azure-eventhub-py

Checkpointed consumption in Python uses an EventHubConsumerClient paired with a BlobCheckpointStore to persist consumer progress. You can apply per-event, batch, time-based, or hybrid checkpointing strategies to ensure fault-tolerant processing of event streams.

High-throughput event streaming to Azure Event Hubs is best handled by the async EventHubProducerClient. It supports batch sends, partitioned routing via partition keys, and context manager lifecycle management for optimal resource handling during production or testing scenarios.

Azure Event Hubs Python client supports partition routing through explicit partition sends and partition keys. Consumer load balancing is handled by EventHubConsumerClient ownership events, allowing distributed processing across partitions efficiently.

DefaultAzureCredential provides authentication for Azure Event Hubs Python producers and consumers without hardcoding secrets. It integrates directly with both sync and async client flavors, streamlining secure access to event streams and BlobCheckpointStore resources.

You can inspect Azure Event Hub properties, partition details, and send test events using a dedicated Python CLI script. This operational utility also supports receiving events with optional checkpointing to validate your streaming pipeline configuration.

A BlobCheckpointStore is needed for fault-tolerant event processing to reliably persist consumer progress across restarts. It stores checkpoint update semantics externally in Azure Blob Storage, preventing data loss or reprocessing when async consumers fail or scale.