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main.py

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+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)

model.py

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+from sklearn.model_selection import RandomizedSearchCV
+from sklearn.ensemble import RandomForestClassifier
+import pandas as pd
+import pickle
+
+def create_model():
+    train_data = pd.read_csv("data.csv")
+
+    features = ["Tournament", "Team A", "Team B", "Map", "TA Agents", "TB Agents"]
+
+    x = pd.get_dummies(train_data[features])
+    y = train_data["Result"]
+
+    print("Train data created...")
+
+    param_dist = {
+        'n_estimators': [i for i in range(1, 501)],
+        'max_depth': [i for i in range(1, 21)]
+    }
+
+    rf = RandomForestClassifier()
+
+    rand_search = RandomizedSearchCV(rf, param_distributions=param_dist, n_iter=5, cv=5)
+
+    rand_search.fit(x, y)
+
+    best_rf = rand_search.best_estimator_
+
+    print("Optimizations and training of the model finished...")
+
+    filename = "model.sav"
+    pickle.dump(best_rf, open(filename, "wb"))
+
+    print("Model saved !")

templates/home.html

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+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <title>Home</title>
+
+    <link href="https://seeklogo.com/images/V/valorant-logo-3D72D9117F-seeklogo.com.png" rel="icon"/>
+
+    <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/uikit@3.20.8/dist/css/uikit.min.css" />
+
+    <script src="https://cdn.jsdelivr.net/npm/uikit@3.20.8/dist/js/uikit.min.js"></script>
+    <script src="https://cdn.jsdelivr.net/npm/uikit@3.20.8/dist/js/uikit-icons.min.js"></script>
+</head>
+<body>
+    <div class="uk-container uk-align-center uk-flex uk-flex-center uk-flex-middle" uk-height-viewport="expand: true">
+        <div>
+            <h1 class="uk-text-center">VCT Map Predictor</h1>
+            <form action="{{url_for('prediction')}}" method="POST">
+                <label>Tournament</label>
+                <select id="tournament" name="tournament" class="uk-select uk-margin-bottom" aria-label="Select">
+                    <option value="">Please select tournament...</option>
+                    {% for tournament in tournaments %}
+                    <option>{{tournament}}</option>
+                    {% endfor %}
+                </select>
+                <br>
+                <label>Map</label>
+                <select id="map" name="map" class="uk-select uk-margin-bottom" aria-label="Select">
+                    <option value="">Please select map...</option>
+                    {% for map in maps %}
+                    <option>{{map}}</option>
+                    {% endfor %}
+                </select>
+                <br>
+                <label>Team A</label>
+                <select id="team_a" name="team_a" class="uk-select uk-margin-bottom" aria-label="Select">
+                    <option value="">Please select team A...</option>
+                    {% for team_a in team_A %}
+                    <option>{{team_a}}</option>
+                    {% endfor %}
+                </select>
+                <br>
+                <label>Team B</label>
+                <select id="team_b" name="team_b" class="uk-select uk-margin-bottom" aria-label="Select">
+                    <option value="">Please select team B...</option>
+                    {% for team_b in team_B %}
+                    <option>{{team_b}}</option>
+                    {% endfor %}
+                </select>
+                <label>Team A agents</label>
+                <input class="uk-input" type="text" id="ta_agents" name="ta_agents" placeholder="Agents1 Agents2 Agents3 Agents4 Agents5" aria-label="Input">
+                <label>Team B agents</label>
+                <input class="uk-input" type="text" id="tb_agents" name="tb_agents" placeholder="Agents1 Agents2 Agents3 Agents4 Agents5" aria-label="Input">
+                <button class="uk-button uk-button-default  uk-margin-top uk-align-center" type="submit">Predict map</button>
+            </form>
+            <div class="uk-flex uk-flex-center">
+                <a class="uk-margin-right" href="{{url_for('loading_train_model')}}">Train model</a> | <a class="uk-margin-left" href="{{url_for('loading_update_data')}}">Update data</a>
+            </div>
+        </div>
+    </div>
+</body>
+</html>

