binaryrain-helper-cloud-azure 0.0.6

Aims to simplify and help with commonly used functions in the azure cloud data areas.

Binary Rain Helper Toolkit: Azure Cloud

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.

Key Functions

• return_http_response(): handles returning HTTP responses with status codes and messages:

    from binaryrain_helper_cloud_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)
  

• read_blob_data(): provides a simplified way to read data from Azure Blob Storage:

    from binaryrain_helper_cloud_azure import read_blob_data
  
    # Read a Parquet file from blob storage
    bytes = read_blob_data(
        blob_account="your_account",
        container_name="your_container",
        blob_name="data.parquet"
    )
  
    # Read CSV with custom format
    bytes = read_blob_data(
        blob_account="your_account",
        container_name="your_container",
        blob_name="data.csv",
    )
  

• upload_blob_data(): handles uploading dataframes to blob storage:

      from binaryrain_helper_cloud_azure import upload_blob_data
  
      # Upload dataframe as Parquet
      upload_blob_data(
          blob_account="your_account",
          container_name="your_container",
          blob_name="data.parquet",
          df=your_dataframe
      )
  
      # Upload with compression options
      upload_blob_data(
          blob_account="your_account",
          container_name="your_container",
          blob_name="data.parquet",
          df=your_dataframe,
          file_format_options={'compression': 'snappy'}
      )