Merge remote-tracking branch 'origin/main'

40 Fio 02 diagnostika 2.py

@@ -1,24 +0,0 @@
-import pymysql
-from pymysql.cursors import DictCursor
-
-conn = pymysql.connect(
-    host="192.168.1.76",
-    port=3307,
-    user="root",
-    password="Vlado9674+",
-    database="fio",
-    charset="utf8mb4",
-    cursorclass=DictCursor
-)
-
-with conn.cursor() as cur:
-    cur.execute("SHOW TABLES;")
-    print("📋 Tables:", [r[f"Tables_in_fio"] for r in cur.fetchall()])
-
-    cur.execute("SELECT COUNT(*) AS cnt FROM transactions;")
-    print("🧾 Rows in `transactions`:", cur.fetchone()["cnt"])
-
-    cur.execute("SHOW COLUMNS FROM transactions;")
-    print("\n📊 Columns:")
-    for r in cur.fetchall():
-        print(" -", r["Field"])

40 Fio 03 excel.py

@@ -1,117 +0,0 @@
-#!/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)

40 fio 01.py

@@ -1,168 +0,0 @@
-#!/usr/bin/env python3
-# -*- coding: utf-8 -*-
-
-"""
-Fio CSV import → MySQL (dev version)
-------------------------------------
-- Always drops & recreates `transactions` table
-- Uses real CSV headers as seen in "Vyhledane pohyby (3).csv"
-- Unique key = (Číslo účtu, ID operace, ID pokynu)
-"""
-
-import csv
-from pathlib import Path
-from datetime import datetime
-import pymysql
-from pymysql.cursors import DictCursor
-import re
-
-# ======== CONFIG ========
-CSV_PATH = Path(r"u:\Dropbox\!!!Days\Downloads Z230\Vyhledane pohyby (3).csv")
-TABLE_NAME = "transactions"
-
-MYSQL_CONFIG = {
-    "host": "192.168.1.76",
-    "port": 3307,
-    "user": "root",
-    "password": "Vlado9674+",
-    "database": "fio",
-    "charset": "utf8mb4",
-    "cursorclass": DictCursor,
-    "autocommit": True,
-}
-
-
-# ======== HELPERS ========
-def clean(s: str):
-    if not s:
-        return None
-    return s.strip() or None
-
-
-def parse_date(raw: str):
-    raw = (raw or "").strip()
-    if not raw:
-        return None
-    try:
-        return datetime.strptime(raw, "%d.%m.%Y").date()
-    except ValueError:
-        return None
-
-
-def parse_float(raw: str):
-    if raw is None:
-        return None
-    s = str(raw).strip()
-    for ch in (" ", "\u00A0", "\u202F", "\u2007"):
-        s = s.replace(ch, "")
-    s = s.replace(",", ".")
-    s = re.sub(r"[^0-9.+-]", "", s)
-    try:
-        return float(s)
-    except ValueError:
-        return None
-
-
-# ======== DB ========
-def get_mysql_connection():
-    return pymysql.connect(**MYSQL_CONFIG)
-
-
-def recreate_table(conn):
-    """Drop and recreate table with schema matching CSV structure."""
-    sql = f"""
-    DROP TABLE IF EXISTS `{TABLE_NAME}`;
-    CREATE TABLE `{TABLE_NAME}` (
-        id INT AUTO_INCREMENT PRIMARY KEY,
-        datum DATE,
-        objem DECIMAL(14,2),
-        mena CHAR(3),
-        cislo_uctu VARCHAR(40),
-        protiucet VARCHAR(40),
-        kod_banky VARCHAR(20),
-        ks VARCHAR(20),
-        vs VARCHAR(20),
-        ss VARCHAR(20),
-        zprava_pro_prijemce VARCHAR(500),
-        poznamka VARCHAR(500),
-        id_operace VARCHAR(50),
-        id_pokynu VARCHAR(50),
-        ks_1 VARCHAR(20),
-        nazev_banky VARCHAR(100),
-        nazev_protiuctu VARCHAR(200),
-        ss_1 VARCHAR(20),
-        typ VARCHAR(100),
-        upresneni_objem VARCHAR(100),
-        upresneni_mena VARCHAR(20),
-        vs_1 VARCHAR(20),
-        zadal VARCHAR(200),
-        imported_at DATETIME DEFAULT CURRENT_TIMESTAMP,
-        UNIQUE KEY uniq_tx (cislo_uctu, id_operace, id_pokynu)
-    ) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4;
-    """
-    with conn.cursor() as cur:
-        for stmt in sql.strip().split(";"):
