app.py

from flask import Flask, render_template, request, redirect, url_for, send_file, flash, jsonify
import os
import traceback
from pathlib import Path
import json
import pandas as pd

app = Flask(__name__)
app.secret_key = os.urandom(24)

try:
    import main as project_main
except Exception as e:
    project_main = None
    import_error = traceback.format_exc()
else:
    import_error = None

RESULTS_CSV = Path("results_flask.csv")

def safe_update_dict_from_json(orig_dict, json_text):
    if not json_text or not json_text.strip():
        return orig_dict
    try:
        new = json.loads(json_text)
        if not isinstance(new, dict):
            return orig_dict
        d = orig_dict.copy()
        d.update(new)
        return d
    except Exception:
        return orig_dict

@app.route("/", methods=["GET"])
def index():
    if project_main is None:
        return render_template("index.html", import_error=import_error, project=None)
    techs = list(project_main.TECHNOLOGY_DATA.keys())
    defaults = {
        "inflation": project_main.INFLATION_RATE,
        "tax": project_main.TAX_RATE,
        "years": project_main.PROJECT_YEARS,
        "cap_min": project_main.OPTIMIZATION_SPACE['capacity_kta'][0],
        "cap_max": project_main.OPTIMIZATION_SPACE['capacity_kta'][1],
        "export_mix": project_main.OPTIMIZATION_SPACE['export_market_mix'][0],
        "technology": "Engro_Pakistan",  # FIX: default برای match IRR main.py
    }
    return render_template("index.html", import_error=None, project=project_main, techs=techs, defaults=defaults)

@app.route("/run", methods=["POST"])
def run():
    if project_main is None:
        flash("خطا: فایل main.py بارگزاری نشد. لطفاً لاگ را بررسی کنید.", "danger")
        return redirect(url_for("index"))
    try:
        inflation_rate = float(request.form.get("inflation", project_main.INFLATION_RATE))
        tax_rate = float(request.form.get("tax", project_main.TAX_RATE))
        project_years = int(request.form.get("years", project_main.PROJECT_YEARS))
        capacity_min = float(request.form.get("cap_min", project_main.OPTIMIZATION_SPACE['capacity_kta'][0]))
        capacity_max = float(request.form.get("cap_max", project_main.OPTIMIZATION_SPACE['capacity_kta'][1]))
        technology = request.form.get("technology", "Engro_Pakistan")  # FIX: default Engro
        export_mix = float(request.form.get("export_mix", project_main.OPTIMIZATION_SPACE['export_market_mix'][0]))
        sell_byproducts = request.form.get("sell_byproducts") == "on"
        tech_json = request.form.get("tech_json", "")
        prices_json = request.form.get("prices_json", "")
    except Exception as e:
        flash("خطا در خواندن ورودی‌ها: " + str(e), "danger")
        return redirect(url_for("index"))

    try:
        project_main.INFLATION_RATE = inflation_rate
        project_main.TAX_RATE = tax_rate
        project_main.PROJECT_YEARS = project_years

        project_main.OPTIMIZATION_SPACE['capacity_kta'] = (capacity_min, capacity_max)
        # FIX: هم‌خوانی با main.py (technology پرهزینه، sourcing صریح)
        project_main.OPTIMIZATION_SPACE['technology'] = ["Engro_Pakistan", "Shin_Etsu_2004"] if technology not in ["Engro_Pakistan", "Shin_Etsu_2004"] else [technology]
        project_main.OPTIMIZATION_SPACE['sourcing_strategy'] = ['Integrated_Production']  # FIX: صریح
        project_main.OPTIMIZATION_SPACE['export_market_mix'] = (0.6, 0.8)
        project_main.OPTIMIZATION_SPACE['sell_byproducts'] = [bool(sell_byproducts)]

        project_main.TECHNOLOGY_DATA = safe_update_dict_from_json(project_main.TECHNOLOGY_DATA, tech_json)
        project_main.PRODUCT_PRICES_USD_PER_TON = safe_update_dict_from_json(project_main.PRODUCT_PRICES_USD_PER_TON, prices_json)
    except Exception as e:
        flash("خطا در اعمال پارامترها: " + str(e), "danger")
        return redirect(url_for("index"))

    try:
        flash("محاسبات شروع شد — صبر کنید تا عملیات به پایان برسد...", "info")
        results = project_main.run_optimizations_without_ml()
        df_results = pd.DataFrame(results).sort_values(by="irr", ascending=False).reset_index(drop=True)
        df_results = df_results.round(2)

        RESULTS_CSV = Path.cwd() / "results_flask.csv"  # FIX: ذخیره در دایرکتوری فعلی
        df_results.to_csv(RESULTS_CSV, index=False, encoding='utf-8-sig')

        try:
            project_main.display_and_save_results(df_results)
            project_main.create_kpi_comparison_dashboard(df_results)
        except Exception:
            pass

        if not df_results.empty:
            best = df_results.iloc[0]
            top_kpis = {
                "irr": round(float(best['irr']), 2),
                "annual_profit_M": round(float(best['annual_profit'])/1_000_000, 2),
                "capex_M": round(float(best['total_capex'])/1_000_000, 2),
                "payback": round(float(best['payback_period']), 2)
            }
        else:
            top_kpis = None

        charts_data = df_results.to_dict(orient="records")

        flash("محاسبات با موفقیت تکمیل شد.", "success")
     
        kpi_img = Path("static/images/kpi_dashboard.png") if Path("static/images/kpi_dashboard.png").exists() else None
        tornado_img = Path("static/images/sensitivity_analysis_tornado.png") if Path("static/images/sensitivity_analysis_tornado.png").exists() else None

        return render_template(
            "index.html",
            project=project_main,
            techs=list(project_main.TECHNOLOGY_DATA.keys()),
            defaults={"inflation": project_main.INFLATION_RATE, "tax": project_main.TAX_RATE},
            table_html = df_results.to_html(
                classes='table table-striped table-dark',
                index=False,
                justify='center',
                float_format=lambda x: f"{x:.2f}"
                ),
            top_kpis=top_kpis,
            charts_json=json.dumps(charts_data, default=str),
            kpi_img="images/kpi_dashboard.png" if kpi_img else None,
            tornado_img="images/sensitivity_analysis_tornado.png" if tornado_img else None
        )

    except Exception as e:
        tb = traceback.format_exc()
        flash("خطا در اجرای الگوریتم‌ها. لاگ: " + str(e), "danger")
        return render_template("index.html", import_error=tb, project=project_main)

@app.route("/download")
def download_results():
    if RESULTS_CSV.exists():
        return send_file(str(RESULTS_CSV), as_attachment=True)
    flash("فایل نتایج آماده نیست.", "warning")
    return redirect(url_for("index"))

if __name__ == "__main__":
    
    app.run(host="0.0.0.0", port=int(os.environ.get("PORT", 7860)))