def decode_csv()

in src/sagemaker_huggingface_inference_toolkit/decoder_encoder.py [0:0]

• 12 lines of code
• 6 McCabe index (conditional complexity)

def decode_csv(string_like):  # type: (str) -> np.array
    """Convert a CSV object to a dictonary with list attributes.

    Args:
        string_like (str): CSV string.
    Returns:
        (dict): dictonatry for input
    """
    stream = StringIO(string_like)
    # detects if the incoming csv has headers
    if not any(header in string_like.splitlines()[0].lower() for header in ["question", "context", "inputs"]):
        raise PredictionException(
            "You need to provide the correct CSV with Header columns to use it with the inference toolkit default handler.",
            400,
        )
    # reads csv as io
    request_list = list(csv.DictReader(stream))
    if "inputs" in request_list[0].keys():
        return {"inputs": [entry["inputs"] for entry in request_list]}
    else:
        return {"inputs": request_list}