-            if stmt.strip():
-                cur.execute(stmt)
-    print(f"✅ Tabulka `{TABLE_NAME}` znovu vytvořena podle CSV struktury.")
-
-
-# ======== IMPORT ========
-def import_fio_csv():
-    with open(CSV_PATH, "r", encoding="utf-8-sig", newline="") as f:
-        reader = csv.DictReader(f, delimiter=";", quotechar='"')
-        rows = list(reader)
-
-    total = len(rows)
-    print(f"📄 Načteno {total} řádků ze souboru {CSV_PATH.name}")
-
-    with get_mysql_connection() as conn:
-        recreate_table(conn)
-        inserted, skipped = 0, 0
-
-        for i, row in enumerate(rows, start=1):
-            data = {
-                "datum": parse_date(row.get("Datum")),
-                "objem": parse_float(row.get("Objem")),
-                "mena": clean(row.get("Měna")),
-                "cislo_uctu": clean(row.get("Číslo účtu")),
-                "protiucet": clean(row.get("Protiúčet")),
-                "kod_banky": clean(row.get("Kód banky")),
-                "ks": clean(row.get("KS")),
-                "vs": clean(row.get("VS")),
-                "ss": clean(row.get("SS")),
-                "zprava_pro_prijemce": clean(row.get("Zpráva pro příjemce")),
-                "poznamka": clean(row.get("Poznámka")),
-                "id_operace": clean(row.get("ID operace")),
-                "id_pokynu": clean(row.get("ID pokynu")),
-                "ks_1": clean(row.get("KS.1")),
-                "nazev_banky": clean(row.get("Název banky")),
-                "nazev_protiuctu": clean(row.get("Název protiúčtu")),
-                "ss_1": clean(row.get("SS.1")),
-                "typ": clean(row.get("Typ")),
-                "upresneni_objem": clean(row.get("Upřesnění - objem")),
-                "upresneni_mena": clean(row.get("Upřesnění - měna")),
-                "vs_1": clean(row.get("VS.1")),
-                "zadal": clean(row.get("Zadal")),
-            }
-
-            cols = ", ".join(data.keys())
-            placeholders = ", ".join(["%s"] * len(data))
-            sql = f"INSERT IGNORE INTO `{TABLE_NAME}` ({cols}) VALUES ({placeholders})"
-
-            with conn.cursor() as cur:
-                affected = cur.execute(sql, list(data.values()))
-                if affected:
-                    inserted += 1
-                else:
-                    skipped += 1
-
-            if i % 500 == 0 or i == total:
-                print(f"  {i}/{total} zpracováno... ({inserted} vloženo, {skipped} duplicit)")
-
-        print(f"\n✅ Import dokončen: {inserted} nových, {skipped} duplicit přeskočeno.")
-
-
-# ======== MAIN ========
-if __name__ == "__main__":
-    import_fio_csv()

40 fio 02 diagnostika.py

@@ -1,47 +0,0 @@
-#!/usr/bin/env python3
-# -*- coding: utf-8 -*-
-
-"""
-Quick, verified dump of all Fio transactions from MySQL → Excel.
-Column names are exactly as in DB.
-"""
-
-import pandas as pd
-import pymysql
-from pymysql.cursors import DictCursor
-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",
-
-}
-
-EXPORT_PATH = Path(r"u:\Dropbox\!!!Days\Downloads Z230") / f"Fio_ALL_{datetime.now():%Y-%m-%d_%H-%M-%S}.xlsx"
-
-# ======== MAIN ========
-def dump_all_transactions():
-    with pymysql.connect(**MYSQL_CONFIG) as conn:
-        sql = """
-            SELECT
-                *
-            FROM transactions
-            ORDER BY datum DESC;
-        """
-        df = pd.read_sql(sql, conn)
-
-    print(f"✅ Načteno {len(df)} transakcí z MySQL.")
-
-    # Save to Excel
-    df.to_excel(EXPORT_PATH, index=False)
-    print(f"📊 Excel export hotov:\n{EXPORT_PATH}")
-
-
-if __name__ == "__main__":
-    dump_all_transactions()

