azure.eventhub package¶

class azure.eventhub.EventHubConsumerClient(fully_qualified_namespace: str, eventhub_name: str, consumer_group: str, credential: Union[AzureSasCredential, TokenCredential, AzureNamedKeyCredential], **kwargs: Any)[source]¶
The EventHubConsumerClient class defines a high level interface for receiving events from the Azure Event Hubs service.

The main goal of EventHubConsumerClient is to receive events from all partitions of an EventHub with load-balancing and checkpointing.

When multiple EventHubConsumerClient instances are running against the same event hub, consumer group and checkpointing location, the partitions will be evenly distributed among them.

To enable load-balancing and persisted checkpoints, checkpoint_store must be set when creating the EventHubConsumerClient. If a checkpoint store is not provided, the checkpoint will be maintained internally in memory.

An EventHubConsumerClient can also receive from a specific partition when you call its method receive() or receive_batch() and specify the partition_id. Load-balancing won’t work in single-partition mode. But users can still save checkpoints if the checkpoint_store is set.

Parameters

fully_qualified_namespace (str) – The fully qualified host name for the Event Hubs namespace. The namespace format is: <yournamespace>.servicebus.windows.net.

eventhub_name (str) – The path of the specific Event Hub to connect the client to.

consumer_group (str) – Receive events from the event hub for this consumer group.

credential (TokenCredential or AzureSasCredential or AzureNamedKeyCredential) – The credential object used for authentication which implements a particular interface for getting tokens. It accepts EventHubSharedKeyCredential, or credential objects generated by the azure-identity library and objects that implement the get_token(self, *scopes) method.

Keyword Arguments

logging_enable (bool) – Whether to output network trace logs to the logger. Default is False.

auth_timeout (float) – The time in seconds to wait for a token to be authorized by the service. The default value is 60 seconds. If set to 0, no timeout will be enforced from the client.

user_agent (str) – If specified, this will be added in front of the user agent string.

retry_total (int) – The total number of attempts to redo a failed operation when an error occurs. Default value is 3. The context of retry_total in receiving is special: The receive method is implemented by a while-loop calling internal receive method in each iteration. In the receive case, retry_total specifies the numbers of retry after error raised by internal receive method in the while-loop. If retry attempts are exhausted, the on_error callback will be called (if provided) with the error information. The failed internal partition consumer will be closed (on_partition_close will be called if provided) and new internal partition consumer will be created (on_partition_initialize will be called if provided) to resume receiving.

retry_backoff_factor (float) – A backoff factor to apply between attempts after the second try (most errors are resolved immediately by a second try without a delay). In fixed mode, retry policy will always sleep for {backoff factor}. In ‘exponential’ mode, retry policy will sleep for: {backoff factor} * (2 ** ({number of total retries} - 1)) seconds. If the backoff_factor is 0.1, then the retry will sleep for [0.0s, 0.2s, 0.4s, …] between retries. The default value is 0.8.

retry_backoff_max (float) – The maximum back off time. Default value is 120 seconds (2 minutes).

retry_mode (str) – The delay behavior between retry attempts. Supported values are ‘fixed’ or ‘exponential’, where default is ‘exponential’.

idle_timeout (float) – Timeout, in seconds, after which this client will close the underlying connection if there is no further activity. By default the value is None, meaning that the client will not shutdown due to inactivity unless initiated by the service.

checkpoint_store (CheckpointStore) – A manager that stores the partition load-balancing and checkpoint data when receiving events. The checkpoint store will be used in both cases of receiving from all partitions or a single partition. In the latter case load-balancing does not apply. If a checkpoint store is not provided, the checkpoint will be maintained internally in memory, and the EventHubConsumerClient instance will receive events without load-balancing.

load_balancing_interval (float) – When load-balancing kicks in. This is the interval, in seconds, between two load-balancing evaluations. Default is 10 seconds.

partition_ownership_expiration_interval (float) – A partition ownership will expire after this number of seconds. Every load-balancing evaluation will automatically extend the ownership expiration time. Default is 6 * load_balancing_interval, i.e. 60 seconds when using the default load_balancing_interval of 10 seconds.

load_balancing_strategy (str or LoadBalancingStrategy) – When load-balancing kicks in, it will use this strategy to claim and balance the partition ownership. Use “greedy” or LoadBalancingStrategy.GREEDY for the greedy strategy, which, for every load-balancing evaluation, will grab as many unclaimed partitions required to balance the load. Use “balanced” or LoadBalancingStrategy.BALANCED for the balanced strategy, which, for every load-balancing evaluation, claims only one partition that is not claimed by other EventHubConsumerClient. If all partitions of an EventHub are claimed by other EventHubConsumerClient and this client has claimed too few partitions, this client will steal one partition from other clients for every load-balancing evaluation regardless of the load balancing strategy. Greedy strategy is used by default.
Example:
Create a new instance of the EventHubConsumerClient.¶
import os
from azure.eventhub import EventHubConsumerClient, EventHubSharedKeyCredential

fully_qualified_namespace = os.environ['EVENT_HUB_HOSTNAME']
eventhub_name = os.environ['EVENT_HUB_NAME']
shared_access_policy = os.environ['EVENT_HUB_SAS_POLICY']
shared_access_key = os.environ['EVENT_HUB_SAS_KEY']

credential = EventHubSharedKeyCredential(shared_access_policy, shared_access_key)
consumer = EventHubConsumerClient(
    fully_qualified_namespace=fully_qualified_namespace,
    eventhub_name=eventhub_name,
    consumer_group='$Default',
    credential=credential)
close() → None [source]¶
Stop retrieving events from the Event Hub and close the underlying AMQP connection and links.

