Confluent Cloud Clients Python Library

The Confluent Cloud Clients Python Library provides a set of clients for interacting with Confluent Cloud REST APIs. The library includes clients for:

• Flink
• Kafka
• Schema Registry
• Tableflow
• Metrics

Note: This library is in active development and is subject to change. It covers only the methods I have needed so far. If you need a method that is not covered, please feel free to open an issue or submit a pull request.

Table of Contents

• 1.0 Library Clients
  • 1.1 Flink Client
  • 1.2 Kafka Client
  • 1.3 Schema Registry Client
  • 1.4 Tableflow Client
  • 1.5 Metrics Client
• 2.0 Unit Tests
  • 2.1 Flink Client
  • 2.2 Kafka Client
  • 2.3 Schema Registry Client
  • 2.4 Tableflow Client
  • 2.5 Metrics Client
• 3.0 Installation

• 4.0 Resources
  • 4.1 Architecture Design Records (ADRs)
  • 4.2 API Documentation
  • 4.3 Flink Resources
  • 4.4 Tableflow Resources
  • 4.5 Metrics Resources
  • 4.6 Other Resources

1.0 Library Clients

1.1 Flink Client

The Flink Client provides the following methods:

• delete_statement
• delete_statements_by_phase
• drop_table

  Note: "The drop_table method will drop the table and all associated statements, including the backing Kafka Topic and Schemas."

• get_compute_pool
• get_compute_pool_list
• get_statement_list
• stop_statement

  Note: "Confluent Cloud for Apache Flink enforces a 30-day retention for statements in terminal states."

• submit_statement
• update_statement
• update_all_sink_statements

1.2 Kafka Client

The Kafka Client provides the following methods:

• delete_kafka_topic
• kafka_topic_exist
• kafka_get_topic

1.3 Schema Registry Client

The Schema Registry Client provides the following methods:

• convert_avro_schema_into_string
• delete_kafka_topic_key_schema_subject
• delete_kafka_topic_value_schema_subject
• get_global_topic_subject_compatibility_level
• get_topic_subject_compatibility_level
• get_topic_subject_latest_schema
• register_topic_subject_schema
• set_topic_subject_compatibility_level

1.4 Tableflow Client

The Tableflow Client provides the following methods:

• get_tableflow_topic
• get_tableflow_topic_table_path

1.5 Metrics Client

The Metrics Client provides the following methods:

• get_topic_total

  Note: "The get_topic_total method can be used to get the total bytes or total records for a Kafka Topic. It requires an additional parameter to specify the metric type."

  • Metric Types:
    • RECEIVED_BYTES
    • RECEIVED_RECORDS
• get_topic_daily_aggregated_totals

  Note: "The get_topic_daily_aggregated_totals method can be used to get the daily aggregated totals for a Kafka Topic within a rolling window of the last 7 days. It requires an additional parameter to specify the metric type."

  • Metric Types:
    • RECEIVED_BYTES
    • RECEIVED_RECORDS

2.0 Unit Tests

The library includes unit tests for each client. The tests are located in the tests directory. To use them, you must clone the repo locally:

git clone https://github.com/j3-signalroom/cc-clients-python_lib.git

Since this project was built using uv, please install it, and then run the following command to install all the project dependencies:

 uv sync

Then within the tests directory, create the .env file and add the following environment variables, filling them with your Confluent Cloud credentials and other required values:

BOOTSTRAP_SERVER_CLOUD_PROVIDER=
BOOTSTRAP_SERVER_CLOUD_REGION=
BOOTSTRAP_SERVER_ID=
CLOUD_PROVIDER=
CLOUD_REGION=
COMPUTE_POOL_ID=
CONFLUENT_CLOUD_API_KEY=
CONFLUENT_CLOUD_API_SECRET=
ENVIRONMENT_ID=
FLINK_API_KEY=
FLINK_API_SECRET=
FLINK_CATALOG_NAME=
FLINK_DATABASE_NAME=
FLINK_STATEMENT_NAME=
FLINK_TABLE_NAME=
FLINK_URL=
KAFKA_API_KEY=
KAFKA_API_SECRET=
KAFKA_CLUSTER_ID=
KAFKA_TOPIC_NAME=
ORGANIZATION_ID=
PRINCIPAL_ID=
QUERY_START_TIME=
QUERY_END_TIME=
SCHEMA_REGISTRY_API_KEY=
SCHEMA_REGISTRY_API_SECRET=
SCHEMA_REGISTRY_URL=
TABLEFLOW_API_KEY=
TABLEFLOW_API_SECRET=

Note: The QUERY_START_TIME and QUERY_END_TIME environment variables should be in the format YYYY-MM-DDTHH:MM:SS, for example, 2025-09-01T00:00:00.

