from flask import Flask, render_template, request, jsonify
import pandas as pd
import hopsworks
import os
import json
import math

app = Flask(__name__)

try:
    with open("../hopsworks/hopsworks-api-key.txt", "r") as file:
        os.environ["HOPSWORKS_API_KEY"] = file.read().rstrip()
except:
    print("In production mode")

project = hopsworks.login()
fs = project.get_feature_store()

players = fs.get_feature_group("fpl_predictions")

player_df = players.read()

player_data = player_df.to_json(orient="records")

players = json.loads(player_data)

for player in players:
    if player["predicted_score"] != None:
        player["predicted_score"] = round(player["predicted_score"])

# Create new list
display_players = []

for player in players:
    if not any(
        p["first_name"] == player["first_name"]
        and p["second_name"] == player["second_name"]
        for p in display_players
    ):
        # Get all players with the same first and last name
        all_predictions = [
            p
            for p in players
            if p["first_name"] == player["first_name"]
            and p["second_name"] == player["second_name"]
        ]
        # Select the one with the highest gameweek
        latest_prediction_entry = max(all_predictions, key=lambda x: x["gameweek"])

        # Remove the selected player from the list
        # all_predictions.remove(latest_prediction_entry)

        # Ensure 'latest_predictions' is initialized as an empty list
        # Create a new dictionary to hold the predictions for this player
        latest_predictions = []

        # Add the field gameweek, points, predicted_score to the selected player as a dictionary
        for p in all_predictions:
            if p != latest_prediction_entry:
                latest_predictions.append(
                    {
                        "gameweek": p["gameweek"],
                        "points": p["predicted_score"],
                        "predicted_score": p["points"],
                    }
                )

        # Add the latest_predictions to the selected player
        latest_prediction_entry["latest_predictions"] = latest_predictions

        latest_prediction_entry["prev_value"] /= 10

        latest_prediction_entry["prev_value"] = (
            f"""£{latest_prediction_entry["prev_value"]}m"""
        )

        # Add to new list
        display_players.append(latest_prediction_entry)

# Mock data (replace with actual database query or file read)
sample_players = [
    {
        "first_name": "Harry",
        "second_name": "Kane",
        "position": "Midfielder",
        "team": "Tottenham",
        "total_points": 100,
        "latest_predictions": [
            {"gameweek": 21, "total_points": 18, "predicted_points": 15},
            {"gameweek": 20, "total_points": 12, "predicted_points": 8},
            {"gameweek": 19, "total_points": 9, "predicted_points": 5},
            {"gameweek": 18, "total_points": 5, "predicted_points": 7},
            {"gameweek": 17, "total_points": 11, "predicted_points": 7},
        ],
        "predicted_score": 7,
    },
    {
        "first_name": "Harry2",
        "second_name": "Kane2",
        "position": "Midfielder",
        "team": "Tottenham",
        "total_points": 100,
        "latest_predictions": [
            {"gameweek": 21, "total_points": 10, "predicted_points": 8},
            {"gameweek": 20, "total_points": 5, "predicted_points": 8},
            {"gameweek": 19, "total_points": 13, "predicted_points": 15},
            {"gameweek": 18, "total_points": 5, "predicted_points": 7},
            {"gameweek": 17, "total_points": 14, "predicted_points": 18},
        ],
        "predicted_score": 7,
    },
    {
        "first_name": "Harry3",
        "second_name": "Kane3",
        "position": "Midfielder",
        "team": "Tottenham",
        "total_points": 100,
        "latest_predictions": [
            {"gameweek": 21, "total_points": 14, "predicted_points": 11},
            {"gameweek": 20, "total_points": 8, "predicted_points": 4},
            {"gameweek": 19, "total_points": 11, "predicted_points": 7},
            {"gameweek": 18, "total_points": 6, "predicted_points": 8},
            {"gameweek": 17, "total_points": 12, "predicted_points": 9},
        ],
        "predicted_score": 7,
    },
    {
        "first_name": "Harry4",
        "second_name": "Kane4",
        "position": "Midfielder",
        "team": "Tottenham",
        "total_points": 100,
        "latest_predictions": [
            {"gameweek": 21, "total_points": 10, "predicted_points": 8},
            {"gameweek": 20, "total_points": 7, "predicted_points": 6},
            {"gameweek": 19, "total_points": 13, "predicted_points": 10},
            {"gameweek": 18, "total_points": 5, "predicted_points": 4},
            {"gameweek": 17, "total_points": 11, "predicted_points": 9},
        ],
        "predicted_score": 7,
    },
    {
        "first_name": "Harry5",
        "second_name": "Kane5",
        "position": "Midfielder",
        "team": "Tottenham",
        "total_points": 100,
        "latest_predictions": [
            {"gameweek": 21, "total_points": 10, "predicted_points": 8},
            {"gameweek": 20, "total_points": 7, "predicted_points": 6},
            {"gameweek": 19, "total_points": 13, "predicted_points": 10},
            {"gameweek": 18, "total_points": 5, "predicted_points": 4},
            {"gameweek": 17, "total_points": 11, "predicted_points": 9},
        ],
        "predicted_score": 7,
    },
]

