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managers.py
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from urllib import response
import requests , json, csv
import pandas as pd
import os
import numpy as np
from decouple import config
import plotly.graph_objs as go
import chart_studio
import chart_studio.plotly as pys
def get_top_picks_df(base_path: str, season: str, overallLeagueID: int, top_n: int, curr_gw: int):
players_ids_df = pd.read_csv(base_path + 'data/' + season + '/player_idlist.csv')
players_ids_df.rename({'id': 'player_id'}, axis=1, inplace=True)
players_ids_df['full_name'] = players_ids_df['first_name'] + ' ' + players_ids_df['second_name']
players_ids_df.drop('first_name', axis=1, inplace=True)
players_ids_df.drop('second_name', axis=1, inplace=True)
players_stats_df = pd.read_csv(base_path + 'data/' + season + '/cleaned_players.csv')
players_stats_df['full_name'] = players_stats_df['first_name'] + ' ' + players_stats_df['second_name']
players_stats_df.drop('first_name', axis=1, inplace=True)
players_stats_df.drop('second_name', axis=1, inplace=True)
players_df = players_ids_df.merge(players_stats_df, on=['full_name'])
picks_df = top_managers_gw_picks_df(overallLeagueID=overallLeagueID, top_n=top_n, curr_gw=curr_gw)
merged = picks_df.merge(players_df, on=['player_id'])
merged=merged.sort_values(by=['team_id', 'gw', 'position'])
return merged
def top_managers_gw_picks_df(overallLeagueID: int, top_n: int, curr_gw: int):
count = 0
picks = []
for manager in get_top_managers_from_api(overallLeagueID):
if count >= top_n:
break
count +=1
teamID = manager['entry']
cols = ['team_id','gw','player_id','position','multiplier']
parsed = get_gw_picks_from_api(teamID=teamID, gw=curr_gw)
for i in range(len(parsed['picks'])):
try:
currPicks = {
'team_id':teamID,
'gw':curr_gw,
'player_id':parsed['picks'][i]['element'],
'position':parsed['picks'][i]['position'],
'multiplier':parsed['picks'][i]['multiplier']
}
picks.append(currPicks)
except:
continue
return pd.DataFrame(picks, columns = cols)
def top_managers_gw_infos_df(overallLeagueID: int, top_n: int, curr_gw: int):
count = 0
infos = []
for manager in get_top_managers_from_api(overallLeagueID):
if count >= top_n:
break
count +=1
teamID = manager['entry']
cols = ['team_id','gw','points','bench','gw_rank','transfers','hits','total_points','overall_rank','team_value','chip']
for gw in range(1,curr_gw):
parsed = get_gw_picks_from_api(teamID=teamID, gw=gw)
try:
currInfo = {
'team_id':teamID,
'gw':gw,
'points':parsed['entry_history']['points'],
'bench':parsed['entry_history']['points_on_bench'],
'gw_rank':parsed['entry_history']['rank'],
'transfers':parsed['entry_history']['event_transfers'],
'hits':parsed['entry_history']['event_transfers_cost'],
'total_points':parsed['entry_history']['total_points'],
'overall_rank':parsed['entry_history']['overall_rank'],
'team_value':int(parsed['entry_history']['value'])/10,
'chip':parsed['active_chip']
}
infos.append(currInfo)
except:
continue
return pd.DataFrame(infos, columns = cols)
def top_managers_df(overallLeagueID: int, top_n: int):
ids = []
managers = []
cols = ['rank','entry','player_name','entry_name','total']
count = 0
for manager in get_top_managers_from_api(overallLeagueID):
if count >= top_n:
break
count +=1
currManager = {
'rank': manager['rank'],
'entry': manager['entry'],
'player_name': manager['player_name'],
'entry_name': manager['entry_name'],
'total': manager['total']}
managers.append(currManager)
ids.append(manager['entry'])
return pd.DataFrame(managers, index=ids, columns = cols)
def get_top_managers_from_api(overallLeagueID: int):
url = "https://fantasy.premierleague.com/api/leagues-classic/"+str(overallLeagueID)+"/standings/"
response = requests.get(url)
data = response.text
parsed = json.loads(data)
return parsed['standings']['results']
def get_gw_picks_from_api(teamID: int, gw: int):
url = "https://fantasy.premierleague.com/api/entry/"+str(teamID)+"/event/"+str(gw)+"/picks/"