Return type

None
Example:
Close down the client.¶
import os
import threading

event_hub_connection_str = os.environ['EVENT_HUB_CONN_STR']
eventhub_name = os.environ['EVENT_HUB_NAME']

from azure.eventhub import EventHubConsumerClient
consumer = EventHubConsumerClient.from_connection_string(
    conn_str=event_hub_connection_str,
    consumer_group="$Default",
    eventhub_name=eventhub_name  # EventHub name should be specified if it doesn't show up in connection string.
)

logger = logging.getLogger("azure.eventhub")

def on_event(partition_context, event):
    # Put your code here.
    # If the operation is i/o intensive, multi-thread will have better performance.
    logger.info("Received event from partition: {}".format(partition_context.partition_id))

# The 'receive' method is a blocking call, it can be executed in a thread for
# non-blocking behavior, and combined with the 'close' method.

worker = threading.Thread(
    target=consumer.receive,
    kwargs={
        "on_event": on_event,
        "starting_position": "-1",  # "-1" is from the beginning of the partition.
    }
)
worker.start()
time.sleep(10)  # Keep receiving for 10s then close.
# Close down the consumer handler explicitly.
consumer.close()
classmethod from_connection_string(conn_str: str, consumer_group: str, **kwargs: Any) → EventHubConsumerClient [source]¶
Create an EventHubConsumerClient from a connection string.

Parameters

conn_str (str) – The connection string of an Event Hub.

consumer_group (str) – Receive events from the Event Hub for this consumer group.

Keyword Arguments

eventhub_name (str) – The path of the specific Event Hub to connect the client to.

logging_enable (bool) – Whether to output network trace logs to the logger. Default is False.

auth_timeout (float) – The time in seconds to wait for a token to be authorized by the service. The default value is 60 seconds. If set to 0, no timeout will be enforced from the client.

user_agent (str) – If specified, this will be added in front of the user agent string.

retry_total (int) – The total number of attempts to redo a failed operation when an error occurs. Default value is 3. The context of retry_total in receiving is special: The receive method is implemented by a while-loop calling internal receive method in each iteration. In the receive case, retry_total specifies the numbers of retry after error raised by internal receive method in the while-loop. If retry attempts are exhausted, the on_error callback will be called (if provided) with the error information. The failed internal partition consumer will be closed (on_partition_close will be called if provided) and new internal partition consumer will be created (on_partition_initialize will be called if provided) to resume receiving.

retry_backoff_factor (float) – A backoff factor to apply between attempts after the second try (most errors are resolved immediately by a second try without a delay). In fixed mode, retry policy will always sleep for {backoff factor}. In ‘exponential’ mode, retry policy will sleep for: {backoff factor} * (2 ** ({number of total retries} - 1)) seconds. If the backoff_factor is 0.1, then the retry will sleep for [0.0s, 0.2s, 0.4s, …] between retries. The default value is 0.8.

retry_backoff_max (float) – The maximum back off time. Default value is 120 seconds (2 minutes).

retry_mode (str) – The delay behavior between retry attempts. Supported values are ‘fixed’ or ‘exponential’, where default is ‘exponential’.

idle_timeout (float) – Timeout, in seconds, after which this client will close the underlying connection if there is no furthur activity. By default the value is None, meaning that the client will not shutdown due to inactivity unless initiated by the service.

checkpoint_store (CheckpointStore) – A manager that stores the partition load-balancing and checkpoint data when receiving events. The checkpoint store will be used in both cases of receiving from all partitions or a single partition. In the latter case load-balancing does not apply. If a checkpoint store is not provided, the checkpoint will be maintained internally in memory, and the EventHubConsumerClient instance will receive events without load-balancing.

load_balancing_interval (float) – When load-balancing kicks in. This is the interval, in seconds, between two load-balancing evaluations. Default is 10 seconds.

partition_ownership_expiration_interval (float) – A partition ownership will expire after this number of seconds. Every load-balancing evaluation will automatically extend the ownership expiration time. Default is 6 * load_balancing_interval, i.e. 60 seconds when using the default load_balancing_interval of 10 seconds.

load_balancing_strategy (str or LoadBalancingStrategy) – When load-balancing kicks in, it will use this strategy to claim and balance the partition ownership. Use “greedy” or LoadBalancingStrategy.GREEDY for the greedy strategy, which, for every load-balancing evaluation, will grab as many unclaimed partitions required to balance the load. Use “balanced” or LoadBalancingStrategy.BALANCED for the balanced strategy, which, for every load-balancing evaluation, claims only one partition that is not claimed by other EventHubConsumerClient. If all partitions of an EventHub are claimed by other EventHubConsumerClient and this client has claimed too few partitions, this client will steal one partition from other clients for every load-balancing evaluation regardless of the load balancing strategy. Greedy strategy is used by default.

