#Import the libraries
import pandas as pd
import requests
from bs4 import BeautifulSoup

#Create empty lists to store the data
crypto_name_list = []
crypto_market_cap_list = []
crypto_price_list = []
crypto_circulating_supply_list = []
crypto_symbol_list = []

#Create an empty dataframe to help organize the data
df = pd.DataFrame()

from datetime import date
#Create a function to scrap the data
# Example: https://coinmarketcap.com/historical/20220227/
def scrape(date = '20220227/'):
  #Get the URL of the website that we want to scrap
  URL = 'https://coinmarketcap.com/historical/'+date
  #Make a request to the website
  webpage = requests.get(URL)
  #Parse the text from the website
  soup = BeautifulSoup(webpage.text, 'html.parser')

  #Get the table row element
  tr = soup.find_all('tr', attrs={'class':'cmc-table-row'})
  #Create  a count variable for the number of crypto currencies that we want scrape
  count = 0
  #Loop through every row to gather the data / information
  for row in tr:
    if count == 10:
      break;
    count = count + 1 #Increment count by 1

    #store the name of the cryptocurrency into a variable
    #Find the td element (or column) to later get the crypto currency name
    name_column = row.find('td', attrs={'class':'cmc-table__cell cmc-table__cell--sticky cmc-table__cell--sortable cmc-table__cell--left cmc-table__cell--sort-by__name'})
    crypto_name = name_column.find('a', attrs={'class':'cmc-table__column-name--name cmc-link'}).text.strip()
    #Store the coin market cap of the cryptocurrency or coin into a variable
    crypto_market_cap = row.find('td', attrs={'class':'cmc-table__cell cmc-table__cell--sortable cmc-table__cell--right cmc-table__cell--sort-by__market-cap'}).text.strip()
    #Find and store the crypto price
    crypto_price = row.find('td', attrs={'class':'cmc-table__cell cmc-table__cell--sortable cmc-table__cell--right cmc-table__cell--sort-by__price'}).text.strip()
    #Find and store the crypto supply and symbol
    crypto_circulating_supply_and_symbol = row.find('td', attrs={'class':'cmc-table__cell cmc-table__cell--sortable cmc-table__cell--right cmc-table__cell--sort-by__circulating-supply'}).text.strip()
    #Split the data
    crypto_circulating_supply = crypto_circulating_supply_and_symbol.split(' ')[0] #first word
    crypto_symbol = crypto_circulating_supply_and_symbol.split(' ')[1] #second word

    #APPEND THE DATA TO THE LISTS
    crypto_name_list.append(crypto_name)
    crypto_market_cap_list.append(crypto_market_cap)
    crypto_price_list.append(crypto_price)
    crypto_circulating_supply_list.append(crypto_circulating_supply)
    crypto_symbol_list.append(crypto_symbol)

#Run the scrape function
scrape(date = '20220227/')

#Store the data into a dataframe to help organize the data
df['Name'] = crypto_name_list
df['Market Cap'] = crypto_market_cap_list
df['Price'] = crypto_market_cap_list
df['Circulating Supply'] = crypto_circulating_supply_list
df['Symbol'] = crypto_symbol_list

#Show the data
df