kafka-connect-py 0.7.1

A client for the Confluent Platform Kafka Connect REST API.

Kafka Connect Python

The Kafka Connect REST API allows you to manage connectors that move data between Apache Kafka and other systems.

The Kafka Connect command line tool, also known as kc or kafka-connect, allows users to manage their Kafka Connect cluster and connectors. With this tool, users can retrieve information about the cluster and connectors, create new connectors, update existing connectors, delete connectors, and perform other actions.

This project aims to supported all features of the Kafka Connect REST API.

Install

pip install kafka-connect-py

Command Line Usage

Get the version and other details of the Kafka Connect cluster.

kc info

Get a list of all connectors

kc list [--expand=status|info] [--connector-pattern=regex]

Get the details of a single connector

kc get <connector>

Get the details of all connectors

kc get --all-connectors [--connector-pattern=regex]

Get the status of all connectors

kc status --all-connectors [--connector-pattern=regex]

Get the config of a connector

kc config <connector>

Get the config of all connectors

kc config --all-connectors [--connector-pattern=regex]

Create a new connector with a JSON file

kc create --config-file <config-file>

Create a new connector with inline JSON data

kc create --config-data <config-data>

Update the configuration for an existing connector with a JSON file

kc update <connector> --config-file <config_file>

Update the configuration for an existing connector with inline JSON data

kc create <connector> --config-data <config-data>

Restart a connector

kc restart <connector> [--include-tasks] [--only-failed]

Restart all connectors

kc restart --all-connectors [--connector-pattern=regex] [--include-tasks] [--only-failed]

Pause a connector

kc pause <connector>

Pause all connectors

kc pause --all-connectors [--connector-pattern=regex]

Resume a connector

kc resume <connector>

Resume all connectors

kc resume --all-connectors [--connector-pattern=regex]

Delete a connector

kc delete <connector>

Delete all connectors

kc delete --all-connectors [--connector-pattern=regex]

Python

# Import the class
from kafka_connect import KafkaConnect

# Instantiate the client
client = KafkaConnect(endpoint="http://localhost:8083")

# Get the version and other details of the Kafka Connect cluster
cluster = client.get_info()
print(cluster)

# Get a list of active connectors
connectors = client.get_connectors()
print(connectors)

# Create a new connector
config = {
    "name": "my-connector",
    "config": {
        "connector.class": "io.confluent.connect.jdbc.JdbcSourceConnector",
        "tasks.max": "1",
        "connection.url": "jdbc:postgresql://localhost:5432/mydatabase",
        "connection.user": "myuser",
        "connection.password": "mypassword",
        "table.whitelist": "mytable",
        "mode": "timestamp+incrementing",
        "timestamp.column.name": "modified_at",
        "validate.non.null": "false",
        "incrementing.column.name": "id",
        "topic.prefix": "my-connector-",
    },
}
response = client.create_connector(config)
print(response)

# Update an existing connector
new_config = {
    "config": {
        "connector.class": "io.confluent.connect.jdbc.JdbcSourceConnector",
        "tasks.max": "1",
        "connection.url": "jdbc:postgresql://localhost:5432/mydatabase",
        "connection.user": "myuser",
        "connection.password": "mypassword",
        "table.whitelist": "mytable",
        "mode": "timestamp+incrementing",
        "timestamp.column.name": "modified_at",
        "validate.non.null": "false",
        "incrementing.column.name": "id",
        "topic.prefix": "my-connector-",
    },
}
response = client.update_connector("my-connector", new_config)
print(response)

# Restart a connector
response = client.restart_connector("my-connector")
print(response)

# Delete a connector
response = client.delete_connector("my-connector")
print(response)

Tests

python3 -m unittest tests/test_kafka_connect.py -v