templates/loading.html

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+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <title>Loading...</title>
+
+    <link href="https://seeklogo.com/images/V/valorant-logo-3D72D9117F-seeklogo.com.png" rel="icon"/>
+
+    <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/uikit@3.20.8/dist/css/uikit.min.css" />
+
+    <script src="https://cdn.jsdelivr.net/npm/uikit@3.20.8/dist/js/uikit.min.js"></script>
+    <script src="https://cdn.jsdelivr.net/npm/uikit@3.20.8/dist/js/uikit-icons.min.js"></script>
+</head>
+<body>
+    <div class="uk-container uk-align-center uk-flex uk-flex-center uk-flex-middle" uk-height-viewport="expand: true">
+        <div>
+            <img src="/static/gif jett.gif">
+            <p>by u/quelm_nossfe</p>
+            <h1 class="uk-text-center">{{loading_mission}}</h1>
+        </div>
+    </div>
+</body>
+{% if next_page == "train_model" %}
+<script> window.location.replace('{{url_for("train_model")}}'); </script>
+{% elif next_page == "update_data" %}
+<script> window.location.replace('{{url_for("update_data")}}'); </script>
+{% endif %}
+</html>

templates/result.html

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+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <title>Result</title>
+
+    <link href="https://seeklogo.com/images/V/valorant-logo-3D72D9117F-seeklogo.com.png" rel="icon"/>
+
+    <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/uikit@3.20.8/dist/css/uikit.min.css" />
+
+    <script src="https://cdn.jsdelivr.net/npm/uikit@3.20.8/dist/js/uikit.min.js"></script>
+    <script src="https://cdn.jsdelivr.net/npm/uikit@3.20.8/dist/js/uikit-icons.min.js"></script>
+</head>
+<body>
+    <div class="uk-container uk-align-center uk-flex uk-flex-center uk-flex-middle" uk-height-viewport="expand: true">
+        <div>
+            <h1 class="uk-text-center">Result</h1>
+            <h2 class="uk-text-center uk-text-medium">{{prediction}}</h2>
+            <div class="uk-flex uk-flex-center">
+                <a class="uk-margin-right" href="{{url_for('home')}}">Home</a>
+            </div>
+        </div>
+    </div>
+</body>
+</html>
+</html>

