如何使用 StorageStreamDownloader 从一个 blob 下载 ZF7B44CFFAFD5C52223D5498196C8A2E7BZ 并将 stream 上传到另一个 blob？

Question

I believe I have a very simple requirement for which a solution has befuddled me. I am new to the azure-python-sdk and have had little success with its new blob streaming functionality.

Some context

I have used the Java SDK for several years now. Each CloudBlockBlob object has a BlobInputStream and a BlobOutputStream object. When a BlobInputStream is opened, one can invoke its many functions (most notably its read() function) to retrieve data in a true-streaming fashion. A BlobOutputStream , once retrieved, has a write(byte[] data) function where one can continuously write data as frequently as they want until the close() function is invoked. So, it was very easy for me to:

1. Get a CloudBlockBlob object, open it's BlobInputStream and essentially get back an InputStream that was 'tied' to the CloudBlockBlob . It usually maintained 4MB of data - at least, that's what I understood. When some amount of data is read from its buffer, a new (same amount) of data is introduced, so it always has approximately 4MB of new data (until all data is retrieved).
2. Perform some operations on that data.
3. Retrieve the CloudBlockBlob object that I am uploading to, get it's BlobOutputStream , and write to it the data I did some operations on.

A good example of this is if I wanted to compress a file. I had a GzipStreamReader class that would accept an BlobInputStream and an BlobOutputStream . It would read data from the BlobInputStream and, whenever it has compressed some amount of data, write to the BlobOutputStream . It could call write() as many times as it wished; when it finishes reading all the daya, it would close both Input and Output streams, and all was good.

Now for Python

Now, the Python SDK is a little different, and obviously for good reason; the io module works differently than Java's InputStream and OutputStream classes (which the Blob{Input/Output}Stream classes inherit from. I have been struggling to understand how streaming truly works in Azure's python SDK. To start out, I am just trying to see how the StorageStreamDownloader class works. It seems like the StorageStreamDownloader is what holds the 'connection' to the BlockBlob object I am reading data from. If I want to put the data in a stream, I would make a new io.BytesIO() and pass that stream to the StorageStreamDownloader 's readinto method.

For uploads, I would call the BlobClient 's upload method . The upload method accepts a data parameter that is of type Union[Iterable[AnyStr], IO[AnyStr]] .

I don't want to go into too much detail about what I understand, because what I understand and what I have done have gotten me nowhere. I am suspicious that I am expecting something that only the Java SDK offers. But, overall, here are the problems I am having:

1. When I call download_blob , I get back a StorageStreamDownloader with all the data in the blob. Some investigation has shown that I can use the offset and length to download the amount of data I want. Perhaps I can call it once with a download_blob(offset=0, length=4MB) , process the data I get back, then again call download_bloc(offset=4MB, length=4MB) , process the data, etc. This is unfavorable. The other thing I could do is utilize the max_chunk_get_size parameter for the BlobClient and turn on the validate_content flag (make it true) so that the StorageStreamDownloader only downloads 4mb. But this all results in several problems: that's not really streaming from a stream object. I'll still have to call download and readinto several times. And fine, I would do that, if it weren't for the second problem:
2. How the heck do I stream an upload? The upload can take a stream. But if the stream doesn't auto-update itself, then I can only upload once, because all the blobs I deal with must be BlockBlobs . The docs for the upload_function function say that I can provide a param overwrite that does:

keyword bool overwrite: Whether the blob to be uploaded should overwrite the current data. If True, upload_blob will overwrite the existing data. If set to False, the operation will fail with ResourceExistsError. The exception to the above is with Append blob types: if set to False and the data already exists, an error will not be raised and the data will be appended to the existing blob. If set overwrite=True, then the existing append blob will be deleted, and a new one created. Defaults to False.

2. And this makes sense because BlockBlobs , once written to, cannot be written to again. So AFAIK, you can't 'stream' an upload. If I can't have a stream object that is directly tied to the blob, or holds all the data, then the upload() function will terminate as soon as it finishes, right?

Okay. I am certain I am missing something important. I am also somewhat ignorant when it comes to the io module in Python. Though I have developed in Python for a long time, I never really had to deal with that module too closely. I am sure I am missing something, because this functionality is very basic and exists in all the other azure SDKs I know about.

To recap

Everything I said above can honestly be ignored, and only this portion read; I am just trying to show I've done some due diligence. I want to know how to stream data from a blob, process the data I get in a stream, then upload that data. I cannot be receiving all the data in a blob at once. Blobs are likely to be over 1GB and all that pretty stuff. I would honestly love some example code that shows:

1. Retrieving some data from a blob (the data received in one call should not be more than 10MB) in a stream.
2. Compressing the data in that stream.
3. Upload the data to a blob.

This should work for blobs of all sizes; whether its 1MB or 10MB or 10GB should not matter. Step 2 can be anything really; it can also be nothing. Just as long as long as data is being downloaded, inserted into a stream, then uploaded, that would be great. Of course, the other extremely important constraint is that the data per 'download' shouldn't be an amount more than 10MB.

I hope this makes sense. I just want to stream data. This shouldn't be that hard.

Edit:

Some people may want to close this and claim the question is a duplicate. I have forgotten to include something very important: I am currently using the newest , mot up-to-date azure-sdk version. My azure-storage-blob package's version is 12.5.0 . There have been other questions similar to what I have asked for severely outdated versions. I have searched for other answers, but haven't found any for 12+ versions.

Answer 1

If you want to download azure blob in chunk, process every chunk data and upload every chunk data to azure blob, please refer to the follwing code

import io
import os
from azure.storage.blob import BlobClient, BlobBlock
import uuid
key = '<account key>'

source_blob_client = BlobClient(account_url='https://andyprivate.blob.core.windows.net',
                                container_name='',
                                blob_name='',
                                credential=key,
                                max_chunk_get_size=4*1024*1024, # the size of chunk is 4M
                                max_single_get_size=4*1024*1024)

des_blob_client = BlobClient(account_url='https://<account name>.blob.core.windows.net',
                             container_name='',
                             blob_name='',
                             credential=key)
stream = source_blob_client.download_blob()
block_list = []
#read data in chunk
for chunk in stream.chunks():
    #process your data 
    
    # use the put block rest api to upload the chunk to azure storage
    blk_id = str(uuid.uuid4())
    des_blob_client.stage_block(block_id=blk_id, data=<the data after you process>)
    block_list.append(BlobBlock(block_id=blk_id))

#use the put blobk list rest api to ulpoad the whole chunk to azure storage and make up one blob
des_blob_client.commit_block_list(block_list)

Besides, if you just want to copy one blob from storage place to anoter storage place, you can directly use the method start_copy_from_url