Azure Storage Queues client library for Python

Azure Queue storage is a service for storing large numbers of messages that can be accessed from anywhere in the world via authenticated calls using HTTP or HTTPS. A single queue message can be up to 64 KiB in size, and a queue can contain millions of messages, up to the total capacity limit of a storage account.

Common uses of Queue storage include:

  • Creating a backlog of work to process asynchronously

  • Passing messages between different parts of a distributed application

Source code | Package (PyPI) | API reference documentation | Product documentation | Samples

Getting started

Prerequisites

Install the package

Install the Azure Storage Queues client library for Python with pip:

pip install azure-storage-queue

Create a storage account

If you wish to create a new storage account, you can use the Azure Portal, Azure PowerShell, or Azure CLI:

# Create a new resource group to hold the storage account -
# if using an existing resource group, skip this step
az group create --name my-resource-group --location westus2

# Create the storage account
az storage account create -n my-storage-account-name -g my-resource-group

Create the client

The Azure Storage Queues client library for Python allows you to interact with three types of resources: the storage account itself, queues, and messages. Interaction with these resources starts with an instance of a client. To create a client object, you will need the storage account’s queue service endpoint URL and a credential that allows you to access the storage account:

from azure.storage.queue import QueueServiceClient

service = QueueServiceClient(account_url="https://<my-storage-account-name>.queue.core.windows.net/", credential=credential)

Looking up the account URL

You can find the storage account’s queue service URL using the Azure Portal, Azure PowerShell, or Azure CLI:

# Get the queue service URL for the storage account
az storage account show -n my-storage-account-name -g my-resource-group --query "primaryEndpoints.queue"

Types of credentials

The credential parameter may be provided in a number of different forms, depending on the type of authorization you wish to use:

  1. To use a shared access signature (SAS) token, provide the token as a string. If your account URL includes the SAS token, omit the credential parameter. You can generate a SAS token from the Azure Portal under “Shared access signature” or use one of the generate_sas() functions to create a sas token for the storage account or queue:

    from datetime import datetime, timedelta
from azure.storage.queue import QueueServiceClient, generate_account_sas, ResourceTypes, AccountSasPermissions

sas_token = generate_account_sas(
    account_name="<storage-account-name>",
    account_key="<account-access-key>",
    resource_types=ResourceTypes(service=True),
    permission=AccountSasPermissions(read=True),
    expiry=datetime.utcnow() + timedelta(hours=1)
)

queue_service_client = QueueServiceClient(account_url="https://<my_account_name>.queue.core.windows.net", credential=sas_token)

  2. To use a storage account shared key (aka account key or access key), provide the key as a string. This can be found in the Azure Portal under the “Access Keys” section or by running the following Azure CLI command:

    az storage account keys list -g MyResourceGroup -n MyStorageAccount

    Use the key as the credential parameter to authenticate the client:

    from azure.storage.queue import QueueServiceClient
service = QueueServiceClient(account_url="https://<my_account_name>.queue.core.windows.net", credential="<account_access_key>")

  3. To use an Azure Active Directory (AAD) token credential, provide an instance of the desired credential type obtained from the azure-identity library. For example, DefaultAzureCredential can be used to authenticate the client.

    This requires some initial setup:

    • Install azure-identity

    • Register a new AAD application and give permissions to access Azure Storage

    • Grant access to Azure Queue data with RBAC in the Azure Portal

    • Set the values of the client ID, tenant ID, and client secret of the AAD application as environment variables: AZURE_TENANT_ID, AZURE_CLIENT_ID, AZURE_CLIENT_SECRET

    Use the returned token credential to authenticate the client:

    from azure.identity import DefaultAzureCredential
from azure.storage.queue import QueueServiceClient
token_credential = DefaultAzureCredential()

queue_service_client = QueueServiceClient(
    account_url="https://<my_account_name>.queue.core.windows.net",
    credential=token_credential
)

