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This article shows how to download a blob using the
Azure Storage client library for Python
. You can download blob data to various destinations, including a local file path, stream, or text string. You can also open a blob stream and read from it.
To learn about downloading blobs using asynchronous APIs, see
Download blobs asynchronously
.
Prerequisites
This article assumes you already have a project set up to work with the Azure Blob Storage client library for Python. To learn about setting up your project, including package installation, adding
import
statements, and creating an authorized client object, see
Get started with Azure Blob Storage and Python
.
To use asynchronous APIs in your code, see the requirements in the
Asynchronous programming
section.
The
authorization mechanism
must have permissions to perform a download operation. To learn more, see the authorization guidance for the following REST API operation:
Get Blob
Download a blob
You can use the following method to download a blob:
BlobClient.download_blob
The
download_blob
method returns a
StorageStreamDownloader
object. During a download, the client libraries split the download request into chunks, where each chunk is downloaded with a separate
Get Blob
range request. This behavior depends on the total size of the blob and how the
data transfer options
are set.
Download to a file path
The following example downloads a blob to a file path:
def download_blob_to_file(self, blob_service_client: BlobServiceClient, container_name):
blob_client = blob_service_client.get_blob_client(container=container_name, blob="sample-blob.txt")
with open(file=os.path.join(r'filepath', 'filename'), mode="wb") as sample_blob:
download_stream = blob_client.download_blob()
sample_blob.write(download_stream.readall())
Download to a stream
The following example downloads a blob to a stream. In this example, StorageStreamDownloader.read_into downloads the blob contents to a stream and returns the number of bytes read:
def download_blob_to_stream(self, blob_service_client: BlobServiceClient, container_name):
blob_client = blob_service_client.get_blob_client(container=container_name, blob="sample-blob.txt")
# readinto() downloads the blob contents to a stream and returns the number of bytes read
stream = io.BytesIO()
num_bytes = blob_client.download_blob().readinto(stream)
print(f"Number of bytes: {num_bytes}")
Download a blob in chunks
The following example downloads a blob and iterates over chunks in the download stream. In this example, StorageStreamDownloader.chunks returns an iterator, which allows you to read the blob content in chunks:
def download_blob_chunks(self, blob_service_client: BlobServiceClient, container_name):
blob_client = blob_service_client.get_blob_client(container=container_name, blob="sample-blob.txt")
# This returns a StorageStreamDownloader
stream = blob_client.download_blob()
chunk_list = []
# Read data in chunks to avoid loading all into memory at once
for chunk in stream.chunks():
# Process your data (anything can be done here - 'chunk' is a byte array)
chunk_list.append(chunk)
Download to a string
The following example downloads blob contents as text. In this example, the encoding
parameter is necessary for readall()
to return a string, otherwise it returns bytes:
def download_blob_to_string(self, blob_service_client: BlobServiceClient, container_name):
blob_client = blob_service_client.get_blob_client(container=container_name, blob="sample-blob.txt")
# encoding param is necessary for readall() to return str, otherwise it returns bytes
downloader = blob_client.download_blob(max_concurrency=1, encoding='UTF-8')
blob_text = downloader.readall()
print(f"Blob contents: {blob_text}")
Download a block blob with configuration options
You can define client library configuration options when downloading a blob. These options can be tuned to improve performance and enhance reliability. The following code examples show how to define configuration options for a download both at the method level, and at the client level when instantiating BlobClient. These options can also be configured for a ContainerClient instance or a BlobServiceClient instance.
Specify data transfer options on download
You can set configuration options when instantiating a client to optimize performance for data transfer operations. You can pass the following keyword arguments when constructing a client object in Python:
max_chunk_get_size
- The maximum chunk size used for downloading a blob. Defaults to 4 MiB.
max_single_get_size
- The maximum size for a blob to be downloaded in a single call. If the total blob size exceeds max_single_get_size
, the remainder of the blob data is downloaded in chunks. Defaults to 32 MiB.
For download operations, you can also pass the max_concurrency
argument when calling download_blob. This argument defines the maximum number of parallel connections for the download operation.
The following code example shows how to specify data transfer options when creating a BlobClient
object, and how to download data using that client object. The values provided in this sample aren't intended to be a recommendation. To properly tune these values, you need to consider the specific needs of your app.
def download_blob_transfer_options(self, account_url: str, container_name: str, blob_name: str):
# Create a BlobClient object with data transfer options for download
blob_client = BlobClient(
account_url=account_url,
container_name=container_name,
blob_name=blob_name,
credential=DefaultAzureCredential(),
max_single_get_size=1024*1024*32, # 32 MiB
max_chunk_get_size=1024*1024*4 # 4 MiB
with open(file=os.path.join(r'file_path', 'file_name'), mode="wb") as sample_blob:
download_stream = blob_client.download_blob(max_concurrency=2)
sample_blob.write(download_stream.readall())
Download blobs asynchronously
The Azure Blob Storage client library for Python supports downloading blobs asynchronously. To learn more about project setup requirements, see Asynchronous programming.
Follow these steps to download a blob using asynchronous APIs:
Add the following import statements:
import asyncio
from azure.identity.aio import DefaultAzureCredential
from azure.storage.blob.aio import BlobServiceClient, BlobClient
Add code to run the program using asyncio.run
. This function runs the passed coroutine, main()
in our example, and manages the asyncio
event loop. Coroutines are declared with the async/await syntax. In this example, the main()
coroutine first creates the top level BlobServiceClient
using async with
, then calls the method that downloads the blob. Note that only the top level client needs to use async with
, as other clients created from it share the same connection pool.
async def main():
sample = BlobSamples()
# TODO: Replace <storage-account-name> with your actual storage account name
account_url = "https://<storage-account-name>.blob.core.windows.net"
credential = DefaultAzureCredential()
async with BlobServiceClient(account_url, credential=credential) as blob_service_client:
await sample.download_blob_to_file(blob_service_client, "sample-container")
if __name__ == '__main__':
asyncio.run(main())
Add code to download the blob. The following example downloads a blob to a local file path using a BlobClient
object. The code is the same as the synchronous example, except that the method is declared with the async
keyword and the await
keyword is used when calling the download_blob
method.
async def download_blob_to_file(self, blob_service_client: BlobServiceClient, container_name):
blob_client = blob_service_client.get_blob_client(container=container_name, blob="sample-blob.txt")
with open(file=os.path.join(r'filepath', 'filename'), mode="wb") as sample_blob:
download_stream = await blob_client.download_blob()
data = await download_stream.readall()
sample_blob.write(data)
With this basic setup in place, you can implement other examples in this article as coroutines using async/await syntax.
Resources
To learn more about how to download blobs using the Azure Blob Storage client library for Python, see the following resources.
REST API operations
The Azure SDK for Python contains libraries that build on top of the Azure REST API, allowing you to interact with REST API operations through familiar Python paradigms. The client library methods for downloading blobs use the following REST API operation:
Get Blob (REST API)
Code samples
View synchronous or asynchronous code samples from this article (GitHub)
Client library resources
Client library reference documentation
Client library source code
Package (PyPi)
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