2.1 Flink Client

To run a specific test, use one of the following commands:

Unit Test	Command
Delete a Flink Statement	uv run pytest -s tests/test_flink_client.py::test_delete_statement
Delete all Flink Statements by Phase	uv run pytest -s tests/test_flink_client.py::test_delete_statements_by_phase
Get list of the all the Statements	uv run pytest -s tests/test_flink_client.py::test_get_statement_list
Submit a Flink Statement	uv run pytest -s tests/test_flink_client.py::test_submit_statement
Get Compute Pool List	uv run pytest -s tests/test_flink_client.py::test_get_compute_pool_list
Get Compute Pool	uv run pytest -s tests/test_flink_client.py::test_get_compute_pool
Stop a Flink Statement	uv run pytest -s tests/test_flink_client.py::test_stop_statement
Update a Flink Statement	uv run pytest -s tests/test_flink_client.py::test_update_statement
Update all the Sink Statements	uv run pytest -s tests/test_flink_client.py::test_update_all_sink_statements
Drop a Flink Table along with any associated statements, including the backing Kafka Topic and Schemas	uv run pytest -s tests/test_flink_client.py::test_drop_table

Otherwise, to run all the tests, use the following command:

uv run pytest -s tests/test_flink_client.py

Note: The tests are designed to be run in a specific order. If you run them out of order, you may encounter errors. The tests are also designed to be run against a Confluent Cloud environment. If you run them against a local environment, you may encounter errors.

2.2 Kafka Client

To run a specific test, use one of the following commands:

Unit Test	Command
Delete a Kafka Topic	uv run pytest -s tests/test_kafka_client.py::test_delete_kafka_topic
Checks if a Kafka Topic Exist	uv run pytest -s tests/test_kafka_client.py::test_kafka_topic_exist
Get Kafka Topic Details	uv run pytest -s tests/test_kafka_client.py::test_kafka_get_topic

Otherwise, to run all the tests, use the following command:

uv run pytest -s tests/test_kafka_client.py

Note: The tests are designed to be run in a specific order. If you run them out of order, you may encounter errors. The tests are also designed to be run against a Confluent Cloud environment. If you run them against a local environment, you may encounter errors.

2.3 Schema Registry Client

To run a specific test, use one of the following commands:

Unit Test	Command
Get the Subject Compatibility Level	uv run pytest -s tests/test_schema_registry_client.py::test_get_subject_compatibility_level
Delete the Kafka Topic Key Schema Subject	uv run pytest -s tests/test_schema_registry_client.py::test_delete_kafka_topic_key_schema_subject
Delete the Kafka Topic Value Schema Subject	uv run pytest -s tests/test_schema_registry_client.py::test_delete_kafka_topic_value_schema_subject

Otherwise, to run all the tests, use the following command:

uv run pytest -s tests/test_schema_registry_client.py

Note: The tests are designed to be run in a specific order. If you run them out of order, you may encounter errors. The tests are also designed to be run against a Confluent Cloud environment. If you run them against a local environment, you may encounter errors.

2.4 Tableflow Client

To run a specific test, use one of the following commands:

Unit Test	Command
Get the Tableflow Topic	uv run pytest -s tests/test_tableflow_client.py::test_get_tableflow_topic
Get the Tableflow Topic Table Path	uv run pytest -s tests/test_tableflow_client.py::test_get_tableflow_topic_table_path

Otherwise, to run all the tests, use the following command:

uv run pytest -s tests/test_tableflow_client.py

Note: The tests are designed to be run in a specific order. If you run them out of order, you may encounter errors. The tests are also designed to be run against a Confluent Cloud environment. If you run them against a local environment, you may encounter errors.

2.5 Metrics Client

To run a specific test, use one of the following commands:

Unit Test	Command
Get the Topic Total Bytes	uv run pytest -s tests/test_metrics_client.py::test_get_topic_total_bytes
Get the Topic Total Records	uv run pytest -s tests/test_metrics_client.py::test_get_topic_total_records
Get the Topic Daily Aggregated Totals Bytes	uv run pytest -s tests/test_metrics_client.py::test_get_topic_daily_aggregated_totals_bytes
Get the Topic Daily Aggregated Totals Records	uv run pytest -s tests/test_metrics_client.py::test_get_topic_daily_aggregated_totals_records
Compute the Topic Partition Count Based on Received Bytes and Record Count	uv run pytest -s tests/test_metrics_client.py::test_compute_topic_partition_count_based_on_received_bytes_record_count

Otherwise, to run all the tests, use the following command:

uv run pytest -s tests/test_metrics_client.py

Note: The tests are designed to be run in a specific order. If you run them out of order, you may encounter errors. The tests are also designed to be run against a Confluent Cloud environment. If you run them against a local environment, you may encounter errors.

3.0 Installation

Install the Confluent Cloud Clients Python Library using pip:

pip install cc-clients-python-lib

Or, using uv:

uv add cc-clients-python-lib

4.0 Resources

4.1 Architecture Design Records (ADRs)

• 001 Architectural Design Record (ADR): Drop Table Plus

4.2 API Documentation

• Flink SQL REST API for Confluent Cloud for Apache Flink
• Kafka REST APIs for Confluent Cloud
• Confluent Cloud APIs - Topic (v3)
• Confluent Cloud Schema Registry REST API Usage

4.3 Flink Resources

• CCAF State management
• Monitor and Manage Flink SQL Statements in Confluent Cloud for Apache Flink
• DROP TABLE Statement in Confluent Cloud for Apache Flink

4.4 Tableflow Resources

• Tableflow Topics (tableflow/v1)

4.4 Tableflow Resources

• Tableflow Topics (tableflow/v1)

4.5 Metrics Resources

• Confluent Cloud Metrics API Version 2 Reference
• Confluent Cloud Metrics API: Metrics Reference
• Confluent Cloud Metrics

4.6 Other Resources

• How to programmatically pause and resume a Flink statement
• How to programmatically pause and resume a Flink statement REDUX