Creating the client from a connection string

Depending on your use case and authorization method, you may prefer to initialize a client instance with a storage connection string instead of providing the account URL and credential separately. To do this, pass the storage connection string to the client’s from_connection_string class method:

from azure.storage.queue import QueueServiceClient

connection_string = "DefaultEndpointsProtocol=https;AccountName=xxxx;AccountKey=xxxx;EndpointSuffix=core.windows.net"
service = QueueServiceClient.from_connection_string(conn_str=connection_string)

The connection string to your storage account can be found in the Azure Portal under the “Access Keys” section or by running the following CLI command:

az storage account show-connection-string -g MyResourceGroup -n MyStorageAccount

Key concepts

The following components make up the Azure Queue Service:

  • The storage account itself

  • A queue within the storage account, which contains a set of messages

  • A message within a queue, in any format, of up to 64 KiB

The Azure Storage Queues client library for Python allows you to interact with each of these components through the use of a dedicated client object.

Clients

Two different clients are provided to to interact with the various components of the Queue Service:

  1. QueueServiceClient -

    this client represents interaction with the Azure storage account itself, and allows you to acquire preconfigured client instances to access the queues within. It provides operations to retrieve and configure the account properties as well as list, create, and delete queues within the account. To perform operations on a specific queue, retrieve a client using the get_queue_client method.

  2. QueueClient -

    this client represents interaction with a specific queue (which need not exist yet). It provides operations to create, delete, or configure a queue and includes operations to send, receive, peek, delete, and update messages within it.

Messages

  • Send - Adds a message to the queue and optionally sets a visibility timeout for the message.

  • Receive - Retrieves a message from the queue and makes it invisible to other consumers.

  • Peek - Retrieves a message from the front of the queue, without changing the message visibility.

  • Update - Updates the visibility timeout of a message and/or the message contents.

  • Delete - Deletes a specified message from the queue.

  • Clear - Clears all messages from the queue.

Examples

The following sections provide several code snippets covering some of the most common Storage Queue tasks, including:

Creating a queue

Create a queue in your storage account

from azure.storage.queue import QueueClient

queue = QueueClient.from_connection_string(conn_str="<connection_string>", queue_name="my_queue")
queue.create_queue()

Use the async client to create a queue

from azure.storage.queue.aio import QueueClient

queue = QueueClient.from_connection_string(conn_str="<connection_string>", queue_name="my_queue")
await queue.create_queue()

Sending messages

Send messages to your queue

from azure.storage.queue import QueueClient

queue = QueueClient.from_connection_string(conn_str="<connection_string>", queue_name="my_queue")
queue.send_message("I'm using queues!")
queue.send_message("This is my second message")

Send messages asynchronously

import asyncio
from azure.storage.queue.aio import QueueClient

queue = QueueClient.from_connection_string(conn_str="<connection_string>", queue_name="my_queue")
await asyncio.gather(
    queue.send_message("I'm using queues!"),
    queue.send_message("This is my second message")
)

Receiving messages

Receive and process messages from your queue

from azure.storage.queue import QueueClient

queue = QueueClient.from_connection_string(conn_str="<connection_string>", queue_name="my_queue")
response = queue.receive_messages()

for message in response:
    print(message.content)
    queue.delete_message(message)

# Printed messages from the front of the queue:
# >> I'm using queues!
# >> This is my second message

Receive and process messages in batches

from azure.storage.queue import QueueClient

queue = QueueClient.from_connection_string(conn_str="<connection_string>", queue_name="my_queue")
response = queue.receive_messages(messages_per_page=10)

for message_batch in response.by_page():
    for message in message_batch:
        print(message.content)
        queue.delete_message(message)

Receive and process messages asynchronously

from azure.storage.queue.aio import QueueClient

queue = QueueClient.from_connection_string(conn_str="<connection_string>", queue_name="my_queue")
response = queue.receive_messages()

async for message in response:
    print(message.content)
    await queue.delete_message(message)

Optional Configuration

Optional keyword arguments that can be passed in at the client and per-operation level.

