import os
from os.path import join
import requests
import urllib3
urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning)

from app.settings import app_cfg

def api_url(path):
  return "https://lens.neural.garden/api/{}/".format(path)

def fetch_cortex_folder(opt_folder_id):
  rows = fetch_json(api_url('file'), folder_id=opt_folder_id)
  fp_out_dir = join(app_cfg.DIR_INPUTS, "cortex", str(opt_folder_id))
  os.makedirs(fp_out_dir, exist_ok=True)
  for row in rows:
    if row['generated'] == 0 and row['processed'] != 1:
      fn, ext = os.path.splitext(row['name'])
      fp_out_image = join(fp_out_dir, "{}{}".format(row['id'], ext))
      if not os.path.exists(fp_out_image):
        fetch_file(row['url'], fp_out_image)

def fetch_json(url, **kwargs):
  resp = requests.get(url, params=kwargs, verify=False, timeout=10)
  return None if resp.status_code != 200 else resp.json()

def fetch_file(url, fn, **kwargs):
  print("Fetch {} => {}".format(url, fn))
  try:
    resp = requests.get(url, params=kwargs, verify=False, timeout=10)
    if resp.status_code != 200:
      return None
  except:
    return None
  size = 0
  with open(fn, 'wb') as f:
    for chunk in resp.iter_content(chunk_size=1024):
      if chunk:
        size += len(chunk)
        f.write(chunk)
  return size

def upload_fp_to_cortex(opt_folder_id, fp):
  files = {
    'file': fp
  }
  data = {
    'folder_id': opt_folder_id,
    'generated': 'true',
    'module': 'biggan',
    'activity': 'invert',
    'datatype': 'image',
  }
  url = os.path.join(api_url('folder'), opt_folder_id, 'upload/')
  print(url)
  r = requests.post(url, files=files, data=data)
  print(r.json())

def upload_bytes_to_cortex(opt_folder_id, fn, fp, mimetype):
  upload_fp_to_cortex(opt_folder_id, (fn, fp.getvalue(), mimetype,))

def upload_file_to_cortex(opt_folder_id, fn):
  with open(fn, 'rb') as fp:
    upload_fp_to_cortex(opt_folder_id, fp)