PSA/01 PSA.py

@@ -1,11 +1,11 @@
-import firebirdsql as fb
+import firebirdsql as fb,os
 import pandas as pd
 
 # TCP to the Firebird 2.5 server. Use the DB path as seen by the *server* (Windows path).
 conn = fb.connect(
-    host="192.168.1.4",
+    host="192.168.1.10",
     port=3050,
-    database=r"z:\Medicus 3\data\MEDICUS.FDB",  # raw string for backslashes
+    database=r"m:\Medicus\data\MEDICUS.FDB",  # raw string for backslashes
     user="SYSDBA",
     password="masterkey",
     charset="WIN1250",  # adjust if needed
@@ -49,7 +49,7 @@ SELECT
     FROM dokladd dd
     WHERE dd.rodcis = kar.rodcis
       AND (dd.kod = '01130' or dd.kod = '01131' OR dd.kod = '01132' OR dd.kod = '01133' OR dd.kod = '01134')
-      AND dd.datose BETWEEN vh.datum - 7 AND vh.datum + 7
+      AND dd.datose BETWEEN vh.datum - 365 AND vh.datum + 365
   ) AS vykodovano,
    lm.kodtext,
   lm.nazev,
@@ -119,11 +119,23 @@ from openpyxl.formatting.rule import ColorScaleRule
 from openpyxl.styles import PatternFill
 from openpyxl.formatting.rule import FormulaRule
 
-# ---- 1) Build timestamped output path ----
+
-base_path = Path("u:\Dropbox\!!!Days\Downloads Z230")
+base_path = Path(r"z:\Dropbox\Ordinace\Reporty")
-base_path.mkdir(parents=True, exist_ok=True)  # ensure folder exists
+base_path.mkdir(parents=True, exist_ok=True)
-timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
+
-output_file = base_path / f"lab_results_2025_{timestamp}.xlsx"
+# ================= DELETE OLD PSA REPORTS ==================
+for fname in os.listdir(base_path):
+    if fname.endswith("PSA report.xlsx"):
+        try:
+            os.remove(base_path / fname)
+            print(f"🗑️ Deleted old PSA report: {fname}")
+        except Exception as e:
+            print(f"⚠️ Could not delete {fname}: {e}")
+
+# ================= CREATE NEW FILENAME ==================
+timestamp = datetime.now().strftime("%Y-%m-%d %H-%M-%S")
+output_file = base_path / f"{timestamp} PSA report.xlsx"
+print(f"📄 New PSA report will be saved as: {output_file}")
 
