#!/usr/bin/env python3
# -*- coding: utf-8 -*-

"""
Export Fio transactions (from MySQL → Excel)
--------------------------------------------
- Reads only cislo_uctu = '2800046620'
- For OZP (protiucet=2070101041) includes only positive objem
- Each sheet = insurance company (filtered by protiucet)
- First sheet = summary with total amounts and transaction counts
"""

import pandas as pd
import pymysql
from pathlib import Path
from datetime import datetime

# ======== CONFIG ========
MYSQL_CONFIG = {
    "host": "192.168.1.76",
    "port": 3307,
    "user": "root",
    "password": "Vlado9674+",
    "database": "fio",
    "charset": "utf8mb4",
}

REPORTOVAT = {
    "VZP": "1114007221",
    "VOZP": "2010009091",
    "ČPZP": "2054108761",
    "OZP": "2070101041",
    "ZPŠ": "2090309181",
    "ZPMV": "2112108031",
}

EXPORT_PATH = Path(r"u:\Dropbox\!!!Days\Downloads Z230") / f"Fio_report_{datetime.now():%Y-%m-%d_%H-%M-%S}.xlsx"


# ======== LOAD DATA ========
def load_data():
    print("🔄 Načítám data z MySQL (účet 2800046620, pro OZP jen kladné objemy)...")
    conn = pymysql.connect(**MYSQL_CONFIG)

    sql = """
        SELECT *
        FROM transactions
        WHERE cislo_uctu = '2800046620'
          AND (
              protiucet <> '2070101041'
              OR (protiucet = '2070101041' AND objem > 0)
          );
    """
    df = pd.read_sql(sql, conn)
    conn.close()

    df.columns = df.columns.str.strip()
    print(f"✅ Načteno {len(df)} řádků, {len(df.columns)} sloupců.")
    return df


# ======== EXPORT TO EXCEL ========
def export_to_excel(df):
    summary_rows = []  # to collect summary per insurer

    with pd.ExcelWriter(EXPORT_PATH, engine="openpyxl") as writer:
        # --- INDIVIDUAL SHEETS ---
        for name, acc in REPORTOVAT.items():
            filtered = df[df["protiucet"].astype(str) == acc]
            if filtered.empty:
                print(f"⚠️ {name}: žádné transakce (účet {acc})")
                summary_rows.append({
                    "Pojišťovna": name,
                    "Číslo účtu": acc,
                    "Počet transakcí": 0,
                    "Součet objemu": 0.0
                })
                continue

            # safe numeric conversion
            filtered = filtered.copy()
            filtered["objem_num"] = (
                filtered["objem"]
                .astype(str)
                .str.replace("\u00A0", "", regex=False)
                .str.replace(",", ".", regex=False)
                .astype(float)
            )

            # --- summary data ---
            total_sum = filtered["objem_num"].sum()
            total_count = len(filtered)

            summary_rows.append({
                "Pojišťovna": name,
                "Číslo účtu": acc,
                "Počet transakcí": total_count,
                "Součet objemu": round(total_sum, 2)
            })

            # --- write detailed sheet ---
            filtered.to_excel(writer, index=False, sheet_name=name)
            print(f"✅ {name}: {len(filtered)} řádků exportováno, součet {total_sum:,.2f} Kč")

        # --- SUMMARY SHEET ---
        summary_df = pd.DataFrame(summary_rows)
        summary_df["Součet objemu"] = summary_df["Součet objemu"].map("{:,.2f} Kč".format)
        summary_df.to_excel(writer, index=False, sheet_name="Přehled")
        print("🧾 Přidán přehledový list s celkovými součty.")

    print(f"\n📊 Hotovo! Soubor uložen jako:\n{EXPORT_PATH}")


# ======== MAIN ========
if __name__ == "__main__":
    df = load_data()
    export_to_excel(df)