The Pulsar Python client
The 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.
Installation​
You can install the pulsar-client
library either via PyPi, using pip, or by building the library from source.
Installation using pip​
To install the pulsar-client
library as a pre-built package using the pip package manager:
pip install pulsar-client==2.3.2
Installation via PyPi is available for the following Python versions:
Platform | Supported Python versions |
---|---|
MacOS 10.11 (El Capitan) — 10.12 (Sierra) — 10.13 (High Sierra) — 10.14 (Mojave) | 2.7, 3.7 |
Linux | 2.7, 3.4, 3.5, 3.6, 3.7 |
Installing from source​
To install the pulsar-client
library by building from source, follow these instructions and compile the Pulsar C++ client library. That will also build 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​
Below you'll find a variety of Python code examples for the pulsar-client
library.
Producer example​
This creates a Python producer for the my-topic
topic and send 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​
This creates a consumer with the my-subscription
subscription on the my-topic
topic, listen for incoming messages, print the content and ID of messages that arrive, and acknowledge 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
Schema​
Declaring and validating schema​
A schema can be declared 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 we can then create producers, consumers and readers instances that will be referring to that.
producer = client.create_producer(
topic='my-topic',
schema=AvroSchema(Example) )
producer.send(Example(a='Hello', b=1))
When the producer is created, the Pulsar broker will validate 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, the producer creation will raise an exception.
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​
There are different builtin schema types that can be used 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 can have a number of fields which can be of either
pulsar.schema.Field
type or even another nested Record
. All the
fields are also 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 these parameters can be used 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". This will set it 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()