 # ---- 2) Export DataFrame to Excel ----
 # Assumes df_direct already exists (your joined query result)

PSA/Reporter PSA.py

@@ -0,0 +1,212 @@
+import firebirdsql as fb,os
+import pandas as pd
+
+# TCP to the Firebird 2.5 server. Use the DB path as seen by the *server* (Windows path).
+conn = fb.connect(
+    host="192.168.1.10",
+    port=3050,
+    database=r"m:\Medicus\data\MEDICUS.FDB",  # raw string for backslashes
+    user="SYSDBA",
+    password="masterkey",
+    charset="WIN1250",  # adjust if needed
+)
+
+# Tiny helper to fetch directly into DataFrame (avoids the pandas/SQLAlchemy warning)
+def query_df(sql, params=None):
+    cur = conn.cursor()
+    cur.execute(sql, params or ())
+    rows = cur.fetchall()
+    cols = [d[0].strip() for d in cur.description]  # Firebird pads column names
+    return pd.DataFrame(rows, columns=cols)
+
+# Smoke test
+print(query_df("SELECT 1 AS ONE FROM RDB$DATABASE"))
+
+# Your table
+df = query_df("SELECT FIRST 100 * FROM kar")
+print(df)
+
+
+
+from datetime import datetime
+start = datetime(2025, 1, 1)
+end   = datetime(2026, 1, 1)
+
+sql = """
+SELECT
+  /*vh.idvh,*/
+  vh.idpacient,
+  kar.prijmeni,
+  kar.jmeno,
+  kar.rodcis,
+  vh.datum,
+  /*vh.idhodn,*/
+  /*vd.poradi,*/
+  /*vd.idmetod,*/
+/* NEW: list of matching dokladd entries within ±7 days, one cell */
+  (
+    SELECT LIST(CAST(dd.datose AS VARCHAR(10)) || ' ' || dd.kod, ', ')
+    FROM dokladd dd
+    WHERE dd.rodcis = kar.rodcis
+      AND (dd.kod = '01130' or dd.kod = '01131' OR dd.kod = '01132' OR dd.kod = '01133' OR dd.kod = '01134')
+      AND dd.datose BETWEEN vh.datum - 7 AND vh.datum + 7
+  ) AS vykodovano,
+   lm.kodtext,
+  lm.nazev,
+  vd.vysl,
+  lj.jedn,
+  ls.normdol,
+  ls.normhor
+FROM labvh vh
+JOIN labvd vd        ON vd.idvh = vh.idvh
+JOIN kar             ON kar.idpac = vh.idpacient
+JOIN labmetod lm     ON lm.idmetod = vd.idmetod
+JOIN labjedn lj      ON lj.idjedn = vd.idjedn
+JOIN labskaly ls     ON ls.idskaly = vd.idskaly
+WHERE vh.datum >= ?
+  AND vh.datum < ?
+  AND lm.nazev CONTAINING 'PSA'
+/*ORDER BY kar.idpac, vh.datum, vd.poradi;*/
+ORDER BY vh.datum desc;
+"""
+
+df_direct = query_df(sql, (start, end))
+
+import re
+import numpy as np
+
+# --- 0) Helper: parse numeric value from string like "5,6", "<0.1", "3.2 mmol/L" ---
+num_re = re.compile(r'[-+]?\d+(?:[.,]\d+)?(?:[eE][-+]?\d+)?')
+
+def to_num(x):
+    if x is None:
+        return np.nan
+    s = str(x).strip()
+    if not s:
+        return np.nan
+    m = num_re.search(s.replace('\u00A0', ' '))  # remove NBSP if any
+    if not m:
+        return np.nan
+    val_str = m.group(0).replace(',', '.')
+    try:
+        val = float(val_str)
+    except ValueError:
+        return np.nan
+    # Heuristic for qualifiers:
+    # "<x" -> take half of x (below detection limit), ">x" -> take x (at least)
+    if s.lstrip().startswith('<'):
+        return val * 0.5
+    if s.lstrip().startswith('>'):
+        return val
+    return val
+
+# --- 1) Prepare numeric columns + ratio in pandas before export ---
+# Assumes df_direct exists with columns 'VYSL' and 'NORMHOR' (case per your SELECT)
+df_direct["VYSL_NUM"] = df_direct["VYSL"].apply(to_num)
+df_direct["NORMHOR_NUM"] = df_direct["NORMHOR"].apply(to_num)
+
+# Avoid division by zero/NaN
+den = df_direct["NORMHOR_NUM"].replace(0, np.nan)
+df_direct["RATIO"] = (df_direct["VYSL_NUM"] / den).clip(lower=0)  # can exceed 1 if over ULN
