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You've created a Snowpark Python UDF that uses a third-party library (e.g., scikit-learn) to perform machine learning inference. You need to ensure that this UDF is executed securely and efficiently in Snowflake. Which of the following approaches represent best practices for managing dependencies and securing the UDF environment? Select all that apply.
Correct Answer: B,E
Including the library's code directly into the UDF is not manageable and maintainable. Snowflake's Anaconda channel simplifies dependency management by providing a curated set of packages. Snowflake's managed dependencies and secure execution environment ensure that the UDF runs in a secure and isolated environment. Disabling security is unacceptable. While external functions could manage dependencies, using the built-in Anaconda integration is simpler within Snowflake. It's also more performant than the overhead of an external function call.