python confluent_kafka producer

As an AI language model, I don't have the capability to execute Python code. However, I can provide you with an example code snippet for creating a producer using the Confluent Kafka Python library:

from confluent_kafka import Producer

def delivery_report(err, msg):
    """
    Called once for each message produced to indicate delivery result.
    Triggered by poll() or flush().
    """
    if err is not None:
        print('Message delivery failed: {}'.format(err))
    else:
        print('Message delivered to {} [{}]'.format(msg.topic(), msg.partition()))

# Set up configuration properties
conf = {
    'bootstrap.servers': '<your-bootstrap-server>',
    'client.id': 'python-producer'
}

# Create a Kafka producer instance
producer = Producer(conf)

# Produce a message to a topic
topic = '<your-topic>'
message = 'Hello, Kafka!'
producer.produce(topic, message.encode('utf-8'), callback=delivery_report)

# Wait for any outstanding messages to be delivered and delivery reports to be received
producer.flush()

In this example, a producer is created using the `Producer()` class of the Confluent Kafka Python library. The `delivery_report()` function is defined to handle delivery reports for produced messages. The producer instance is used to produce a message to a topic using the `produce()` method. The `flush()` method is called to wait for any outstanding messages to be delivered and delivery reports to be received.

Note: Make sure to replace `<your-bootstrap-server>` and `<your-topic>` with your actual bootstrap server and topic names, respectively.