response = requests.get(url)
data = response.text
return json.loads(data)
def plot_df(df):
goalkeepers = df[(df['element_type']=='GK')]
defenders = df[(df['element_type']=='DEF')]
midfielders = df[(df['element_type']=='MID')]
forwards = df[(df['element_type']=='FWD')]
trace_gkp = get_trace(goalkeepers,'Goalkeeper')
trace_def = get_trace(defenders,'Defender')
trace_mid = get_trace(midfielders,'Midfielder')
trace_fwd = get_trace(forwards,'Forward')
data = [trace_gkp,trace_def,trace_mid,trace_fwd]
updatemenus = list([
dict(active=0,
pad = {'r': 0, 't': 10},
x = 0,
y = 1.18,
type = 'buttons',
font=dict(color='#404040'),
bgcolor = 'rgba(255,255,255,100)',
direction = 'right',
xanchor = 'left',
buttons=list([
dict(label = 'All',
method = 'update',
args = [{'visible': [True, True, True, True]}]),
dict(label = 'Goalkeepers',
method = 'update',
args = [{'visible': [True, False, False, False]}]),
dict(label = 'Defenders',
method = 'update',
args = [{'visible': [False, True, False, False]}]),
dict(label = 'Midfielders',
method = 'update',
args = [{'visible': [False, False, True, False]}]),
dict(label = 'Forwards',
method = 'update',
args = [{'visible': [False, False, False, True]}])
]),
)
])
layout = go.Layout(
modebar={'bgcolor': 'rgba(0,0,0,0)'},
hovermode = 'closest',
showlegend=False,
updatemenus=updatemenus,
paper_bgcolor='rgba(0,0,0,0)',
plot_bgcolor='rgba(0,0,0,0)',
xaxis=go.layout.XAxis(
showgrid=True,
zeroline=False,
color='rgba(255,255,255,1)',
showticklabels=False,
title=go.layout.xaxis.Title(
text='Picked by',
font=dict(
size=18,
color='white'
)
)
),
yaxis=go.layout.YAxis(
showgrid=True,
zeroline=False,
color='rgba(255,255,255,10)',
showticklabels=False,
title=go.layout.yaxis.Title(
text='Total points',
font=dict(
size=18,
color='white'
)
)
)
)
fig = go.Figure(data=data, layout=layout)
return fig
def get_trace(df, position):
return go.Scatter(
x = df['picked_by_percent'],
y = df['total_points'],
name= (position+'s'),
text = df['full_name'] + ' (£' + (df['now_cost']/10).map(str) + ')',
mode = 'markers',
marker=dict(color = map_position_to_color(position),
size = 1/df['now_cost'],
sizeref = 0.00003,
sizemode = 'area'),
hoverlabel= dict(
font=dict(color='#404040'),
bordercolor='#404040',
bgcolor='white'
),
hovertemplate = "<b>%{text}</b><br><br>" +
"Total points: %{y:f}</br>"+
"Picked by: %{x:.2f}%</br>"+
"<extra></extra>")
def map_position_to_color(position):
if position == 'Goalkeeper':
return 'rgba(0,53,166, 0.8)'
elif position == 'Defender':
return 'rgba(101,255,71, 0.8)'
elif position == 'Midfielder':
return 'rgba(254,213,0, 0.8)'
else:
return 'rgba(236,0,0, 0.8)'
def main():
print('Fetching curr gameweek...')
URL = "https://fantasy.premierleague.com/api/bootstrap-static/"
DATA = requests.get(URL).json()
CURR_GW_OBJS = [x for x in DATA['events'] if x['is_current'] == True]
if len(CURR_GW_OBJS) == 0:
CURR_GW_OBJS = DATA['events']
CURR_GW = CURR_GW_OBJS[-1]['id']
# Overall FPL league ID is 314
OVERALL_LEAGUE_ID = 314
TOP_N = 25
BASE_PATH = './scraper/'
SEASON = '2022-23'
CHARTS_USER = config('CHARTS_USER')
CHARTS_API_KEY = config('CHARTS_API_KEY')
chart_studio.tools.set_credentials_file(username=CHARTS_USER, api_key=CHARTS_API_KEY)
print('Fetching top picks...')
df = get_top_picks_df(base_path=BASE_PATH, season=SEASON, overallLeagueID=OVERALL_LEAGUE_ID, top_n=TOP_N, curr_gw=CURR_GW)
df['picked_by'] = df['player_id'].apply(lambda x: (df['player_id'] == x).sum())
df = df[['element_type','player_id','full_name','picked_by','total_points','now_cost','multiplier']]
df = df.drop_duplicates(subset='player_id', keep="last")
df['picked_by_percent'] = df['picked_by']*100/TOP_N
df = df[df.picked_by_percent >= 5]
df.sort_values(by="picked_by_percent", ascending=False, inplace=False)
print(df)
print('Generating plot...')
fig = plot_df(df)
chart_studio.plotly.plot(fig,filename="top-picked")
if __name__ == '__main__':
main()