import requests , json, csv
import pandas as pd

# Overall FPL league ID, 314 for 2019/20 season.
overallLeageID = 314

# number of GW in 2019/20 season. Done as array to avoid calling api for blank GW 30-38.
gameWeeks = [1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,39,40,
		41,42,43,44,45,46,47]

# adds the top 10 team ID's to this array
teamIDarray = []

# number of top manager information required.
topManagerNumber = 10

url = "https://fantasy.premierleague.com/api/leagues-classic/"+str(overallLeageID)+"/standings/"

response = requests.get(url)
data = response.text
parsed = json.loads(data)
managerParsed = parsed['standings']['results']

# open 3 files for writing
manager_data = open('data/2019-20/managers/top_managers.csv', 'w', newline='', encoding="utf-8")
gw_data = open('data/2019-20/managers/top_managers_gwInfo.csv', 'w', newline='', encoding="utf-8")
gw_picks = open('data/2019-20/managers/top_managers_gwPicks.csv', 'w', newline='', encoding="utf-8")

# create the 3 csv writer objects
csvwriter1 = csv.writer(manager_data)
csvwriter2 = csv.writer(gw_data)
csvwriter3 = csv.writer(gw_picks)

#get csv of top 10 manager information and write to top_managers.csv
count = 0
for manager in managerParsed:
	if count == 0:
		header = ['rank','entry','player_name','entry_name','total']
		csvwriter1.writerow(header)
		count += 1
	
	if count <= topManagerNumber:
		csvwriter1.writerow([manager['rank'],manager['entry'],manager['player_name'],
						manager['entry_name'],manager['total']])

		count +=1
		teamIDarray.append(manager['entry'])

# for each teamID in the top 10, call the api and update both top_managers_gwInfo.csv and top_managers_gwPicks.csv
count1 = 0
count2 = 0
for teamID in teamIDarray:
	for x in gameWeeks:
		url = "https://fantasy.premierleague.com/api/entry/"+str(teamID)+"/event/"+str(x)+"/picks/"
		response = requests.get(url)
		data = response.text
		parsed = json.loads(data)

		# write data to top_managers_gwInfo.csv
		if count1 == 0:
			header = ['team_id','gw','points','bench','gw_rank','transfers','hits','total_points',
				'overall_ank','team_value','chip']

			csvwriter2.writerow(header)
			count1 += 1
		try:
			csvwriter2.writerow([teamID,x, parsed['entry_history']['points'], parsed['entry_history']['points_on_bench'],
							parsed['entry_history']['rank'], parsed['entry_history']['event_transfers'],
							parsed['entry_history']['event_transfers_cost'], parsed['entry_history']['total_points'],
							parsed['entry_history']['overall_rank'], int(parsed['entry_history']['value'])/10, parsed['active_chip']])
		except:
			continue

		# write data to top_managers_gwPicks.csv
		for i in range(len(parsed['picks'])):
			if count2 == 0:
				header = ['team_id','gw','id','position','multiplier']
				csvwriter3.writerow(header)
				count2 += 1
			csvwriter3.writerow([teamID, x, parsed['picks'][i]['element'], parsed['picks'][i]['position'], parsed['picks'][i]['multiplier']])

manager_data.close()
gw_data.close()
gw_picks.close()

# do some formatting on top_managers_gwPicks by adding the name of the player picked from player_idlist.csv
df = pd.read_csv('data/2019-20/managers/top_managers_gwPicks.csv')
df1 = pd.read_csv('data/2019-20/player_idlist.csv') 

merged = df.merge(df1, on=['id'])
merged.drop('first_name', axis=1, inplace=True)
merged = merged[['team_id', 'gw', 'second_name', 'id', 'position', 'multiplier']]
merged.rename({'id': 'player_id'}, axis=1, inplace=True)
merged=merged.sort_values(by=['team_id', 'gw', 'position'])
merged.to_csv('data/2019-20/managers/top_managers_gwPicks.csv',index=False)