SPS-C01 Exam Dumps | You are developing a Snowpark Python UDF to perform sentiment analysis on product reviews. The UDF takes

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Question 117/151

You are developing a Snowpark Python UDF to perform sentiment analysis on product reviews. The UDF takes a text review (STRING) as input and returns a sentiment score (FLOAT). You want to operationalize this UDF, ensuring type safety and performance. Which of the following approaches is MOST recommended, considering both ease of use and explicit type declaration?

A. Using Python type hints alone: 'def sentiment_score(review: str) -> float: .... and relying on Snowpark to infer types.

B. Using gudf(return_type=FloatType(), decorator with explicit data type registration.

D. Using only the function name without any explicit type declaration or registration.

E. Casting the result of the UDF to FLOAT within the UDF definition.

Correct Answer: C

Using a combination of type hints and the registration API provides the best balance of readability and explicit type safety. The @udf decorator with 'return_type' and ensures that Snowflake understands the data types, while the Python type hints improve code readability and help catch type errors during development. Option A relies on inference, which can be less explicit and potentially lead to unexpected behavior. Option B lacks the readability of Python type hints. Option D is not a valid way to register a UDF. Casting the result (Option E) doesn't define the data type beforehand and is less efficient than defining during registration.

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