Pulsar Python client

Pulsar Python client library is a wrapper over the existing C++ client library and exposes all of the same features. You can find the code in the python GitHub Repository of the C++ client code.

All the methods in producer, consumer, and reader of a Python client are thread-safe.

pdoc-generated API docs for the Python client are available here.

Install

You can install the pulsar-client library either via PyPi, using pip, or by building the library from source.

Install using pip

To install the pulsar-client library as a pre-built package using the pip package manager:

pip install pulsar-client==2.6.3

Installation via PyPi is available for the following Python versions:

Platform	Supported Python versions
MacOS 10.13 (High Sierra), 10.14 (Mojave)	2.7, 3.7
Linux	2.7, 3.4, 3.5, 3.6, 3.7

Install from source

To install the pulsar-client library by building from source, follow instructions and compile the Pulsar C++ client library. That builds the Python binding for the library.

To install the built Python bindings:

$ git clone https://github.com/apache/pulsar
$ cd pulsar/pulsar-client-cpp/python
$ sudo python setup.py install

API Reference

The complete Python API reference is available at api/python.

Examples

You can find a variety of Python code examples for the pulsar-client library.

Producer example

The following example creates a Python producer for the my-topic topic and sends 10 messages on that topic:

import pulsar

client = pulsar.Client('pulsar://localhost:6650')

producer = client.create_producer('my-topic')

for i in range(10):
    producer.send(('Hello-%d' % i).encode('utf-8'))

client.close()

Consumer example

The following example creates a consumer with the my-subscription subscription name on the my-topic topic, receives incoming messages, prints the content and ID of messages that arrive, and acknowledges each message to the Pulsar broker.

import pulsar

client = pulsar.Client('pulsar://localhost:6650')

consumer = client.subscribe('my-topic', 'my-subscription')

while True:
    msg = consumer.receive()
    try:
        print("Received message '{}' id='{}'".format(msg.data(), msg.message_id()))
        # Acknowledge successful processing of the message
        consumer.acknowledge(msg)
    except:
        # Message failed to be processed
        consumer.negative_acknowledge(msg)

client.close()

Reader interface example

You can use the Pulsar Python API to use the Pulsar reader interface. Here's an example:

# MessageId taken from a previously fetched message
msg_id = msg.message_id()

reader = client.create_reader('my-topic', msg_id)

while True:
    msg = reader.read_next()
    print("Received message '{}' id='{}'".format(msg.data(), msg.message_id()))
    # No acknowledgment

Multi-topic subscriptions

In addition to subscribing a consumer to a single Pulsar topic, you can also subscribe to multiple topics simultaneously. To use multi-topic subscriptions, you can supply a regular expression (regex) or a List of topics. If you select topics via regex, all topics must be within the same Pulsar namespace.

The following is an example.

import re
consumer = client.subscribe(re.compile('persistent://public/default/topic-*'), 'my-subscription')
while True:
    msg = consumer.receive()
    try:
        print("Received message '{}' id='{}'".format(msg.data(), msg.message_id()))
        # Acknowledge successful processing of the message
        consumer.acknowledge(msg)
    except:
        # Message failed to be processed
        consumer.negative_acknowledge(msg)
client.close()

Schema

Declare and validate schema

You can declare a schema by passing a class that inherits from pulsar.schema.Record and defines the fields as class variables. For example:

from pulsar.schema import *

class Example(Record):
    a = String()
    b = Integer()
    c = Boolean()

With this simple schema definition, you can create producers, consumers and readers instances that refer to that.

producer = client.create_producer(
                    topic='my-topic',
                    schema=AvroSchema(Example) )

producer.send(Example(a='Hello', b=1))

After creating the producer, the Pulsar broker validates that the existing topic schema is indeed of "Avro" type and that the format is compatible with the schema definition of the Example class.

If there is a mismatch, an exception occurs in the producer creation.

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

Similarly, for a consumer/reader, the consumer will return an object, instance of the schema record class, rather than the raw bytes:

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:
        # Message failed to be processed
        consumer.negative_acknowledge(msg)

Supported schema types

You can use different builtin 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 which 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 fields 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. Eg: 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()