vct_data.py

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+from bs4 import BeautifulSoup
+import pandas as pd
+import requests
+
+headers = {
+    'User-Agent': 'Mozilla/5.0 (X11; Ubuntu; Linux x86_64; rv:35.0) Gecko/20100101 Firefox/35.0',
+}
+
+def get_html_document(url):
+    response = requests.get(url, headers=headers)
+
+    return response.text
+
+def create_data():
+    url = "https://www.vlr.gg/"
+
+    html_document_events = get_html_document(url + "events")
+
+    soup_events = BeautifulSoup(html_document_events, 'html.parser')
+
+    events_html = soup_events.find_all("a", {"class": "wf-card mod-flex event-item"})
+
+    data = {"Tournament": [], "Match ID": [], "Team A": [], "Team B": [], "Map ID": [], "Map": [], "TA Agents": [], "TB Agents": [], "Result": []}
+
+    events_id = []
+    events_name = []
+    for event_html in events_html:
+        event_id = ""
+
+        i = 0
+        for character in event_html["href"]:
+            if i > 6 and i < 11:
+                event_id += character
+                i += 1
+            else:
+                i += 1
+
+        event_name = event_html.find_all("div", {"class": "event-item-title"})[0].text.strip()
+
+        print("Tournament : " + event_name)
+
+        if "Champions Tour 2024" not in event_name:
+            continue
+
+        events_id.append(event_id)
+        events_name.append(event_name)
+
+        html_document_matches = get_html_document(url + f"event/matches/{event_id}")
+
+        soup_matches = BeautifulSoup(html_document_matches, 'html.parser')
+
+        matches_html = soup_matches.find_all("a", {"class": "wf-module-item match-item mod-color mod-left mod-bg-after-striped_purple mod-first"}) + soup_matches.find_all("a", {"class": "wf-module-item match-item mod-color mod-left mod-bg-after-striped_purple"})
+
+        matches_id = []
+        for match_html in matches_html:
+            match_id = ""
+
+            i = 0
+            for character in match_html["href"]:
+                if i > 0 and i < 7:
+                    match_id += character
+                    i += 1
+                else:
+                    i += 1
+
+            matches_id.append(match_id)
+
+            print("Match ID : " + match_id)
+
+            html_document_match = get_html_document(url + match_id)
+
+            soup_match = BeautifulSoup(html_document_match, 'html.parser')
+
+            match_header_vs = soup_match.find_all("div", {"class": "match-header-vs"})
+
+            team_a_split = match_header_vs[0].find_all("div", {"class": "match-header-link-name mod-1"})[0].find_all("div", {"class": "wf-title-med"})[0].text.split()
+            team_a = ""
+            for a in team_a_split:
+                team_a = team_a + a + " "
+
+            print("Team A : " + team_a)
+
+            team_b_split = match_header_vs[0].find_all("div", {"class": "match-header-link-name mod-2"})[0].find_all("div", {"class": "wf-title-med"})[0].text.split()
+            team_b = ""
+            for b in team_b_split:
+                team_b = team_b + b + " "
+
+            print("Team B : " + team_b)
+
+            if team_a == "TBD" or team_b == "TBD":
+                print("not finished")
+            else:
+                maps_html = soup_match.find_all("div",  {"class": "vm-stats-gamesnav-item js-map-switch"})
+
+                maps_id = []
+                for map_html in maps_html:
+                    map_id = map_html["data-game-id"]
+
+                    print("Map ID : " + map_id)
+
+                    maps_id.append(map_id)
+
+                    html_document_map = get_html_document(url + match_id + "/?game=" + map_id)
+
+                    soup_map = BeautifulSoup(html_document_map, 'html.parser')
+
+                    vm_stats_game = soup_map.find_all("div", {"class": "vm-stats-game mod-active"})
+
+                    map_html = vm_stats_game[0].find_all("div", {"class": "map"})
+
+                    map_text = map_html[0].find_all("span", {"style": "position: relative;"})[0].text.split()
+
+                    map = map_text[0]
+
+                    print("Map : " + map)
+
+                    agents_html = vm_stats_game[0].find_all("span", {"class": "stats-sq mod-agent small"})
+
+                    i = 0
+                    ta_agents = []
+                    tb_agents = []
+                    for agent_html in agents_html:
+                        if i <= 4:
+                            agent = agent_html.find_all("img")[0]["title"]
+                            ta_agents.append(agent)
+                            i += 1
+                        else:
+                            agent = agent_html.find_all("img")[0]["title"]
+                            tb_agents.append(agent)
+                            i += 1
+
+                    ta_agents = sorted(ta_agents)
+                    tb_agents = sorted(tb_agents)
+
+                    print("TA Agents : ", ta_agents)
+                    print("TB Agents : ", tb_agents)
+
+                    if ta_agents == [] or tb_agents == []:
+                        print("not finished")
+                        pass
+                    else:
+                        is_winner = vm_stats_game[0].find_all("div", {"class": "team"})[0].find_all("div", {"class": "score mod-win"})
+
+                        if is_winner == []:
+                            result = "Team B win"
+                        else:
+                            result = "Team A win"
+
+                        data["Tournament"].append(event_name)
+                        data["Match ID"].append(match_id)
+                        data["Team A"].append(team_a)
+                        data["Team B"].append(team_b)
+                        data["Map ID"].append(map_id)
+                        data["Map"].append(map)
+                        data["TA Agents"].append(ta_agents)
+                        data["TB Agents"].append(tb_agents)
+                        data["Result"].append(result)
+
+                        print("All data of the map : ", data)
+
+    df = pd.DataFrame(data=data)
+
+    df.to_csv("data.csv", sep=",", index=False, encoding="utf-8")
+
+    print(".csv file downloaded...")