from multiprocessing import Pool
import os
import requests
import time
from PIL import Image

headers = {
  'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_14_0) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/70.0.3538.77 Safari/537.36',
}

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

def fetch_raw(url, **kwargs):
  try:
    resp = requests.get(url, params=kwargs, headers=headers, verify=False)
    if resp.status_code != 200:
      return None
  except:
    return None
  return resp.text

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

# Run this with a pool of 5 agents having a chunksize of 3 until finished
def parallel_fetch(dataset):
  print("Fetching {} tiles".format(len(dataset)))
  agents = 5
  chunksize = 3
  with Pool(processes=agents) as pool:
    pool.starmap(fetch_file, dataset, chunksize)

def load_image(fn):
  try:
    image = Image.open(fn)
    width, height = image.size
    return image, width, height
  except:
    return None, 0, 0