+
+
+from datetime import datetime
+from pathlib import Path
+from openpyxl import load_workbook
+from openpyxl.utils import get_column_letter
+from openpyxl.styles import Alignment, Border, Side
+from openpyxl.formatting.rule import ColorScaleRule
+from openpyxl.styles import PatternFill
+from openpyxl.formatting.rule import FormulaRule
+
+
+base_path = Path(r"z:\Dropbox\Ordinace\Reporty")
+base_path.mkdir(parents=True, exist_ok=True)
+
+# ================= DELETE OLD PSA REPORTS ==================
+for fname in os.listdir(base_path):
+    if fname.endswith("PSA report.xlsx"):
+        try:
+            os.remove(base_path / fname)
+            print(f"🗑️ Deleted old PSA report: {fname}")
+        except Exception as e:
+            print(f"⚠️ Could not delete {fname}: {e}")
+
+# ================= CREATE NEW FILENAME ==================
+timestamp = datetime.now().strftime("%Y-%m-%d %H-%M-%S")
+output_file = base_path / f"{timestamp} PSA report.xlsx"
+print(f"📄 New PSA report will be saved as: {output_file}")
+
+# ---- 2) Export DataFrame to Excel ----
+# Assumes df_direct already exists (your joined query result)
+df_direct.to_excel(output_file, index=False, sheet_name="PSA")
+
+# ---- 3) Open with openpyxl for formatting ----
+wb = load_workbook(output_file)
+ws = wb["PSA"]
+
+# Auto width for columns
+for col in ws.columns:
+    max_len = 0
+    col_letter = get_column_letter(col[0].column)
+    for cell in col:
+        try:
+            if cell.value is not None:
+                max_len = max(max_len, len(str(cell.value)))
+        except Exception:
+            pass
+    ws.column_dimensions[col_letter].width = min(max_len + 2, 50)  # cap width
+
+# Thin border style
+thin_border = Border(
+    left=Side(style="thin"),
+    right=Side(style="thin"),
+    top=Side(style="thin"),
+    bottom=Side(style="thin"),
+)
+
+# Apply borders to all cells and center A, B, E
+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 = thin_border
+        if cell.column_letter in ["A", "B", "E"]:
+            cell.alignment = Alignment(horizontal="center")
+
+# Enable filter on header row and freeze it
+ws.auto_filter.ref = ws.dimensions
+ws.freeze_panes = "A2"
+
+
+# map headers
+hdr = {c.value: i+1 for i, c in enumerate(ws[1])}
+vysl_idx  = hdr.get("VYSL")
+ratio_idx = hdr.get("RATIO")
+if not (vysl_idx and ratio_idx):
+    raise RuntimeError("Missing required columns: VYSL and/or RATIO")
+
+vysl_col  = get_column_letter(vysl_idx)
+ratio_col = get_column_letter(ratio_idx)
+max_row   = ws.max_row
+rng_vysl  = f"{vysl_col}2:{vysl_col}{max_row}"
+
+green  = PatternFill(start_color="63BE7B", end_color="63BE7B", fill_type="solid")
+yellow = PatternFill(start_color="FFEB84", end_color="FFEB84", fill_type="solid")
+red    = PatternFill(start_color="F8696B", end_color="F8696B", fill_type="solid")
+
+# Non-overlapping rules; stop when one matches
+ws.conditional_formatting.add(
+    rng_vysl,
+    FormulaRule(formula=[f"${ratio_col}2<=0.80"], fill=green,  stopIfTrue=True)
+)
+ws.conditional_formatting.add(
+    rng_vysl,
+    FormulaRule(formula=[f"AND(${ratio_col}2>0.80, ${ratio_col}2<1)"], fill=yellow, stopIfTrue=True)
+)
+ws.conditional_formatting.add(
+    rng_vysl,
+    FormulaRule(formula=[f"${ratio_col}2>=1"], fill=red,      stopIfTrue=True)
+)
+
+
+wb.save(output_file)
+print(f"Saved: {output_file}")

