Pulsar Python client library is a wrapper over the existing C++ client library and exposes all of the same features. 你可以在 C++ 客户端源码的 python 子目录中找到 Pulsar Python 客户端的相关源码 。

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.

安装

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==2.6.1

Installation via PyPi is available for the following Python versions:

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 手册：

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

示例

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

生产者示例

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()

消费者示例

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.

consumer = client.subscribe('my-topic', 'my-subscription')
while True:
    msg = consumer.receive()
    try:
        print("Received message '{}' id='{}'".format(msg.data(), msg.message_id()))
        # 确认已经成功处理消息
        consumer.acknowledge(msg)
    except:
        # 消息处理失败
        consumer.negative_acknowledge(msg)
client.close()

读者接口示例

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

# MessageId 取自先前获取的消息
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()))
    # 无确认操作

多主题订阅

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. 如果通过 regex 选择主题, 则所有主题都必须位于同一Pulsar命名空间中。

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. 例如:

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 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.

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

字段参数

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

Schema 定义示例

简单定义

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

使用枚举

from enum import Enum
class Color(Enum):
    red = 1
    green = 2
    blue = 3
class Example(Record):
    name = String()
    color = Color

复杂类型

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