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app.py

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+import gradio as gr
+import cfbd
+import numpy as np
+import pandas as pd
+from fastai.tabular import *
+from fastai.tabular.all import *
+
+configuration = cfbd.Configuration()
+configuration.api_key["Authorization"] = "be81N7cB5mpl4z+BdHBuD5wUACNkh5YSAhO8uaC3tKCRAgC9WMhJjoHrO3Qx3TFp"
+configuration.api_key_prefix["Authorization"] = "Bearer"
+api_config = cfbd.ApiClient(configuration)
+teams_api = cfbd.TeamsApi(api_config)
+ratings_api = cfbd.RatingsApi(api_config)
+games_api = cfbd.GamesApi(api_config)
+betting_api = cfbd.BettingApi(api_config)
+
+
+def predict(game_details):
+    learn = load_learner("cfb-prediction.pkl")
+
+    pdf = pd.DataFrame([game_details])
+    dl = learn.dls.test_dl(pdf)
+    pdf["predicted"] = learn.get_preds(dl=dl)[0].numpy()
+    pdf['margin'] = abs(game_details['home_points'] - game_details['away_points'])
+    
+    return pdf[['home_team','away_team','home_points','away_points','spread','margin','predicted']]
+
+
+# def home_team_change(x):
+#     ratings = ratings_api.get_elo_ratings(team=x, year=2023)
+#     team_detail = ratings[0]
+#     return "Conference: " + team_detail.conference + ", ELO Rating: " + str(team_detail.elo)
+
+
+def home_team_change(team, year):
+    games = games_api.get_games(team=team, year=year)
+    names = []
+    for game in games:
+        if game.home_team == team:
+            names.append(game.away_team)
+        else:
+            names.append(game.home_team)
+
+    return gr.update(choices=names, value=None)
+
+
+def get_game_details(year, target, opponent):
+    games = games_api.get_games(team=target, year=year)
+    the_game = null
+
+    for game in games:
+        if game.home_team == opponent or game.away_team == opponent:
+            the_game = dict(
+                id=game.id,
+                year=game.season,
+                week=game.week,
+                neutral_site=game.neutral_site,
+                home_team=game.home_team,
+                home_conference=game.home_conference,
+                home_points=game.home_points,
+                home_elo=game.home_pregame_elo,
+                away_team=game.away_team,
+                away_conference=game.away_conference,
+                away_points=game.away_points,
+                away_elo=game.away_pregame_elo,
+            )
+            break
+            
+    spread = betting_api.get_lines(game_id=the_game['id'],year=year)
+
+    the_game['spread'] = spread[0].lines[0].spread
+
+    return the_game
+
+def lookup_teams(teams_api):
+    team_names = []
+    teams = teams_api.get_fbs_teams()
+    for team in teams:
+        team_names.append(team.school)
+
+    return team_names
+
+
+def update_target(x):
+    print(x)
+
+
+teams = lookup_teams(teams_api)
+
+with gr.Blocks() as app:
+    with gr.Row():
+        with gr.Column(scale=1):
+            yearDd = gr.Dropdown(
+                [2023, 2022, 2021, 2020, 2019, 2018, 2017], label="Year"
+            )
+    with gr.Row():
+        with gr.Column(scale=1):
+            ddTeams1 = gr.Dropdown(choices=teams, label="Target Team")
+        with gr.Column(scale=1):
+            oponents = gr.Dropdown(choices=[], label="Opponents", interactive=True)
+    #     with gr.Column(scale=1):
+    #         ddTeams2 = gr.Dropdown(choices=teams, label="Away Team")
+    #         label2 = (gr.Label(num_top_classes=4, label="Away Team Details"))
+    #         ddTeams2.select(home_team_change, inputs=ddTeams2, outputs=[label2])
+    with gr.Row():
+            game_details = gr.JSON({})
+    with gr.Row():
+        submit = gr.Button("Predict")
+    with gr.Row():
+        data_table = gr.Dataframe(
+            headers=["Home Team", "Away Team", "Home Points", "Away Points", "Consensus Spread", "Margin", "Predicted Spread"],
+            datatype=["str", "str", "number", "number", "number", "number", "number"],
+            row_count=1,
+            col_count=(7, "dynamic")
+        )
+
+    ddTeams1.select(home_team_change, inputs=[ddTeams1, yearDd], outputs=[oponents])
+    oponents.select(
+        get_game_details,
+        inputs=[yearDd, ddTeams1, oponents],
+        outputs=[game_details]
+    )
+    submit.click(
+        predict, inputs=[game_details], outputs=[data_table]
+    )
+app.launch()
+
+
+# import gradio as gr
+
+# languages = ['spanish', 'english']
+# homeworks = {'spanish': ['hola', 'bien', 'gracias'], 'english': ['hello', 'good', 'thank you']}
+
+# def rs_change(rs):
+#     return gr.update(choices=homeworks[rs], value=None)
+
+# with gr.Blocks() as app:
+
+#     rs = gr.Dropdown(choices=languages, value='english')
+#     rs_hw = gr.Dropdown(choices=homeworks['english'], interactive=True)
+
+#     rs.change(fn=rs_change, inputs=[rs], outputs=[rs_hw])
+
+# app.launch()

cfb-prediction.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:5a6f950de0b7a1cddd6a7dcd30e469b1a107730f1780b7733597c51c0d08d9f8
+size 136375

requirements.txt

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+cfbd
+fastai
+pandas