Return type

EventHubConsumerClient
Example:
Create a new instance of the EventHubConsumerClient from connection string.¶
import os
from azure.eventhub import EventHubConsumerClient
event_hub_connection_str = os.environ['EVENT_HUB_CONN_STR']
eventhub_name = os.environ['EVENT_HUB_NAME']
consumer = EventHubConsumerClient.from_connection_string(
    conn_str=event_hub_connection_str,
    consumer_group='$Default',
    eventhub_name=eventhub_name  # EventHub name should be specified if it doesn't show up in connection string.
)
get_eventhub_properties() → Dict[str, Any][source]¶

Get properties of the Event Hub.

Keys in the returned dictionary include:

eventhub_name (str)

created_at (UTC datetime.datetime)

partition_ids (list[str])

Return type

dict

Raises

EventHubError

get_partition_ids() → List[str][source]¶

Get partition IDs of the Event Hub.

Return type

list[str]

Raises

EventHubError

get_partition_properties(partition_id: str) → Dict[str, Any][source]¶

Get properties of the specified partition.

Keys in the properties dictionary include:

eventhub_name (str)

id (str)

beginning_sequence_number (int)

last_enqueued_sequence_number (int)

last_enqueued_offset (str)

last_enqueued_time_utc (UTC datetime.datetime)

is_empty (bool)

Parameters

partition_id (str) – The target partition ID.

Return type

dict

Raises

EventHubError
receive(on_event: Callable[[PartitionContext, Optional[EventData]], None], **kwargs: Any) → None [source]¶
Receive events from partition(s), with optional load-balancing and checkpointing.

Parameters

on_event (Callable[PartitionContext, Optional[EventData]]) – The callback function for handling a received event. The callback takes two parameters: partition_context which contains partition context and event which is the received event. The callback function should be defined like: on_event(partition_context, event). For detailed partition context information, please refer to PartitionContext.

Keyword Arguments

max_wait_time (float) – The maximum interval in seconds that the event processor will wait before calling the callback. If no events are received within this interval, the on_event callback will be called with None. If this value is set to None or 0 (the default), the callback will not be called until an event is received.

partition_id (str) – If specified, the client will receive from this partition only. Otherwise the client will receive from all partitions.

owner_level (int) – The priority for an exclusive consumer. An exclusive consumer will be created if owner_level is set. A consumer with a higher owner_level has higher exclusive priority. The owner level is also know as the ‘epoch value’ of the consumer.

prefetch (int) – The number of events to prefetch from the service for processing. Default is 300.

track_last_enqueued_event_properties (bool) – Indicates whether the consumer should request information on the last-enqueued event on its associated partition, and track that information as events are received. When information about the partitions last-enqueued event is being tracked, each event received from the Event Hubs service will carry metadata about the partition. This results in a small amount of additional network bandwidth consumption that is generally a favorable trade-off when considered against periodically making requests for partition properties using the Event Hub client. It is set to False by default.

starting_position (str, int, datetime.datetime or dict[str,Any]) – Start receiving from this event position if there is no checkpoint data for a partition. Checkpoint data will be used if available. This can be a a dict with partition ID as the key and position as the value for individual partitions, or a single value for all partitions. The value type can be str, int or datetime.datetime. Also supported are the values “-1” for receiving from the beginning of the stream, and “@latest” for receiving only new events. Default value is “@latest”.

starting_position_inclusive (bool or dict[str,bool]) – Determine whether the given starting_position is inclusive(>=) or not (>). True for inclusive and False for exclusive. This can be a dict with partition ID as the key and bool as the value indicating whether the starting_position for a specific partition is inclusive or not. This can also be a single bool value for all starting_position. The default value is False.

on_error (Callable[[PartitionContext, Exception]]) – The callback function that will be called when an error is raised during receiving after retry attempts are exhausted, or during the process of load-balancing. The callback takes two parameters: partition_context which contains partition information and error being the exception. partition_context could be None if the error is raised during the process of load-balance. The callback should be defined like: on_error(partition_context, error). The on_error callback will also be called if an unhandled exception is raised during the on_event callback.

on_partition_initialize (Callable[[PartitionContext]]) – The callback function that will be called after a consumer for a certain partition finishes initialization. It would also be called when a new internal partition consumer is created to take over the receiving process for a failed and closed internal partition consumer. The callback takes a single parameter: partition_context which contains the partition information. The callback should be defined like: on_partition_initialize(partition_context).

on_partition_close (Callable[[PartitionContext, CloseReason]]) – The callback function that will be called after a consumer for a certain partition is closed. It would be also called when error is raised during receiving after retry attempts are exhausted. The callback takes two parameters: partition_context which contains partition information and reason for the close. The callback should be defined like: on_partition_close(partition_context, reason). Please refer to CloseReason for the various closing reasons.

Return type

None
Example:
Receive events from the EventHub.¶
    logger = logging.getLogger("azure.eventhub")

    def on_event(partition_context, event):
        # Put your code here.
        # If the operation is i/o intensive, multi-thread will have better performance.
        logger.info("Received event from partition: {}".format(partition_context.partition_id))

    with consumer:
        consumer.receive(on_event=on_event)
receive_batch(on_event_batch: Callable[[PartitionContext, List[EventData]], None], **kwargs: Any) → None [source]¶
Receive events from partition(s), with optional load-balancing and checkpointing.