Vakcíny/12 Vakcina na samostatnych listech.py

@@ -3,23 +3,23 @@
 
 from pathlib import Path
 import time
-import fdb
+import firebirdsql as fb
 import pandas as pd
 import re
 from openpyxl import load_workbook
 from openpyxl.worksheet.table import Table, TableStyleInfo
 from openpyxl.styles import Font, PatternFill, Alignment
 from openpyxl.utils import get_column_letter
-from Functions import get_medicus_connection
+# from Functions import get_medicus_connection
 
 # ================== Výstupní cesta ==================
 BASE_DIR = Path(r"z:\Dropbox\Ordinace\Reporty")  # uprav dle potřeby
 timestamp = time.strftime("%Y-%m-%d %H-%M-%S")
-xlsx_name = f"Pacienti očkování {timestamp}.xlsx"
+xlsx_name = f"{timestamp} Očkování report.xlsx"
 xlsx_path = BASE_DIR / xlsx_name
 
 # ================== Smazání starých souborů ==================
-for old_file in BASE_DIR.glob("Pacienti očkování *.xlsx"):
+for old_file in BASE_DIR.glob("*očkování report.xlsx"):
     try:
         if old_file != xlsx_path:  # skip the file we’re about to create
             old_file.unlink()
@@ -39,7 +39,15 @@ SHEETS = {
 }
 
 # ================== Připojení k DB ==================
-con = get_medicus_connection()
+# con = get_medicus_connection()
+con = fb.connect(
+    host="192.168.1.10",
+    port=3050,
+    database=r"m:\Medicus\data\MEDICUS.FDB",  # raw string for backslashes
+    user="SYSDBA",
+    password="masterkey",
+    charset="WIN1250",  # adjust if needed
+)
 # ================== SQL dotaz ==================
 sql = """
 SELECT

