Cloud Azure

binaryrain_helper_cloud_azure is a python package that aims to simplify and help with common functions in Azure Cloud areas. It builds on top of the azure library and provides additional functionality to make working with Azure Cloud easier, reduces boilerplate code and provides clear error messages.

Installation

To install the package you can use your favorite python package manager:

PIP

pip install binaryrain-helper-cloud-azure

UV

uv add binaryrain-helper-cloud-azure

Key Functions

return_http_response()

azure.functions.HttpResponse

handles returning HTTP responses with status codes and messages:

from binaryrain_helper_cloud_azure.azure import return_http_response
import json

# Return a 200 OK response

return return_http_response('Success Message', 200)

# Return json data with a 201 Created response

return return_http_response(json.dumps({'key': 'value'}), 201)

# Return a 404 Not Found response

return return_http_response('Resource not found', 404)

# Return a 500 Internal Server Error response

return return_http_response('Internal Server Error', 500)

Parameters:

• message: str | The message to be returned in the response.
• status_code: int | The status code of the response.

read_blob_data()

bytes

provides a simplified way to read data from Azure Blob Storage:

from binaryrain_helper_cloud_azure.azure import read_blob_data

# Read a Parquet file from blob storage

df = read_blob_data(
blob_account="your_account",
container_name="your_container",
blob_name="data.parquet"
)

# Read CSV with custom format

df = read_blob_data(
blob_account="your_account",
container_name="your_container",
blob_name="data.csv",
)

Parameters

• blob_account: str | The name of the blob account. For example, “https://YOUR-ACCOUNT.blob.core.windows.net/”
• container_name: str | The name of the container.
• blob_name: str | The name of the blob.

upload_blob_data()

bool

handles uploading dataframes to blob storage:

from binaryrain_helper_cloud_azure.azure import upload_blob_data

# Upload dataframe as Parquet

upload_blob_data(
blob_account="your_account",
container_name="your_container",
blob_name="data.parquet",
file_contents=your_data
)

# Upload with compression options

upload_blob_data(
blob_account="your_account",
container_name="your_container",
blob_name="data.parquet",
file_contents=your_data,
file_format_options={'compression': 'snappy'}
)

# Upload a dataframe

upload_blob_data(
blob_account="your_account",
container_name="your_container",
blob_name="data.csv",
file_contents=bytes(df.to_csv(sep=";", index=False), encoding="utf-8")
)

Parameters

• blob_account: str | The name of the blob account.
• container_name: str | The name of the container.
• blob_name: str | The name of the blob.
• file_contents: bytes | The file contents to be saved.

get_secret_data()

dict

Get secret data from Azure Key Vault:

from binaryrain_helper_cloud_azure.azure import get_secret_data

secret = get_secret_data("your_keyvault_url", "your_secret_name")

Parameters

• key_vault_url: str | The URL of the Azure Key Vault.
• secret_name: str | The name of the secret.

create_adf_pipeline()

str

Create an Azure Data Factory pipeline run:

from binaryrain_helper_cloud_azure.azure import create_adf_pipeline

# Create a data factory run

params_json = {"param1": "value1"}
pipeline_id = create_adf_pipeline(
subscription_id="your_subscription_id",
resource_group_name="your_resource_group_name",
factory_name="your_adf_name",
pipeline_name="your_pipeline_name",
parameters=params_json,
)

Parameters

• subscription_id: str | The subscription ID of the Azure account.
• resource_group_name: str | The name of the resource group.
• factory_name: str | The name of the Data Factory.
• pipeline_name: str | The name of the pipeline.
• parameters: dict | None | (Optional) The parameters to be passed to the pipeline.
• credentials: DefaultAzureCredential | TokenCredential | (Optional) The credentials to be used for authentication. Defaults to DefaultAzureCredential()
• adf_base_url: str | (Optional) The base URL of the Azure Data Factory Management API. Defaults to https://management.azure.com