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You are working with a data science team that needs to create Snowpark DataFrames from various file types (CSV, JSON, Parquet, and XML) stored in different locations (internal stages, external stages on AWS S3, and Azure Blob Storage). The team wants a unified and reusable function to create DataFrames, abstracting away the specific file format and location details. Which of the following approaches using Snowpark Python API will provide the MOST flexible and maintainable solution?
Correct Answer: C
Option C provides the best balance of flexibility, maintainability, and conciseness. Using 'getattr(session.read, file_format)' allows dynamically calling the appropriate 'session.read' method (e.g., 'session.read.csv', 'session.read.json') based on a string parameter. Passing additional configuration through a dictionary allows customizing the read operation without modifying the core function. Options A, B, D, and E are less flexible, more verbose, or less efficient.