Parameters

on_event_batch (Callable[PartitionContext, List[EventData]]) – The callback function for handling a batch of received events. The callback takes two parameters: partition_context which contains partition context and event_batch, which is the received events. The callback function should be defined like: on_event_batch(partition_context, event_batch). event_batch could be an empty list if max_wait_time is not None nor 0 and no event is received after max_wait_time. For detailed partition context information, please refer to PartitionContext.

Keyword Arguments

max_batch_size (int) – The maximum number of events in a batch passed to callback on_event_batch. If the actual received number of events is larger than max_batch_size, the received events are divided into batches and call the callback for each batch with up to max_batch_size events.

max_wait_time (float) – The maximum interval in seconds that the event processor will wait before calling the callback. If no events are received within this interval, the on_event_batch callback will be called with an empty list.

partition_id (str) – If specified, the client will receive from this partition only. Otherwise the client will receive from all partitions.

owner_level (int) – The priority for an exclusive consumer. An exclusive consumer will be created if owner_level is set. A consumer with a higher owner_level has higher exclusive priority. The owner level is also know as the ‘epoch value’ of the consumer.

prefetch (int) – The number of events to prefetch from the service for processing. Default is 300.

track_last_enqueued_event_properties (bool) – Indicates whether the consumer should request information on the last-enqueued event on its associated partition, and track that information as events are received. When information about the partitions last-enqueued event is being tracked, each event received from the Event Hubs service will carry metadata about the partition. This results in a small amount of additional network bandwidth consumption that is generally a favorable trade-off when considered against periodically making requests for partition properties using the Event Hub client. It is set to False by default.

starting_position (str, int, datetime.datetime or dict[str,Any]) – Start receiving from this event position if there is no checkpoint data for a partition. Checkpoint data will be used if available. This can be a a dict with partition ID as the key and position as the value for individual partitions, or a single value for all partitions. The value type can be str, int or datetime.datetime. Also supported are the values “-1” for receiving from the beginning of the stream, and “@latest” for receiving only new events. Default value is “@latest”.

starting_position_inclusive (bool or dict[str,bool]) – Determine whether the given starting_position is inclusive(>=) or not (>). True for inclusive and False for exclusive. This can be a dict with partition ID as the key and bool as the value indicating whether the starting_position for a specific partition is inclusive or not. This can also be a single bool value for all starting_position. The default value is False.

on_error (Callable[[PartitionContext, Exception]]) – The callback function that will be called when an error is raised during receiving after retry attempts are exhausted, or during the process of load-balancing. The callback takes two parameters: partition_context which contains partition information and error being the exception. partition_context could be None if the error is raised during the process of load-balance. The callback should be defined like: on_error(partition_context, error). The on_error callback will also be called if an unhandled exception is raised during the on_event callback.

on_partition_initialize (Callable[[PartitionContext]]) – The callback function that will be called after a consumer for a certain partition finishes initialization. It would also be called when a new internal partition consumer is created to take over the receiving process for a failed and closed internal partition consumer. The callback takes a single parameter: partition_context which contains the partition information. The callback should be defined like: on_partition_initialize(partition_context).

on_partition_close (Callable[[PartitionContext, CloseReason]]) – The callback function that will be called after a consumer for a certain partition is closed. It would be also called when error is raised during receiving after retry attempts are exhausted. The callback takes two parameters: partition_context which contains partition information and reason for the close. The callback should be defined like: on_partition_close(partition_context, reason). Please refer to CloseReason for the various closing reasons.

Return type

None
Example:
Receive events in batches from the EventHub.¶
    logger = logging.getLogger("azure.eventhub")

    def on_event_batch(partition_context, event_batch):
        # Put your code here.
        # If the operation is i/o intensive, multi-thread will have better performance.
        logger.info("Received events from partition: {}".format(partition_context.partition_id))

    with consumer:
        consumer.receive_batch(on_event_batch=on_event_batch)
class azure.eventhub.EventHubProducerClient(fully_qualified_namespace: str, eventhub_name: str, credential: Union[AzureSasCredential, TokenCredential, AzureNamedKeyCredential], **kwargs: Any)[source]¶
The EventHubProducerClient class defines a high level interface for sending events to the Azure Event Hubs service.

Parameters

fully_qualified_namespace (str) – The fully qualified host name for the Event Hubs namespace. This is likely to be similar to <yournamespace>.servicebus.windows.net

eventhub_name (str) – The path of the specific Event Hub to connect the client to.

credential (TokenCredential or AzureSasCredential or AzureNamedKeyCredential) – The credential object used for authentication which implements a particular interface for getting tokens. It accepts EventHubSharedKeyCredential, or credential objects generated by the azure-identity library and objects that implement the get_token(self, *scopes) method.

