Самообновляющиеся нейростикеры

import lxml.html
from lxml.cssselect import CSSSelector as css
import requests
from urllib.request import urlretrieve


response = requests.get('https://emojipedia.org/people/')
tree = lxml.html.fromstring(response.content)
links = css('.emoji-list>li>a')(tree)

for l in links:
    url = l.get('href')[1:]
    if url == 'serious-face-with-symbols-covering-mouth/':
        # stops downloading on specific emoji
        break
    print(url)
    response = requests.get('https://emojipedia.org/people/'+url)
    tree2 = lxml.html.fromstring(response.content)
    imgs = css('.vendor-image>img')(tree2)
    index = 0
    for i in imgs:
        index += 1
        img_url = i.get('src')
        filename = img_url.split('/')[-1].split('.')
        filename[0] += '_'+str(index)
        filename = '.'.join(filename)
        print('       - '+img_url)
        urlretrieve(img_url, '/Users/z/Downloads/Neuroji_images/'+filename)

%matplotlib inline

import telegram
from telegram.ext import Updater, CommandHandler

from PIL import Image, ImageDraw
from random import randrange
from io import BytesIO

import matplotlib.pyplot as plt
import numpy as np

from keras.layers import Dense, Flatten, Reshape
from keras.layers.advanced_activations import LeakyReLU
from keras.models import Sequential
from keras.optimizers import Adam
from keras.models import model_from_json

import time
import sys

def sample_images(number=1):
    global bot
    global model
    
    print("Hello, World!")
    
    z = np.random.normal(0, 1, (number, z_dim))

    gen_imgs = model.predict(z)
    print('Generated {} images'.format(number))
    gen_imgs = 0.5 * gen_imgs + 0.5

    clear()

    for i in range(number):
        im_ar = (gen_imgs[i, :, :, :]) * 256.
        pil_im = Image.fromarray(im_ar.astype('uint8'), 'RGBA')
        pil_im = pil_im.resize((512,512), Image.NEAREST)
        bio = BytesIO()
        bio.name = 'image.png'
        pil_im.save(bio, 'PNG')
        bio.seek(0)
        bot.add_sticker_to_set(user_id = 115178271, 
                               name = 'neuroji_by_neuroji_bot',
                               png_sticker = bio,
                               emojis = '😶')
    bot.send_message(chat_id='@zbottesting', text='{} neurojis added!'.format(number))

def clear():
    global bot
    stickers = bot.get_sticker_set('neuroji_by_neuroji_bot').stickers
    for s in stickers:
        bot.delete_sticker_from_set(s.file_id)

z_dim = 100 # Size of the noise vector, used as input to the Generator
number = 80

# load json and create model
json_file = open('model_17500.json', 'r')
model_json = json_file.read()
json_file.close()
model = model_from_json(model_json)
model.load_weights("model_17500.h5")
print("Loaded model from disk")

bot = telegram.Bot('851927713:Aa0hGqlACKcGD-deGbTX5BPYdfv3biNywRE')  #FIXME paste your token here
updater = Updater(bot = bot, use_context=True)
j = updater.job_queue

updater.dispatcher.add_handler(CommandHandler('clear', clear))

def recurring_job():
    try:
        sample_images(number)
    except: # catch *all* exceptions
        e = sys.exc_info()[0]
        bot.send_message(chat_id='@zbottesting', text='{}'.format(e))
    time.sleep(60*5)
    recurring_job()
    
recurring_job()