import os

import sys

import nltk

import moline_sheet_src

import caa_sheet_src

import sag_sheet_src

from request_handling_aws import *

def identify_pipeline(full_body):

    print(dir(moline_sheet_src.main))

    identifiers = {

                    'moline_id' : ('QUAD CITIES',moline_sheet_src.main.run_pipeline),

                    'sag_id' : ('SAINT ANTHONY',sag_sheet_src.main.run_pipeline),

                    'caa_id' : ('Advocate Illinois Masonic Medical Center',caa_sheet_src.main.run_pipeline)

                    }

    for line in full_body:

        for key, val in identifiers.items():

            if nltk.edit_distance(val[0], line.strip())<3:

                return val[1]

def run_pipeline(event, context):

    full_body, ids, form_data = get_all_text(os.getenv("S3_BUCKET_NAME"),os.getenv("BUCKET_DIR"), event_list = event["Records"], require_form=True)

    pipeline_func = identify_pipeline(full_body)

    # block_markers = ['<START>', 'ENCOUNTER', 'PATIENT', 'GUARANTOR', 'COVERAGE']

    # breaking_phrase = 'QUAD CITIES'

    # patient_list = get_patients(full_body,block_markers,breaking_phrase)

    # fin_df = compile_dataframe(patient_list)

    fin_df = pipeline_func(full_body, form_data)

    put_dynamo(os.getenv("DYNAMO_TABLE_NAME"), fin_df, ids)

if __name__ == "__main__":

    os.environ["S3_BUCKET_NAME"] = "facesheet-ap"

    os.environ["BUCKET_DIR"] = "facesheet_moline/"

    os.environ["DYNAMO_TABLE_NAME"] = "patient_data"

    event = {"Records":[{"s3":{"object":{"key":"facesheet_moline/000a5953-9b4a-4abd-9002-a1347ba949e2.png"}}}]}

    run_pipeline(event, {})