Keyword Arguments

logging_enable (bool) – Whether to output network trace logs to the logger. Default is False.

auth_timeout (float) – The time in seconds to wait for a token to be authorized by the service. The default value is 60 seconds. If set to 0, no timeout will be enforced from the client.

user_agent (str) – If specified, this will be added in front of the user agent string.

retry_total (int) – The total number of attempts to redo a failed operation when an error occurs. Default value is 3.

retry_backoff_factor (float) – A backoff factor to apply between attempts after the second try (most errors are resolved immediately by a second try without a delay). In fixed mode, retry policy will always sleep for {backoff factor}. In ‘exponential’ mode, retry policy will sleep for: {backoff factor} * (2 ** ({number of total retries} - 1)) seconds. If the backoff_factor is 0.1, then the retry will sleep for [0.0s, 0.2s, 0.4s, …] between retries. The default value is 0.8.

retry_backoff_max (float) – The maximum back off time. Default value is 120 seconds (2 minutes).

retry_mode (str) – The delay behavior between retry attempts. Supported values are ‘fixed’ or ‘exponential’, where default is ‘exponential’.

idle_timeout (float) – Timeout, in seconds, after which this client will close the underlying connection if there is no activity. By default the value is None, meaning that the client will not shutdown due to inactivity unless initiated by the service.
Example:
Create a new instance of the EventHubProducerClient.¶
import os
from azure.eventhub import EventHubProducerClient, EventHubSharedKeyCredential

fully_qualified_namespace = os.environ['EVENT_HUB_HOSTNAME']
eventhub_name = os.environ['EVENT_HUB_NAME']
shared_access_policy = os.environ['EVENT_HUB_SAS_POLICY']
shared_access_key = os.environ['EVENT_HUB_SAS_KEY']

credential = EventHubSharedKeyCredential(shared_access_policy, shared_access_key)
producer = EventHubProducerClient(
    fully_qualified_namespace=fully_qualified_namespace,
    eventhub_name=eventhub_name,  # EventHub name should be specified if it doesn't show up in connection string.
    credential=credential
)
close() → None [source]¶
Close the Producer client underlying AMQP connection and links.

Return type

None
Example:
Close down the client.¶
import os
from azure.eventhub import EventHubProducerClient, EventData

event_hub_connection_str = os.environ['EVENT_HUB_CONN_STR']
eventhub_name = os.environ['EVENT_HUB_NAME']

producer = EventHubProducerClient.from_connection_string(
    conn_str=event_hub_connection_str,
    eventhub_name=eventhub_name  # EventHub name should be specified if it doesn't show up in connection string.
)
try:
    event_data_batch = producer.create_batch()

    while True:
        try:
            event_data_batch.add(EventData('Message inside EventBatchData'))
        except ValueError:
            # EventDataBatch object reaches max_size.
            # New EventDataBatch object can be created here to send more data
            break

    producer.send_batch(event_data_batch)
finally:
    # Close down the producer handler.
    producer.close()
create_batch(**kwargs: Any) → azure.eventhub._common.EventDataBatch[source]¶
Create an EventDataBatch object with the max size of all content being constrained by max_size_in_bytes.

The max_size_in_bytes should be no greater than the max allowed message size defined by the service.

Keyword Arguments

partition_id (str) – The specific partition ID to send to. Default is None, in which case the service will assign to all partitions using round-robin.

partition_key (str) – With the given partition_key, event data will be sent to a particular partition of the Event Hub decided by the service. If both partition_id and partition_key are provided, the partition_id will take precedence. WARNING: Setting partition_key of non-string value on the events to be sent is discouraged as the partition_key will be ignored by the Event Hub service and events will be assigned to all partitions using round-robin. Furthermore, there are SDKs for consuming events which expect partition_key to only be string type, they might fail to parse the non-string value.

max_size_in_bytes (int) – The maximum size of bytes data that an EventDataBatch object can hold. By default, the value is determined by your Event Hubs tier.

Return type

EventDataBatch
Example:
Create EventDataBatch object within limited size¶
    event_data_batch = producer.create_batch()
    while True:
        try:
            event_data_batch.add(EventData('Message inside EventBatchData'))
        except ValueError:
            # The EventDataBatch object reaches its max_size.
            # You can send the full EventDataBatch object and create a new one here.
            break
classmethod from_connection_string(conn_str: str, **kwargs: Any) → azure.eventhub._producer_client.EventHubProducerClient[source]¶
Create an EventHubProducerClient from a connection string.

Parameters

conn_str (str) – The connection string of an Event Hub.

Keyword Arguments

eventhub_name (str) – The path of the specific Event Hub to connect the client to.

logging_enable (bool) – Whether to output network trace logs to the logger. Default is False.

auth_timeout (float) – The time in seconds to wait for a token to be authorized by the service. The default value is 60 seconds. If set to 0, no timeout will be enforced from the client.

user_agent (str) – If specified, this will be added in front of the user agent string.

retry_total (int) – The total number of attempts to redo a failed operation when an error occurs. Default value is 3.

retry_backoff_factor (float) – A backoff factor to apply between attempts after the second try (most errors are resolved immediately by a second try without a delay). In fixed mode, retry policy will always sleep for {backoff factor}. In ‘exponential’ mode, retry policy will sleep for: {backoff factor} * (2 ** ({number of total retries} - 1)) seconds. If the backoff_factor is 0.1, then the retry will sleep for [0.0s, 0.2s, 0.4s, …] between retries. The default value is 0.8.

retry_backoff_max (float) – The maximum back off time. Default value is 120 seconds (2 minutes).

retry_mode (str) – The delay behavior between retry attempts. Supported values are ‘fixed’ or ‘exponential’, where default is ‘exponential’.

idle_timeout (float) – Timeout, in seconds, after which this client will close the underlying connection if there is no activity. By default the value is None, meaning that the client will not shutdown due to inactivity unless initiated by the service.

