咨询：Azure中storage_account_name等存储参数的查找位置

First, let's recap the code snippet you're working with, which requires three key storage parameters to configure:

def invokeBatchExecutionService(): 
    storage_account_name = "mystorageacct" # Replace this with your Azure Storage Account name 
    storage_account_key = "a_storage_account_key" # Replace this with your Azure Storage Key 
    storage_container_name = "mycontainer" # Replace this with your Azure Storage Container name 
    connection_string = "DefaultEndpointsProtocol=https;AccountName=" + storage_account_name + ";AccountKey=" + storage_account_key 
    api_key = "abc123" # Replace this with the API key for the web service 
    url = "https://ussouthcentral.services.azureml.net/workspaces/e810bf8e16bb4dec9719b07f0205b0bb/services/bc8304cebe1a42bfb2518b302eba979d/jobs" 
    uploadFileToBlob("input1data.file_extension", # Replace this with the location of your input file, and valid file extension (usually .csv) 
    "input1datablob.file_extension", # Replace this with the name you would like to use for your Azure blob; this needs to have the same extension as the input file 
    storage_container_name, storage_account_name, storage_account_key) 

Here's exactly where to find each parameter in the Azure Portal, step by step:

1. storage_account_name #

• Log into the Azure Portal.
• In the top search bar, type Storage Accounts and select the service from the results.
• Locate the storage account you want to use for your batch execution (it might be linked to your Azure ML workspace).
• On the storage account's overview page, the Account name displayed at the top is your storage_account_name.

2. storage_account_key #

• From the same storage account page, look in the left-hand menu under Security + networking and select Access keys.
• You'll see two keys (Key1 and Key2) listed here—either one works. Copy the value from the Key field (not the full connection string) and use that for storage_account_key.
• Pro tip: Treat these keys like passwords—never share them publicly or commit them to code repos.

3. storage_container_name #

• Still on the storage account page, navigate to Data storage in the left-hand menu and select Containers.
• You'll see a list of all containers in this storage account. You can use an existing container's name, or create a new one by clicking the + Container button (pick an access level that fits your use case).
• Copy the container's name into the storage_container_name variable.

Quick Shortcut (If Using a Linked Storage Account) #

If your storage account is automatically linked to your Azure ML workspace:

• Go to your Azure ML workspace in the portal.
• In the left-hand menu under Resources, select Linked resources.
• Find the storage account listed here, click into it, and follow the steps above to grab your parameters.

内容的提问来源于stack exchange，提问作者user9270170