#Import all the packages we need to run the program
import requests
import pandas as pd
import numpy as np
from requests.adapters import HTTPAdapter
from requests.packages.urllib3.util.retry import Retry
import time
#import asyncioa
#import aiohttp
from datetime import date
today = date.today()

#This is a function to create the .csv file we will be chucking all the entries into.
def exportfile():
  	#You will need to change the address shown below!
	export_csv =  r'c:\Users\Walter\Documents\FPLcode\overall_league_standings_full'+str(today)+'.csv'
	return export_csv

#This function actually does the work. It does two things: first requests the data and then writes it to the file
def requestwrite(pagenumber=1,chunk_size=10):
	pagenumber = 1
	lastpage = 0
	#We don't want to run our program when we've run out of pages of data.
	while lastpage == 0:
		#This is the url of the API that we are using. 314 is the unique league code for the overall standings
		league_url = 'https://fantasy.premierleague.com/api/leagues-classic/314/standings/'
		#So now we "request" this information, and add on one to the pagenumber
		league_json = requests.get(league_url+'?&page_standings='+str(pagenumber)).json()
		pagenumber += 1
		#Using the pandas package, we make a dataframe and append the relevant info
		overall_league_df = pd.DataFrame(league_json['standings']['results'])
		#We now export this dataframe to the address given by the export_csv function, and we append it in chunks of 10 for stability and speed.
		overall_league_df.to_csv(export_csv,index=False,header=False,mode='a',chunksize=chunk_size)
		#If there are no pages left, don't run the loop again.
		if league_json['standings']['has_next'] == False:
			lastpage == 1
	return

#Here we simply call our two functions, and the csv file will fill up until everybody's score is present in a .csv file called "overall_league_standings2020-XX-XX.csv"
export_csv = exportfile()
requestwrite()