from os.path import join

import click

from app.utils.logger_utils import Logger

log = Logger.getLogger()

# datasets
dataset_keys = ['pipa', 'megaface', 'helen', 'ibm_dif', 'adience', 'who_goes_there', 'vgg_face']
FP_DATASET_ROOT = '/data_store/datasets/people/'


@click.command()
@click.option('-i', '--input', 'opt_fp_in', required=True,
  help='Input file for embassies')
@click.option('-o', '--output', 'opt_fp_out', required=True,
  help='Output file')
@click.option('--datasets-dir', 'opt_dataset_dir', default=FP_DATASET_ROOT)
@click.option('--slice', 'opt_slice', type=(int, int), default=(None, None),
  help='Slice list of files')
@click.option('-f', '--force', 'opt_force', is_flag=True,
  help='Force overwrite')
@click.pass_context
def cli(ctx, opt_fp_in, opt_fp_out, opt_dataset_dir, opt_slice, opt_force):
  """Cross reference"""
  
  import sys
  from os.path import join
  from glob import glob
  from pathlib import Path
  import time

  import pandas as pd
  from tqdm import tqdm

  log = Logger.getLogger()
  log.info('Finding Flickr matches')

  
  fp_counts = {}
  fp_filepaths = {}

  for dk in dataset_keys:
    fp_counts[dk] = join(opt_dataset_dir, dk, f'metadata/{dk}_counts.csv')
    fp_filepaths[dk] = join(opt_dataset_dir, dk, f'metadata/{dk}_filepaths.csv')

  df_query = pd.read_csv(opt_fp_in)
  df_query.fillna('', inplace=True)
  query_nsids = list(df_query['nsid'])

  match_items = []
  matched_images = []
  malta_images = []

  for dataset_key, fp_dataset in tqdm(fp_counts.items()):
    df_counts = pd.read_csv(fp_dataset)
    log.debug(f'loading: {fp_filepaths[dataset_key]}')
    df_filepaths = pd.read_csv(fp_filepaths[dataset_key])
    nsids = list(df_counts['nsid'])
    for nsid in nsids:
      if nsid in query_nsids:
        # add to matches, and count
        count = df_counts[df_counts['nsid'] == nsid]['count'].values[0]
        path_alias = df_query[df_query['nsid'] == nsid]['path_alias'].values[0]
        page_url = f'https://flickr.com/photos/{path_alias}'
        flickr_user_meta = df_query[df_query['nsid'] == nsid].iloc[0]

        match_obj = {
          'count': count,
          'path_alias': path_alias,
          'dataset_key': dataset_key,
          'nsid': nsid,
          'page_url': page_url,
          'username': flickr_user_meta.username
        }
        match_items.append(match_obj)

        # add photo ids or url
        df_nsids = df_filepaths[df_filepaths['nsid'] == nsid]
        nsid_records = df_nsids.to_dict('records')
        for nsid_record in nsid_records:
          photo_id = nsid_record.get('photo_id')
          im_obj = {
            'nsid': nsid,
            'url': nsid_record.get('url'),
            'photo_id': photo_id,
            'dataset_key': dataset_key,
            'path_alias': path_alias,
            'page_url': page_url,
            'filepath': f'{photo_id}.jpg'
          }
          matched_images.append(im_obj)

  # Save embassy matches
  df = pd.DataFrame.from_dict(match_items)
  df.to_csv(opt_fp_out, index=False)
  total = df['count'].sum()
  
  # Save image matches
  df = pd.DataFrame.from_dict(matched_images)
  fp_out = opt_fp_out.replace('.csv', '_images.csv')
  df.to_csv(fp_out, index=False)
  total = len(matched_images)
  log.debug(f'wrote {fp_out}')
  log.debug(f'Found {total:,} images')