Vakcíny/Reporter Očkování report.py

@@ -0,0 +1,168 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+
+from pathlib import Path
+import time
+import firebirdsql as fb
+import pandas as pd
+import re
+from openpyxl import load_workbook
+from openpyxl.worksheet.table import Table, TableStyleInfo
+from openpyxl.styles import Font, PatternFill, Alignment
+from openpyxl.utils import get_column_letter
+# from Functions import get_medicus_connection
+
+# ================== Výstupní cesta ==================
+BASE_DIR = Path(r"z:\Dropbox\Ordinace\Reporty")  # uprav dle potřeby
+timestamp = time.strftime("%Y-%m-%d %H-%M-%S")
+xlsx_name = f"{timestamp} Očkování report.xlsx"
+xlsx_path = BASE_DIR / xlsx_name
+
+# ================== Smazání starých souborů ==================
+for old_file in BASE_DIR.glob("*očkování report.xlsx"):
+    try:
+        if old_file != xlsx_path:  # skip the file we’re about to create
+            old_file.unlink()
+            print(f"Smazán starý soubor: {old_file.name}")
+    except Exception as e:
+        print(f"⚠️ Nelze smazat {old_file.name}: {e}")
+
+# ================== Definice skupin vakcín ==================
+SHEETS = {
+    "COVID-19": ["commirnaty", "spikevax", "nuvaxovid"],
+    "Chřipka": ["vaxigrip", "influvac", "fluarix", "afluria"],
+    "Klíšťová encefalitida": ["fsme", "encepur"],
+    "Tetanus": ["tetavax", "boostrix", "adacel"],
+    "HepA": ["avaxim", "havrix","vaqta"],
+    "HepB": ["engerix"],
+    "HepA+B": ["twinrix"],
+}
+
+# ================== Připojení k DB ==================
+# con = get_medicus_connection()
+con = fb.connect(
+    host="192.168.1.10",
+    port=3050,
+    database=r"m:\Medicus\data\MEDICUS.FDB",  # raw string for backslashes
+    user="SYSDBA",
+    password="masterkey",
+    charset="WIN1250",  # adjust if needed
+)
+# ================== SQL dotaz ==================
+sql = """
+SELECT
+    kar.rodcis    AS "Rodné číslo",
+    kar.prijmeni  AS "Příjmení",
+    kar.jmeno     AS "Jméno",
+    ockzaz.datum  AS "Datum očkování",
+    ockzaz.kodmz  AS "Kód MZ",
+    ockzaz.poznamka AS "Šarže",
+    ockzaz.latka  AS "Látka",
+    ockzaz.nazev  AS "Název",
+    ockzaz.expire AS "Expirace",
+    (
+      SELECT LIST(l.kod, ', ')
+      FROM lecd l
+      WHERE l.rodcis = kar.rodcis
+        AND l.datose = CAST(ockzaz.datum AS DATE)
+    ) AS "LECD kódy (ten den)",
+    (
+      SELECT LIST(d.kod, ', ')
+      FROM dokladd d
+      WHERE d.rodcis = kar.rodcis
+        AND d.datose = CAST(ockzaz.datum AS DATE)
+    ) AS "Výkony (ten den)"
+FROM registr
+JOIN kar     ON registr.idpac = kar.idpac
+JOIN ockzaz  ON registr.idpac = ockzaz.idpac
+WHERE
+    registr.datum_zruseni IS NULL
+    AND kar.vyrazen <> 'A'
+    AND kar.rodcis IS NOT NULL
+    AND idicp <> 0
+    AND EXTRACT(YEAR FROM ockzaz.datum) = 2025
+ORDER BY ockzaz.datum DESC
+"""
+
+# ================== Načtení do DataFrame ==================
+df = pd.read_sql(sql, con)
+con.close()
+
+# ================== Datové typy ==================
+for col in ["Kód MZ", "Šarže", "Rodné číslo", "Látka", "Název", "Příjmení", "Jméno", "LECD kódy", "Výkony"]:
+    if col in df.columns:
+        df[col] = df[col].astype("string")
+
+for dcol in ["Datum očkování", "Expirace"]:
+    if dcol in df.columns:
+        df[dcol] = pd.to_datetime(df[dcol], errors="coerce")
+
+# ================== Uložení do Excelu – více listů ==================
+with pd.ExcelWriter(xlsx_path, engine="openpyxl") as writer:
+    for sheet_name, vakciny in SHEETS.items():
+        pattern = "|".join(re.escape(v) for v in vakciny if v)
+        mask = df["Látka"].astype(str).str.contains(pattern, case=False, na=False)
+        df_filtered = df[mask]
+        if not df_filtered.empty:
+            df_filtered.to_excel(writer, index=False, sheet_name=sheet_name)
+    # navíc celkový přehled všech očkování
+    df.to_excel(writer, index=False, sheet_name="Vše")
+
+# ================== Formátování ==================
+wb = load_workbook(xlsx_path)
+
+def autosize_columns(ws):
+    for col_idx in range(1, ws.max_column + 1):
+        col_letter = get_column_letter(col_idx)
+        max_len = 0
+        for cell in ws[col_letter]:
+            val = "" if cell.value is None else str(cell.value)
+            if len(val) > max_len:
+                max_len = len(val)
+        ws.column_dimensions[col_letter].width = min(max(12, max_len + 2), 60)
+
+def safe_table_name(sheet_name):
+    """Return an Excel-safe, unique table name."""
+    name = re.sub(r"[^0-9A-Za-z_]", "_", sheet_name)
+    return f"tbl_{name[:25]}"
+
+def style_table(ws):
+    max_row = ws.max_row
+    max_col = ws.max_column
+    if max_col == 0:
+        return
+
+    header_fill = PatternFill("solid", fgColor="D9E1F2")
+    for cell in ws[1]:
+        cell.font = Font(bold=True)
+        cell.fill = header_fill
+        cell.alignment = Alignment(vertical="center")
+
+    ws.freeze_panes = "A2"
+
+    if max_row < 2:
+        autosize_columns(ws)
+        return
+
+    ref = f"A1:{get_column_letter(max_col)}{max_row}"
+    tbl = Table(displayName=safe_table_name(ws.title), ref=ref)
+    tbl.tableStyleInfo = TableStyleInfo(
+        name="TableStyleMedium9", showRowStripes=True, showColumnStripes=False
+    )
+    ws.add_table(tbl)
+    autosize_columns(ws)
+
+def format_dates(ws, columns_names):
+    header = [c.value for c in ws[1]]
+    date_cols = [header.index(name) + 1 for name in columns_names if name in header]
+    for col_idx in date_cols:
+        for row in ws.iter_rows(min_row=2, min_col=col_idx, max_col=col_idx, max_row=ws.max_row):
+            row[0].number_format = "DD.MM.YYYY"
+
+for ws in wb.worksheets:
+    style_table(ws)
+    format_dates(ws, ["Datum očkování", "Expirace"])
+
+wb.save(xlsx_path)
+
+print(f"✅ Hotovo. Uloženo do: {xlsx_path.resolve()}")