Reading and writing files in Azure Blob Storage with Python

Azure Blob storage is Microsoft's object storage solution for the cloud and allows you to store massive amounts of unstructured data, such as text or binary data at low cost for every scale. If you are not familiar with it, I can recommend taking a look at the Store data in Azure learning path on Microsoft Learn

Using Python in combination with Azure Blob Storage is quite easy using the azure-storage-blob client library for Python . You can set up a container with private access meaning that you will need to provide credentials to access the containers and the blobs contained within. The easiest way to do this is using a shared access signature (SAS) token. You can generate a SAS token from the Azure Portal.

To interact with the different parts of Azure  Blob Storage you will typically use the BlobServiceClient to work with the Azure storage account itself, the ContainerClient to work with a specific container and the BlobClient to work with a specific blob.  Below is the sample code which uses these different clients in a Jupyter notebook (based on Quickstart: Manage blobs with Python v12 SDK)   - you can find the full Jupyter notebook at tradingnotebooks/AzureBlobStorage.ipynb at master · jorisp/tradingnotebooks (github.com) 

 References:

• Quickstart: Manage blobs with Python v12 SDK
• Using your data lake as a cheap time series database: do's and don'ts
• How to download blobs from Azure Storage using Python - sample code for multithreading