import os
import json
import random
import io
import time

from helpers import aws_helper, tar_helper, csv_helper, service_helper

from models.solver_run import SolverRun
from models.solution import Solution
from models.form import Form

from services.base import Base

class Loft(Base):
  def process(self):
    self.solver_run = SolverRun.parse_obj(self.retreive_attributes_from_message())
    self.solution = self.generate_solution()
    self.result = self.stream_to_s3_bucket()

  def retreive_attributes_from_message(self):
    # get s3 object
    key = aws_helper.get_key_from_message(self.source)
    s3_object = aws_helper.get_object(key, os.environ['SOLVER_INGEST_BUCKET'])

    # convert to tar
    tar = tar_helper.raw_to_tar(s3_object)

    # get attributes file and convert to dict
    attributes = json.loads(tar_helper.extract_file_from_tar(tar, 'solver_run_attributes.json').read())

    # get items file and convert to dict
    items_csv = tar_helper.extract_file_from_tar(tar, 'items.csv')
    items_csv_reader = csv_helper.file_stream_reader(items_csv)

    # add items to attributes dict
    attributes['items'] = service_helper.items_csv_to_dict(items_csv_reader)

    return attributes

  def generate_solution(self):
    # temporary data for mocks
    form_count = 10

    # items will be generated from real solver process, this is for mock purposes
    # real solver will return N forms and process a cut score, this is for mock purposes
    return Solution(
      response_id=random.randint(100,5000),
      forms=[
        Form(
          items=[item.id for item in random.sample(self.solver_run.items, self.solver_run.total_form_items)],
          cut_score=120
        ) for x in range(form_count)
      ]
    )

  def stream_to_s3_bucket(self):
    # setup writer buffer and write processed forms to file
    buffer = io.StringIO()
    solution_file = service_helper.solution_to_file(buffer, self.solver_run.total_form_items, self.solution.forms)

    # upload generated file to s3 and return result
    return aws_helper.file_stream_upload(solution_file, f'test_solution_{time.time()}.csv', os.environ['MEASURE_PROCESSED_BUCKET'])