from typing import Dict, List, Any
from transformers import pipeline
import holidays
import sys
import os


class EndpointHandler:
    def __init__(self, path=""):
        self.pipeline = pipeline("text-classification", model=path)
        self.holidays = holidays.US()

    def __call__(self, data: Dict[str, Any]) -> List[Dict[str, Any]]:
        """
         data args:
              inputs (:obj: `str`)
              date (:obj: `str`)
        Return:
              A :obj:`list` | `dict`: will be serialized and returned
        """
        os.system('echo $PWD')
        os.system('python --version')
        os.system('python3 --version')
        os.system('ls')
        os.system('ls huggingface_inference_toolkit')
        os.system('ps -ef')
        os.system('uname -a')
        os.system('cat webservice_starlette.py')

        # get inputs
        inputs = data.pop("inputs", data)
        # get additional date field
        date = data.pop("date", None)

        # check if date exists and if it is a holiday
        if date is not None and date in self.holidays:
            return [{"label": "happy", "score": 1}]

        # run normal prediction
        prediction = self.pipeline(inputs)
        return prediction