Return type

EventHubProducerClient
Example:
Create a new instance of the EventHubProducerClient from connection string.¶
import os
from azure.eventhub import EventHubProducerClient
event_hub_connection_str = os.environ['EVENT_HUB_CONN_STR']
eventhub_name = os.environ['EVENT_HUB_NAME']
producer = EventHubProducerClient.from_connection_string(
    conn_str=event_hub_connection_str,
    eventhub_name=eventhub_name  # EventHub name should be specified if it doesn't show up in connection string.
)
get_eventhub_properties() → Dict[str, Any][source]¶

Get properties of the Event Hub.

Keys in the returned dictionary include:

eventhub_name (str)

created_at (UTC datetime.datetime)

partition_ids (list[str])

Return type

dict

Raises

EventHubError

get_partition_ids() → List[str][source]¶

Get partition IDs of the Event Hub.

Return type

list[str]

Raises

EventHubError

get_partition_properties(partition_id: str) → Dict[str, Any][source]¶

Get properties of the specified partition.

Keys in the properties dictionary include:

eventhub_name (str)

id (str)

beginning_sequence_number (int)

last_enqueued_sequence_number (int)

last_enqueued_offset (str)

last_enqueued_time_utc (UTC datetime.datetime)

is_empty (bool)

Parameters

partition_id (str) – The target partition ID.

Return type

dict

Raises

EventHubError
send_batch(event_data_batch: Union[azure.eventhub._common.EventDataBatch, List[Union[azure.eventhub._common.EventData, azure.eventhub.amqp._amqp_message.AmqpAnnotatedMessage]]], **kwargs: Any) → None [source]¶
Sends event data and blocks until acknowledgement is received or operation times out.

If you’re sending a finite list of EventData or AmqpAnnotatedMessage and you know it’s within the event hub frame size limit, you can send them with a send_batch call. Otherwise, use create_batch() to create EventDataBatch and add either EventData or AmqpAnnotatedMessage into the batch one by one until the size limit, and then call this method to send out the batch.

Parameters

event_data_batch (Union[EventDataBatch, List[Union[EventData, AmqpAnnotatedMessage]]) – The EventDataBatch object to be sent or a list of EventData to be sent in a batch. All EventData or AmqpAnnotatedMessage in the list or EventDataBatch will land on the same partition.

Keyword Arguments

timeout (float) – The maximum wait time to send the event data. If not specified, the default wait time specified when the producer was created will be used.

partition_id (str) – The specific partition ID to send to. Default is None, in which case the service will assign to all partitions using round-robin. A TypeError will be raised if partition_id is specified and event_data_batch is an EventDataBatch because EventDataBatch itself has partition_id.

partition_key (str) – With the given partition_key, event data will be sent to a particular partition of the Event Hub decided by the service. A TypeError will be raised if partition_key is specified and event_data_batch is an EventDataBatch because EventDataBatch itself has partition_key. If both partition_id and partition_key are provided, the partition_id will take precedence. WARNING: Setting partition_key of non-string value on the events to be sent is discouraged as the partition_key will be ignored by the Event Hub service and events will be assigned to all partitions using round-robin. Furthermore, there are SDKs for consuming events which expect partition_key to only be string type, they might fail to parse the non-string value.

Return type

None

Raises

AuthenticationError ConnectError ConnectionLostError EventDataError EventDataSendError EventHubError ValueError TypeError
Example:
Sends event data¶
    with producer:
        event_data_batch = producer.create_batch()

        while True:
            try:
                event_data_batch.add(EventData('Message inside EventBatchData'))
            except ValueError:
                # EventDataBatch object reaches max_size.
                # New EventDataBatch object can be created here to send more data
                break

        producer.send_batch(event_data_batch)
class azure.eventhub.EventData(body: Optional[Union[str, bytes, List]] = None)[source]¶
The EventData class is a container for event content.

Parameters

body (str or bytes) – The data to send in a single message. body can be type of str or bytes.
Example:
Create instances of EventData¶
    from azure.eventhub import EventData

    event_data = EventData("String data")
    event_data = EventData(b"Bytes data")
body_as_json(encoding: str = 'UTF-8') → Dict[str, Any][source]¶

The content of the event loaded as a JSON object, if the data is compatible.

Parameters

encoding – The encoding to use for decoding event data. Default is ‘UTF-8’

Return type

dict

body_as_str(encoding: str = 'UTF-8') → str [source]¶

The content of the event as a string, if the data is of a compatible type.

Parameters

encoding – The encoding to use for decoding event data. Default is ‘UTF-8’

Return type

str

property body¶

The body of the Message. The format may vary depending on the body type: For azure.eventhub.amqp.AmqpMessageBodyType.DATA, the body could be bytes or Iterable[bytes]. For azure.eventhub.amqp.AmqpMessageBodyType.SEQUENCE, the body could be List or Iterable[List]. For azure.eventhub.amqp.AmqpMessageBodyType.VALUE, the body could be any type.

Return type

int or bool or float or bytes or str or dict or list or uuid.UUID

property body_type¶

The body type of the underlying AMQP message.

