Update main.py

main.py

@@ -1,109 +1,109 @@
-from flask import Flask, render_template, redirect, url_for, request
-from vct_data import create_data
-from model import create_model
-import pandas as pd
-import pickle
-import os
-
-app = Flask(__name__)
-
-@app.route('/')
-def home():
-    if "data.csv" not in os.listdir():
-        return redirect(url_for("loading_update_data"))
-    elif "model.sav" not in os.listdir():
-        return redirect(url_for("loading_train_model"))
-    else:
-        df = pd.read_csv("data.csv")
-
-        tournaments_df = df["Tournament"]
-        tournaments = list(pd.unique(tournaments_df))
-
-        maps_df = df["Map"]
-        maps = list(pd.unique(maps_df))
-
-        team_A_df = df["Team A"]
-        team_A = list(pd.unique(team_A_df))
-
-        team_B_df = df["Team B"]
-        team_B = list(pd.unique(team_B_df))
-
-        agents = ["Astra", "Breach", "Brimstone", "Chamber", "Clove", "Cypher", "Deadlock", "Fade", "Gekko", "Harbor", "Iso", "Jett", "Kayo", "Killjoy", "Neon", "Omen", "Phoenix", "Raze", "Reyna", "Sage", "Skye", "Sova", "Viper", "Yoru"]
-
-        return render_template("home.html", tournaments=tournaments, maps=maps, team_A=team_A, team_B=team_B, agents=agents)
-
-@app.route('/update-data')
-def update_data():
-    create_data()
-    return redirect(url_for("loading_train_model"))
-
-@app.route('/loading-update-data')
-def loading_update_data():
-    return render_template("loading.html", next_page="update_data", loading_mission="Updating data...")
-
-@app.route('/train-model')
-def train_model():
-    create_model()
-    return redirect(url_for("home"))
-
-@app.route('/loading-train-model')
-def loading_train_model():
-    return render_template("loading.html", next_page="train_model", loading_mission="Training model...")
-
-@app.route('/prediction', methods=["post", "get"])
-def prediction():
-    if request.method == "POST":
-        tournament = request.form["tournament"]
-        map = request.form["map"]
-        team_a = request.form["team_a"]
-        team_b = request.form["team_b"]
-        ta_agents_list = sorted(request.form["ta_agents"].split())
-        tb_agents_list = sorted(request.form["tb_agents"].split())
-
-        i = 0
-        ta_agents = "["
-        for agents in ta_agents_list:
-            if i == 4:
-                ta_agents += agents + "]"
-            else:
-                ta_agents += agents + ", "
-
-        i = 0
-        tb_agents = "["
-        for agents in tb_agents_list:
-            if i == 4:
-                tb_agents += agents + "]"
-            else:
-                tb_agents += agents + ", "
-
-        train_data = pd.read_csv("data.csv")
-        model = pickle.load(open("model.sav", 'rb'))
-
-        features = ["Tournament", "Map", "Team A", "Team B", "TA Agents", "TB Agents"]
-
-        x = pd.get_dummies(train_data[features])
-
-        data_test = {"Tournament": [tournament], "Map": [map], "Team A": [team_a], "Team B": [team_b], "TA Agents": [ta_agents], "TB Agents": [tb_agents]}
-        test_data = pd.DataFrame(data=data_test)
-        x_test = pd.get_dummies(test_data[features])
-
-        col_x_test = []
-        for column in x_test:
-            col_x_test.append(column)
-
-        for column in x:
-            if column in col_x_test:
-                pass
-            else:
-                x_test.insert(0, column, [False])
-
-        x_test = x_test.reindex(x.columns, axis=1)
-
-        prediction = model.predict(x_test)[0]
-
-        return render_template("result.html", prediction=prediction)
-    else:
-        return redirect(url_for("home"))
-
-if __name__ == "__main__":
-    app.run(debug=True)
+from flask import Flask, render_template, redirect, url_for, request
+from vct_data import create_data
+from model import create_model
+import pandas as pd
+import pickle
+import os
+
+app = Flask(__name__)
+
+@app.route('/')
+def home():
+    if "data.csv" not in os.listdir():
+        return redirect(url_for("loading_update_data"))
+    elif "model.sav" not in os.listdir():
+        return redirect(url_for("loading_train_model"))
+    else:
+        df = pd.read_csv("data.csv")
+
+        tournaments_df = df["Tournament"]
+        tournaments = list(pd.unique(tournaments_df))
+
+        maps_df = df["Map"]
+        maps = list(pd.unique(maps_df))
+
+        team_A_df = df["Team A"]
+        team_A = list(pd.unique(team_A_df))
+
+        team_B_df = df["Team B"]
+        team_B = list(pd.unique(team_B_df))
+
+        agents = ["Astra", "Breach", "Brimstone", "Chamber", "Clove", "Cypher", "Deadlock", "Fade", "Gekko", "Harbor", "Iso", "Jett", "Kayo", "Killjoy", "Neon", "Omen", "Phoenix", "Raze", "Reyna", "Sage", "Skye", "Sova", "Viper", "Yoru"]
+
+        return render_template("home.html", tournaments=tournaments, maps=maps, team_A=team_A, team_B=team_B, agents=agents)
+
+@app.route('/update-data')
+def update_data():
+    create_data()
+    return redirect(url_for("loading_train_model"))
+
+@app.route('/loading-update-data')
+def loading_update_data():
+    return render_template("loading.html", next_page="update_data", loading_mission="Updating data...")
+
+@app.route('/train-model')
+def train_model():
+    create_model()
+    return redirect(url_for("home"))
+
+@app.route('/loading-train-model')
+def loading_train_model():
+    return render_template("loading.html", next_page="train_model", loading_mission="Training model...")
+
+@app.route('/prediction', methods=["post", "get"])
+def prediction():
+    if request.method == "POST":
+        tournament = request.form["tournament"]
+        map = request.form["map"]
+        team_a = request.form["team_a"]
+        team_b = request.form["team_b"]
+        ta_agents_list = sorted(request.form["ta_agents"].split())
+        tb_agents_list = sorted(request.form["tb_agents"].split())
+
+        i = 0
+        ta_agents = "["
+        for agents in ta_agents_list:
+            if i == 4:
+                ta_agents += agents + "]"
+            else:
+                ta_agents += agents + ", "
+
+        i = 0
+        tb_agents = "["
+        for agents in tb_agents_list:
+            if i == 4:
+                tb_agents += agents + "]"
+            else:
+                tb_agents += agents + ", "
+
+        train_data = pd.read_csv("data.csv")
+        model = pickle.load(open("model.sav", 'rb'))
+
+        features = ["Tournament", "Map", "Team A", "Team B", "TA Agents", "TB Agents"]
+
+        x = pd.get_dummies(train_data[features])
+
+        data_test = {"Tournament": [tournament], "Map": [map], "Team A": [team_a], "Team B": [team_b], "TA Agents": [ta_agents], "TB Agents": [tb_agents]}
+        test_data = pd.DataFrame(data=data_test)
+        x_test = pd.get_dummies(test_data[features])
+
+        col_x_test = []
+        for column in x_test:
+            col_x_test.append(column)
+
+        for column in x:
+            if column in col_x_test:
+                pass
+            else:
+                x_test.insert(0, column, [False])
+
+        x_test = x_test.reindex(x.columns, axis=1)
+
+        prediction = model.predict(x_test)[0]
+
+        return render_template("result.html", prediction=prediction)
+    else:
+        return redirect(url_for("home"))
+
+if __name__ == "__main__":
+    app.run(host="0.0.0.0", port=7860, debug=True)