# Format the latest_predictions for each player
for player in sample_players:
    player["latest_predictions_str"] = ", ".join(
        [
            f"GW{pred['gameweek']}: {pred['total_points']} pts (Pred: {pred['predicted_points']} pts)"
            for pred in player["latest_predictions"]
        ]
    )


@app.route("/test")
def test():
    # Create new list
    display_players = []

    for player in players:
        if not any(
            p["first_name"] == player["first_name"]
            and p["second_name"] == player["second_name"]
            for p in display_players
        ):
            # Get all players with the same first and last name
            all_predictions = [
                p
                for p in players
                if p["first_name"] == player["first_name"]
                and p["second_name"] == player["second_name"]
            ]
            # Select the one with the highest gameweek
            latest_prediction_entry = max(all_predictions, key=lambda x: x["gameweek"])

            # Remove the selected player from the list
            # all_predictions.remove(latest_prediction_entry)

            # Ensure 'latest_predictions' is initialized as an empty list
            # Create a new dictionary to hold the predictions for this player
            latest_predictions = []

            # Add the field gameweek, points, predicted_score to the selected player as a dictionary
            for p in all_predictions:
                if p != latest_prediction_entry:
                    latest_predictions.append(
                        {
                            "gameweek": p["gameweek"],
                            "points": p["points"],
                            "predicted_score": p["predicted_score"],
                        }
                    )

            # Add the latest_predictions to the selected player
            latest_prediction_entry["latest_predictions"] = latest_predictions

            # Add to new list
            display_players.append(latest_prediction_entry)

    return display_players


@app.route("/")
def index():
    """Render the main page."""
    return render_template("players.html", players=display_players, current_gameweek=20)


@app.route("/api/players", methods=["POST", "GET"])
def get_players():
    """API endpoint to fetch players with all 5 gameweeks, filtering by player name and position if provided."""
    player_name = request.form.get(
        "player", ""
    ).lower()  # Get search query for player name
    position = request.form.get("position", "").upper()  # Get search query for position

    # Filter players based on search term in firstname, lastname or position
    filtered_players = [
        player
        for player in sample_players
        if (
            player_name in player["first_name"].lower()
            or player_name in player["second_name"].lower()
        )
        and (not position or position == player["position"])
    ]

    # If no search filter is provided, show all players by default
    if not player_name and not position:
        filtered_players = sample_players

    # Generate the HTML table rows for filtered players
    player_rows = ""
    for player in filtered_players:
        player_rows += f"""
        <tr>
            <td>{player['first_name']} {player['second_name']}</td>
            <td>{player['position']}</td>
            <td>{player['club']}</td>
            <td>{player['points']}</td>
            <td>
                <table class="inner-table">
                    <tr>
                        <th>Gameweek</th>
                        <th>Points</th>
                        <th>Predicted Points</th>
                    </tr>
        """
        # for gw in player["5latestGws"]:
        #     player_rows += f"""
        #     <tr>
        #         <td>{gw['gameweek']}</td>
        #         <td>{gw['total_points']}</td>
        #         <td>{gw['predicted_points']}</td>
        #     </tr>
        #     """
        player_rows += f"""</table></td>
        <td>{player["nextGwPrediction"]}</td</tr>"""

    return player_rows


if __name__ == "__main__":
    app.run(debug=True)