Retry Policy configuration

Use the following keyword arguments when instantiating a client to configure the retry policy:

  • retry_total (int): Total number of retries to allow. Takes precedence over other counts. Pass in retry_total=0 if you do not want to retry on requests. Defaults to 10.

  • retry_connect (int): How many connection-related errors to retry on. Defaults to 3.

  • retry_read (int): How many times to retry on read errors. Defaults to 3.

  • retry_status (int): How many times to retry on bad status codes. Defaults to 3.

  • retry_to_secondary (bool): Whether the request should be retried to secondary, if able. This should only be enabled of RA-GRS accounts are used and potentially stale data can be handled. Defaults to False.

Other client / per-operation configuration

Other optional configuration keyword arguments that can be specified on the client or per-operation.

Client keyword arguments:

  • connection_timeout (int): Optionally sets the connect and read timeout value, in seconds.

  • transport (Any): User-provided transport to send the HTTP request.

Per-operation keyword arguments:

  • raw_response_hook (callable): The given callback uses the response returned from the service.

  • raw_request_hook (callable): The given callback uses the request before being sent to service.

  • client_request_id (str): Optional user specified identification of the request.

  • user_agent (str): Appends the custom value to the user-agent header to be sent with the request.

  • logging_enable (bool): Enables logging at the DEBUG level. Defaults to False. Can also be passed in at the client level to enable it for all requests.

  • headers (dict): Pass in custom headers as key, value pairs. E.g. headers={'CustomValue': value}

Troubleshooting

General

Storage Queue clients raise exceptions defined in Azure Core. All Queue service operations will throw a StorageErrorException on failure with helpful error codes.

Logging

This library uses the standard logging library for logging. Basic information about HTTP sessions (URLs, headers, etc.) is logged at INFO level.

Detailed DEBUG level logging, including request/response bodies and unredacted headers, can be enabled on a client with the logging_enable argument:

import sys
import logging
from azure.storage.queue import QueueServiceClient

# Create a logger for the 'azure.storage.queue' SDK
logger = logging.getLogger('azure.storage.queue')
logger.setLevel(logging.DEBUG)

# Configure a console output
handler = logging.StreamHandler(stream=sys.stdout)
logger.addHandler(handler)

# This client will log detailed information about its HTTP sessions, at DEBUG level
service_client = QueueServiceClient.from_connection_string("your_connection_string", logging_enable=True)

Similarly, logging_enable can enable detailed logging for a single operation, even when it isn’t enabled for the client:

service_client.get_service_stats(logging_enable=True)

Next steps

More sample code

Get started with our Queue samples.

Several Storage Queues Python SDK samples are available to you in the SDK’s GitHub repository. These samples provide example code for additional scenarios commonly encountered while working with Storage Queues:

  • queue_samples_hello_world.py (async version) - Examples found in this article:

    • Client creation

    • Create a queue

    • Send messages

    • Receive messages

  • queue_samples_authentication.py (async version) - Examples for authenticating and creating the client:

    • From a connection string

    • From a shared access key

    • From a shared access signature token

    • From Azure Active Directory

  • queue_samples_service.py (async version) - Examples for interacting with the queue service:

    • Get and set service properties

    • List queues in a storage account

    • Create and delete a queue from the service

    • Get the QueueClient

  • queue_samples_message.py (async version) - Examples for working with queues and messages:

    • Set an access policy

    • Get and set queue metadata

    • Send and receive messages

    • Delete specified messages and clear all messages

    • Peek and update messages

Additional documentation

For more extensive documentation on Azure Queue storage, see the Azure Queue storage documentation on docs.microsoft.com.

Contributing

This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.microsoft.com.

When you submit a pull request, a CLA-bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.

This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.