This commit is contained in:
michaela.buzalkova
2025-10-24 18:56:12 +02:00
parent 6d2b4e9858
commit eda5ec3d82
3 changed files with 311 additions and 142 deletions

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#!/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")