Return type

AmqpMessageBodyType

property content_type¶

The content type descriptor. Optionally describes the payload of the message, with a descriptor following the format of RFC2045, Section 5, for example “application/json”. :rtype: str

property correlation_id¶

The correlation identifier. Allows an application to specify a context for the message for the purposes of correlation, for example reflecting the MessageId of a message that is being replied to. :rtype: str

property enqueued_time¶

The enqueued timestamp of the event.

Return type

datetime.datetime

property message_id¶

The id to identify the message. The message identifier is an application-defined value that uniquely identifies the message and its payload. The identifier is a free-form string and can reflect a GUID or an identifier derived from the application context. If enabled, the duplicate detection feature identifies and removes second and further submissions of messages with the same message id. :rtype: str

property offset¶

The offset of the event.

Return type

str

property partition_key¶

The partition key of the event.

Return type

bytes

property properties¶

Application-defined properties on the event.

Return type

dict

property raw_amqp_message¶

Advanced usage only. The internal AMQP message payload that is sent or received.

property sequence_number¶

The sequence number of the event.

Return type

int

property system_properties¶

Metadata set by the Event Hubs Service associated with the event.

An EventData could have some or all of the following meta data depending on the source of the event data.

b”x-opt-sequence-number” (int)

b”x-opt-offset” (bytes)

b”x-opt-partition-key” (bytes)

b”x-opt-enqueued-time” (int)

b”message-id” (bytes)

b”user-id” (bytes)

b”to” (bytes)

b”subject” (bytes)

b”reply-to” (bytes)

b”correlation-id” (bytes)

b”content-type” (bytes)

b”content-encoding” (bytes)

b”absolute-expiry-time” (int)

b”creation-time” (int)

b”group-id” (bytes)

b”group-sequence” (bytes)

b”reply-to-group-id” (bytes)

Return type

dict
class azure.eventhub.EventDataBatch(max_size_in_bytes: Optional[int] = None, partition_id: Optional[str] = None, partition_key: Optional[Union[str, bytes]] = None)[source]¶

A batch of events.

Sending events in a batch is more performant than sending individual events. EventDataBatch helps you create the maximum allowed size batch of EventData to improve sending performance.

Use the add method to add events until the maximum batch size limit in bytes has been reached - at which point a ValueError will be raised. Use the send_batch method of EventHubProducerClient or the async EventHubProducerClient for sending.

Please use the create_batch method of EventHubProducerClient to create an EventDataBatch object instead of instantiating an EventDataBatch object directly.

WARNING: Updating the value of the instance variable max_size_in_bytes on an instantiated EventDataBatch object is HIGHLY DISCOURAGED. The updated max_size_in_bytes value may conflict with the maximum size of events allowed by the Event Hubs service and result in a sending failure.

Parameters

max_size_in_bytes (int) – The maximum size of bytes data that an EventDataBatch object can hold.

partition_id (str) – The specific partition ID to send to.

partition_key (str) – With the given partition_key, event data will be sent to a particular partition of the Event Hub decided by the service.

add(event_data: Union[azure.eventhub._common.EventData, azure.eventhub.amqp._amqp_message.AmqpAnnotatedMessage]) → None [source]¶

Try to add an EventData to the batch.

The total size of an added event is the sum of its body, properties, etc. If this added size results in the batch exceeding the maximum batch size, a ValueError will be raised.

Parameters

event_data (Union[EventData, AmqpAnnotatedMessage]) – The EventData to add to the batch.

Return type

None

Raise

ValueError, when exceeding the size limit.

property size_in_bytes¶

The combined size of the events in the batch, in bytes.

Return type

int

class azure.eventhub.EventHubSharedKeyCredential(policy: str, key: str)[source]¶

The shared access key credential used for authentication.

Parameters

policy (str) – The name of the shared access policy.

key (str) – The shared access key.

get_token(*scopes: str, **kwargs: Any) → azure.eventhub._client_base.AccessToken[source]¶

class azure.eventhub.CheckpointStore[source]¶

CheckpointStore deals with the interaction with the chosen storage service.

It can list and claim partition ownerships as well as list and save checkpoints.

abstract claim_ownership(ownership_list: Iterable[Dict[str, Any]], **kwargs: Any) → Iterable[Dict[str, Any]][source]¶

Tries to claim ownership for a list of specified partitions.

Parameters

ownership_list (Iterable[Dict[str,Any]]) – Iterable of dictionaries containing all the ownerships to claim.

Return type

Iterable[Dict[str,Any]], Iterable of dictionaries containing partition ownership information:

fully_qualified_namespace (str): The fully qualified namespace that the Event Hub belongs to. The format is like “<namespace>.servicebus.windows.net”.

eventhub_name (str): The name of the specific Event Hub the checkpoint is associated with, relative to the Event Hubs namespace that contains it.

consumer_group (str): The name of the consumer group the ownership are associated with.

partition_id (str): The partition ID which the checkpoint is created for.

owner_id (str): A UUID representing the owner attempting to claim this partition.

last_modified_time (UTC datetime.datetime): The last time this ownership was claimed.

etag (str): The Etag value for the last time this ownership was modified. Optional depending on storage implementation.

abstract list_checkpoints(fully_qualified_namespace: str, eventhub_name: str, consumer_group: str, **kwargs: Any) → Iterable[Dict[str, Any]][source]¶

List the updated checkpoints from the chosen storage service.

