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

"""
Report: DXA requisitions (Medicus → Dropbox)
--------------------------------------------
- Selects all histdoc records for year 2025 containing "DXA"
- Finds matching PDF files in Dropbox (by rod_cis + "dxa" in name)
- Outputs Excel report: datum, idpaci, rod_cis, prijmeni, jmeno, file
"""

import os
import firebirdsql as fb
import pandas as pd
from pathlib import Path
from datetime import datetime

# ================== CONFIGURATION ==================
FDB_PATH = r"M:\Medicus\Data\Medicus.fdb"
EXPORT_DIR = Path(r"z:\Dropbox\Ordinace\Reporty")
DOC_DIR = Path(r"z:\Dropbox\Ordinace\Dokumentace_zpracovaná")


timestamp = datetime.now().strftime("%Y-%m-%d_%H-%M-%S")
xlsx_path = EXPORT_DIR / f"{timestamp} DXA report.xlsx"

# ================== DATABASE QUERY ==================
conn = fb.connect(
    host="192.168.1.10",
    port=3050,
    database=FDB_PATH,
    user="SYSDBA",
    password="masterkey",
    charset="WIN1250",
)

sql = """
SELECT
    h.datum,
    h.idpaci,
    k.rodcis,
    k.prijmeni,
    k.jmeno,
    (
        SELECT LIST(
            CAST(dd.datose AS DATE) || ':' || dd.kod, ', '
        )
        FROM dokladd dd
        WHERE dd.rodcis = k.rodcis
          AND EXTRACT(YEAR FROM dd.datose) = 2025
          AND dd.kod STARTING WITH '1132'
    ) AS vykony_1132_2025

FROM histdoc h
JOIN kar k ON h.idpaci = k.idpac
WHERE EXTRACT(YEAR FROM h.datum) = 2025
  AND h.data CONTAINING 'dxa'
ORDER BY h.datum DESC
"""


df = pd.read_sql(sql, conn)
conn.close()

# ================== REMOVE DUPLICATES AND SORT ==================
# Convert to datetime → drop duplicates → keep newest per patient → sort descending
df["DATUM"] = pd.to_datetime(df["DATUM"], errors="coerce")

# Drop duplicates, keep the newest by date
df = (
    df.sort_values("DATUM", ascending=False)
      .drop_duplicates(subset="RODCIS", keep="first")
      .sort_values("DATUM", ascending=False)
      .reset_index(drop=True)
)

# Convert to pure date (no time portion)
df["DATUM"] = df["DATUM"].dt.date

# ================== FIND MATCHING PDF FILES ==================
def find_dxa_file(rod_cis: str) -> str:
    """Return first matching DXA file for given rod_cis or ''."""
    if not rod_cis:
        return ""
    rod_cis = rod_cis.strip()

    # Case-insensitive search for files like "1234567890 [DXA] something.pdf"
    for file in DOC_DIR.iterdir():
        name = file.name.lower()
        if (
            file.suffix.lower() == ".pdf"
            and name.startswith(rod_cis.lower())
            and "[dxa]" in name
        ):
            return file.name
    return ""


df["FILE"] = df["RODCIS"].apply(find_dxa_file)


# ================== CLEAN OLD REPORTS ==================
for f in EXPORT_DIR.glob("* DXA report.xlsx"):
    try:
        f.unlink()
        print(f"🗑️ Deleted old report: {f.name}")
    except Exception as e:
        print(f"⚠️ Could not delete {f.name}: {e}")


# ================== EXPORT TO EXCEL ==================
with pd.ExcelWriter(xlsx_path, engine="openpyxl") as writer:
    df.to_excel(writer, index=False, sheet_name="DXA")
    ws = writer.sheets["DXA"]

    # Format header
    from openpyxl.styles import Font, Alignment, PatternFill, Border, Side
    header_fill = PatternFill(start_color="FFFF00", end_color="FFFF00", fill_type="solid")
    for cell in ws[1]:
        cell.font = Font(bold=True, color="000000")
        cell.alignment = Alignment(horizontal="center", vertical="center")
        cell.fill = header_fill

    # Auto column width, but hardcode FILE column to 120
    from openpyxl.utils import get_column_letter

    for col in ws.columns:
        col_letter = get_column_letter(col[0].column)
        header = ws.cell(row=1, column=col[0].column).value

        if header == "FILE":
            ws.column_dimensions[col_letter].width = 120
        else:
            max_len = max(len(str(cell.value)) if cell.value else 0 for cell in col)
            ws.column_dimensions[col_letter].width = min(max_len + 2, 80)

    # Borders
    thin = Side(border_style="thin", color="000000")
    border = Border(top=thin, left=thin, right=thin, bottom=thin)
    for row in ws.iter_rows(min_row=1, max_row=ws.max_row,
                            min_col=1, max_col=ws.max_column):
        for cell in row:
            cell.border = border

print(f"✅ Report created: {xlsx_path}")
print(f"📂 Source folder scanned: {DOC_DIR}")
print(f"🩻 {df['FILE'].astype(bool).sum()} matching DXA PDFs found")