import pandas as pd
import flask
from flask import request, jsonify

app = flask.Flask(__name__)
app.config["DEBUG"] = True

@app.route('/analyze', methods=['POST'])
def analyze_csv():
    try:
        # Read CSV data from the POST request
        csv_data = request.data.decode('utf-8')

        # Write the CSV data to a file (optional, for debugging)
        with open('received_data.csv', 'w') as file:
            file.write(csv_data)

        # Load the CSV data into a DataFrame
        from io import StringIO
        data = StringIO(csv_data)
        df = pd.read_csv(data)

        # Ensure the CSV has the correct columns
        required_columns = ['date', 'prev_high', 'prev_low', 'prev_open', 'prev_close', 'prev_volume']
        for column in required_columns:
            if column not in df.columns:
                return jsonify({"error": f"Missing column: {column}"}), 400

        # Print the received metrics for debugging
        print("Received metrics:")
        print(df)

        # Perform analysis (Example: Calculate average price and volume)
        df['average_price'] = (df['prev_high'] + df['prev_low'] + df['prev_open'] + df['prev_close']) / 4
        average_price = df['average_price'].mean()  # Average of all the average prices
        average_volume = df['prev_volume'].mean()  # Average volume

        # Print the computed averages
        print(f"Average Price: {average_price}")
        print(f"Average Volume: {average_volume}")

        # Create a trading signal based on a simple rule
        last_close = df['prev_close'].iloc[-1]
        if last_close > average_price:
            signal = "BUY"
            signal_explanation = f"The last close price ({last_close}) is higher than the average price ({average_price})."
        else:
            signal = "SELL"
            signal_explanation = f"The last close price ({last_close}) is lower than the average price ({average_price})."

        # Print the signal and explanation
        print(f"Generated Signal: {signal}")
        print(f"Signal Explanation: {signal_explanation}")

        # Return the signal as JSON
        return jsonify({
            "signal": signal,
            "average_price": average_price,
            "average_volume": average_volume,
            "signal_explanation": signal_explanation
        })

    except Exception as e:
        return jsonify({"error": str(e)}), 500

if __name__ == '__main__':
    app.run(host='189.7.6.8', port=5877)