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==2.6.2
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()