Parameters

fully_qualified_namespace (str) – The fully qualified namespace that the Event Hub belongs to. The format is like “<namespace>.servicebus.windows.net”.

eventhub_name (str) – The name of the specific Event Hub the checkpoints are associated with, relative to the Event Hubs namespace that contains it.

consumer_group (str) – The name of the consumer group the checkpoints are associated with.

Return type

Iterable[Dict[str,Any]], Iterable of dictionaries containing partition checkpoint information:

fully_qualified_namespace (str): The fully qualified namespace that the Event Hub belongs to. The format is like “<namespace>.servicebus.windows.net”.

eventhub_name (str): The name of the specific Event Hub the checkpoints are associated with, relative to the Event Hubs namespace that contains it.

consumer_group (str): The name of the consumer group the checkpoints are associated with.

partition_id (str): The partition ID which the checkpoint is created for.

sequence_number (int): The sequence number of the EventData.

offset (str): The offset of the EventData.

abstract list_ownership(fully_qualified_namespace: str, eventhub_name: str, consumer_group: str, **kwargs: Any) → Iterable[Dict[str, Any]][source]¶

Retrieves a complete ownership list from the chosen storage service.

Parameters

fully_qualified_namespace (str) – The fully qualified namespace that the Event Hub belongs to. The format is like “<namespace>.servicebus.windows.net”.

eventhub_name (str) – The name of the specific Event Hub the partition ownerships are associated with, relative to the Event Hubs namespace that contains it.

consumer_group (str) – The name of the consumer group the ownerships are associated with.

Return type

Iterable[Dict[str, Any]], Iterable of dictionaries containing partition ownership information:

fully_qualified_namespace (str): The fully qualified namespace that the Event Hub belongs to. The format is like “<namespace>.servicebus.windows.net”.

eventhub_name (str): The name of the specific Event Hub the checkpoint is associated with, relative to the Event Hubs namespace that contains it.

consumer_group (str): The name of the consumer group the ownership are associated with.

partition_id (str): The partition ID which the checkpoint is created for.

owner_id (str): A UUID representing the current owner of this partition.

last_modified_time (UTC datetime.datetime): The last time this ownership was claimed.

etag (str): The Etag value for the last time this ownership was modified. Optional depending on storage implementation.

abstract update_checkpoint(checkpoint: Dict[str, Optional[Union[str, int]]], **kwargs: Any) → None [source]¶

Updates the checkpoint using the given information for the offset, associated partition and consumer group in the chosen storage service.

Note: If you plan to implement a custom checkpoint store with the intention of running between cross-language EventHubs SDKs, it is recommended to persist the offset value as an integer.

Parameters

checkpoint (Dict[str,Any]) –
A dict containing checkpoint information:

fully_qualified_namespace (str): The fully qualified namespace that the Event Hub belongs to. The format is like “<namespace>.servicebus.windows.net”.

eventhub_name (str): The name of the specific Event Hub the checkpoint is associated with, relative to the Event Hubs namespace that contains it.

consumer_group (str): The name of the consumer group the checkpoint is associated with.

partition_id (str): The partition ID which the checkpoint is created for.

sequence_number (int): The sequence number of the EventData the new checkpoint will be associated with.

offset (str): The offset of the EventData the new checkpoint will be associated with.

Return type

None

class azure.eventhub.PartitionContext(fully_qualified_namespace: str, eventhub_name: str, consumer_group: str, partition_id: str, checkpoint_store: Optional[azure.eventhub._eventprocessor.checkpoint_store.CheckpointStore] = None)[source]¶

Contains partition related context information.

A PartitionContext instance will be passed to the event, error and initialization callbacks defined when calling EventHubConsumerClient.receive(). Users can call update_checkpoint() of this class to persist checkpoint data.

update_checkpoint(event: Optional[EventData] = None, **kwargs: Any) → None [source]¶

Updates the receive checkpoint to the given events offset.

Parameters

event (EventData) – The EventData instance which contains the offset and sequence number information used for checkpoint.

Return type

None

property last_enqueued_event_properties¶

The latest enqueued event information.

This property will be updated each time an event is received if the receiver is created with track_last_enqueued_event_properties set to True. The properties dict includes following information of the last enqueued event:

sequence_number (int)

offset (str)

enqueued_time (UTC datetime.datetime)

retrieval_time (UTC datetime.datetime)

Return type

dict or None

class azure.eventhub.CloseReason(value)[source]¶

The reason a partition consumer is closed.

OWNERSHIP_LOST = 1¶

SHUTDOWN = 0¶

class azure.eventhub.TransportType(value)[source]¶

Transport type The underlying transport protocol type:

Amqp: AMQP over the default TCP transport protocol, it uses port 5671. AmqpOverWebsocket: Amqp over the Web Sockets transport protocol, it uses port 443.

Amqp = 1¶

AmqpOverWebsocket = 2¶

class azure.eventhub.LoadBalancingStrategy(value)[source]¶

An enumeration.

BALANCED = 'balanced'¶

GREEDY = 'greedy'¶

azure.eventhub package¶

Subpackages¶