulsar. All the definitions are in the pulsar.schema package.

Schema	Notes
BytesSchema	Get the raw payload as a bytes object. No serialization/deserialization are performed. This is the default schema mode
StringSchema	Encode/decode payload as a UTF-8 string. Uses str objects
JsonSchema	Require record definition. Serializes the record into standard JSON payload
AvroSchema	Require record definition. Serializes in AVRO format

Schema definition reference

The schema definition is done through a class that inherits from pulsar.schema.Record.

This class has a number of fields that can be of either pulsar.schema.Field type or another nested Record. All the fields are specified in the pulsar.schema package. The fields are matching the AVRO field types.

Field Type	Python Type	Notes
Boolean	bool
Integer	int
Long	int
Float	float
Double	float
Bytes	bytes
String	str
Array	list	Need to specify record type for items.
Map	dict	Key is always String. Need to specify value type.

Additionally, any Python Enum type can be used as a valid field type.

Fields parameters

When adding a field, you can use these parameters in the constructor.

Argument	Default	Notes
default	None	Set a default value for the field, such as a = Integer(default=5).
required	False	Mark the field as "required". It is set in the schema accordingly.

Schema definition examples

Simple definition

class Example(Record):
    a = String()
    b = Integer()
    c = Array(String())
    i = Map(String())

Using enums

from enum import Enum

class Color(Enum):
    red = 1
    green = 2
    blue = 3

class Example(Record):
    name = String()
    color = Color

Complex types

class MySubRecord(Record):
    x = Integer()
    y = Long()
    z = String()

class Example(Record):
    a = String()
    sub = MySubRecord()

Set namespace for Avro schema

Set the namespace for the Avro Record schema using the special field _avro_namespace.

class NamespaceDemo(Record):
   _avro_namespace = 'xxx.xxx.xxx'
   x = String()
   y = Integer()

The schema definition is like this.

{
  "name": "NamespaceDemo", "namespace": "xxx.xxx.xxx", "type": "record", "fields": [
    {"name": "x", "type": ["null", "string"]},
    {"name": "y", "type": ["null", "int"]}
  ]
}

Declare and validate schema

Before the producer is created, the Pulsar broker validates that the existing topic schema is the correct type and that the format is compatible with the schema definition of a class. If the format of the topic schema is incompatible with the schema definition, an exception occurs in the producer creation.

Once a producer is created with a certain schema definition, it only accepts objects that are instances of the declared schema class.

Similarly, for a consumer or reader, the consumer returns an object (which is an instance of the schema record class) rather than raw bytes.

Example

consumer = client.subscribe(
                  topic='my-topic',
                  subscription_name='my-subscription',
                  schema=AvroSchema(Example) )

while True:
    msg = consumer.receive()
    ex = msg.value()
    try:
        print("Received message a={} b={} c={}".format(ex.a, ex.b, ex.c))
        # Acknowledge successful processing of the message
        consumer.acknowledge(msg)
    except Exception:
        # Message failed to be processed
        consumer.negative_acknowledge(msg)