Reducing the amount of List in a WebScraper At the moment, I'm learning and experimenting on the use of web scraping content from different varieties of web pages. But I've come across a common smelly code among several of my applications. I have many repetitive List that has data being append to them.

from requests import get
import requests
import json
from time import sleep
import pandas as pd

url = 'https://shopee.com.my/api/v2/flash_sale/get_items?offset=0&amp;limit=16&amp;filter_soldout=true'
list_name = []
list_price = []
list_discount = []
list_stock = []

response = get(url)
json_data = response.json()


def getShockingSales():
    index = 0
    if response.status_code is 200:
        print('Response: ' + 'OK')
    else:
        print('Unable to access')
    total_flashsale = len(json_data['data']['items'])
    total_flashsale -= 1
    for i in range(index, total_flashsale):
        print('Getting data from site... please wait a few seconds')
        while i &lt;= total_flashsale:
            flash_name = json_data['data']['items'][i]['name']
            flash_price = json_data['data']['items'][i]['price']
            flash_discount = json_data['data']['items'][i]['discount']
            flash_stock = json_data['data']['items'][i]['stock']
            list_name.append(flash_name)
            list_price.append(flash_price)
            list_discount.append(flash_discount)
            list_stock.append(flash_stock)
            sleep(0.5)
            i += 1
        if i &gt; total_flashsale:
            print('Task is completed...')
            return

getShockingSales()
new_panda = pd.DataFrame({'Name': list_name, 'Price': list_price,
                          'Discount': list_discount, 'Stock Available': list_stock})

print('Converting to Panda Frame....')
sleep(5)
print(new_panda)


Would one list be more than sufficient? Am I approaching this wrongly.
Review


Creating functions that read and modify global variables is not a good idea, for example if someone wants to reuse your function, they won't know about side effects.
index is not useful, and range(0, n) is the same as range(n)
Using == is more appropriate than is in general, hence response.status_code == 200
If response.status_code != 200, I think the function should ~return an empty result~ raise an exception like said by @Ludisposed.
You use json_data["data"]["items"] a lot, you could define items = json_data["data"]["items"] instead, but see below.
Your usage of i is totally messy. Never use both for and while on the same variable. I think you just want to get the information for each item. So just use for item in json_data["data"]["items"]:.
Actually, print("Getting data from site... please wait a few seconds") is wrong as you got the data at response = get(url). Also, sleep(0.5) and sleep(5) don't make any sense.
Speaking from this, requests.get is more explicit.
You can actually create a pandas DataFrame directly from a list of dictionaries.
Actually, if you don't use the response in another place, you can use the url as an argument of the function.
Putting spaces in column names of a DataFrame is not a good idea. It removes the possibility to access the column named stock (for example) with df.stock. If you still want that, you can use pandas.DataFrame.rename
You don't need to import json.
The discounts are given as strings like "59%". I think integers are preferable if you want to perform computations on them. I used df.discount = df.discount.apply(lambda s: int(s[:-1])) to perform this.
Optional: you might want to use logging instead of printing everything. Or at least print to stderr with:

from sys import stderr

print('Information', file=stderr)


Code

import requests
import pandas as pd


def getShockingSales(url):
    response = requests.get(url)
    columns = ["name", "price", "discount", "stock"]
    response.raise_for_status()
    print("Response: OK")
    json_data = response.json()
    df = pd.DataFrame(json_data["data"]["items"])[columns]
    df.discount = df.discount.apply(lambda s: int(s[:-1]))
    print("Task is completed...")
    return df


URL = "https://shopee.com.my/api/v2/flash_sale/get_items?offset=0&amp;limit=16&amp;filter_soldout=true"
df = getShockingSales(URL)