/
tab1.py
executable file
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tab1.py
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import os
from random import randint
import plotly.plotly as py
from plotly.graph_objs import *
import dash
import dash_table
from dash.dependencies import Input, Output, State, Event
import dash_core_components as dcc
import dash_html_components as html
import plotly.graph_objs as go
import pandas as pd
from app import app, conn
from datetime import datetime
import elo_score
def tab1(init_player_df, elo_score_df, player_dict):
tab = html.Div(children=[
html.H1(children="Dart-Tally-Awesome",
style={'textAlign' : 'center'}),
html.Div(
style={'padding' : '40px',
'margin' : '20px',
'border-style' : 'solid',
'border-radius' : "10",
'border-width' : '1px',
'border-color' : 'gray',
'textAlign' : "center",
'box-shadow' : "5px 5px 6px grey",
'background-color' : '#d9d9d9'},
children=[
html.Div([html.Div("Player 1"),
dcc.Dropdown(options=[{'label' : i['player_name'],
'value' : i['player_id']}
for i in init_player_df.to_dict("rows")],
id="player_1_dropdown",
style={"textAlign" : "center",
'box-shadow' : "2px 2px 6px grey"}
),
html.Div("Player 1 Score"),
html.Div(dcc.Input(id='player_1_score',
value='',
type='number',
style={"textAlign" : "center",
"width" : "100px",
'box-shadow' : "2px 2px 6px grey",
}))],
className="four columns",
style={'textAlign' : 'center'}),
html.H3("-VS-",
className="four columns"),
html.Div([html.Div("Player 2"),
dcc.Dropdown(options=[{'label' : i['player_name'],
'value' : i['player_id']}
for i in init_player_df.to_dict("rows")],
id="player_2_dropdown",
style={"textAlign" : "center",
'box-shadow' : "2px 2px 6px grey"}
),
html.Div("Player 2 Score"),
html.Div(dcc.Input(id='player_2_score',
value='',
type='number',
style={"textAlign" : "center",
"width" : "100px",
'box-shadow' : "2px 2px 6px grey"}))],
className="four columns",
style={'textAlign' : 'center'}),
html.Button("Add Score",
id="add_score_button",
style={"textAlign" : 'center',
'box-shadow' : "2px 2px 6px grey",
"background-color" : "white"}
)],
className="row"),
dcc.Graph(id='timeseries',
config={'displayModeBar': False},
figure=go.Figure(
data = [go.Scatter(x=elo_score_df.index,
y=elo_score_df[i],
name=player_dict[i]['player_name'])
for i in list(elo_score_df)],
layout = go.Layout(hovermode='closest'))
),
html.Div(children=[
html.H3("The Elo Rating System"),
html.P("This web app is uses the Elo Rating System to rate players through time."\
" The previous rankings of the two players, and the outcome of the game all"\
" contribute to the new scores of each player. The Elo Rating System was"\
" originally divised by Arpad Elo for rating chess players. It has since"\
" been used for all sorts of zero-sum games. For more about this, head over"\
" to the Wikipedia Article:"),
html.A("The Elo Rating System - Wikipedia.org",
href="https://en.wikipedia.org/wiki/Elo_rating_system")
],
style={'padding' : '40px',
'margin' : '20px',
'border-style' : 'solid',
'border-radius' : "10",
'border-width' : '1px',
'border-color' : 'gray',
'textAlign' : "left",
'box-shadow' : "5px 5px 6px grey",
'background-color' : '#d9d9d9'},
)
])
return(tab)
@app.callback(
Output(component_id='timeseries', component_property='figure'),
[Input('add_score_button', 'n_clicks_timestamp')],
[State('player_1_dropdown', 'value'),
State('player_2_dropdown', 'value'),
State('player_1_score', 'value'),
State('player_2_score', 'value')])
def update_games(timestamp, p1_id, p2_id, p1_score, p2_score):
df = pd.read_sql(sql='SELECT * FROM game_log;', con=conn, parse_dates=['created_at'])
try:
p1_id = int(p1_id)
p2_id = int(p2_id)
p1_score = int(p1_score)
p2_score = int(p2_score)
except TypeError:
pass
else:
if p1_score >= p2_score:
winner_id = p1_id
winner_score = p1_score
looser_id = p2_id
looser_score=p2_score
else:
winner_id = p2_id
winner_score = p2_score
looser_id = p1_id
looser_score=p1_score
utc_stamp = str(datetime.utcfromtimestamp(int(timestamp / 1000)))
conn.execute("INSERT INTO game_log "\
"(winner_id, winner_score, looser_id, looser_score, created_at) "\
"VALUES({}, {}, {}, {}, '{}');".format(winner_id,
winner_score,
looser_id,
looser_score,
utc_stamp))
finally:
kfactor_list = pd.read_sql(sql='SELECT * FROM kfactor;', con=conn)['value'].tolist()
kfactor = kfactor_list.pop()
init_player_df = pd.read_sql(sql='SELECT * FROM player_ids;',
con=conn)
init_game_log_df = pd.read_sql(sql='SELECT * FROM game_log;',
con=conn,
parse_dates=['created_at'])
elo_score_df = elo_score.make_elo_scores_df(init_game_log_df,
init_player_df,
K=kfactor)
player_dict = init_player_df.set_index("player_id").to_dict('index')
figure = go.Figure(
data = [go.Scatter(x=elo_score_df.index,
y=elo_score_df[i],
name=player_dict[i]['player_name'])
for i in list(elo_score_df)],
layout = go.Layout(hovermode='closest'))
return(figure)