Merge remote-tracking branch 'origin/main'
This commit is contained in:
michaela.buzalkova
24
40 Fio 02 diagnostika 2.py
Normal file
24
40 Fio 02 diagnostika 2.py
Normal file
@@ -0,0 +1,24 @@
|
||||
import pymysql
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||||
from pymysql.cursors import DictCursor
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||||
|
||||
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:
|
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cur.execute("SHOW TABLES;")
|
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print("📋 Tables:", [r[f"Tables_in_fio"] for r in cur.fetchall()])
|
||||
|
||||
cur.execute("SELECT COUNT(*) AS cnt FROM transactions;")
|
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print("🧾 Rows in `transactions`:", cur.fetchone()["cnt"])
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|
||||
cur.execute("SHOW COLUMNS FROM transactions;")
|
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print("\n📊 Columns:")
|
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for r in cur.fetchall():
|
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print(" -", r["Field"])
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117
40 Fio 03 excel.py
Normal file
117
40 Fio 03 excel.py
Normal file
@@ -0,0 +1,117 @@
|
||||
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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|
||||
"""
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Export Fio transactions (from MySQL → Excel)
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--------------------------------------------
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||||
- Reads only cislo_uctu = '2800046620'
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- For OZP (protiucet=2070101041) includes only positive objem
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- Each sheet = insurance company (filtered by protiucet)
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- First sheet = summary with total amounts and transaction counts
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"""
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|
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import pandas as pd
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import pymysql
|
||||
from pathlib import Path
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||||
from datetime import datetime
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||||
|
||||
# ======== CONFIG ========
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||||
MYSQL_CONFIG = {
|
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"host": "192.168.1.76",
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||||
"port": 3307,
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"user": "root",
|
||||
"password": "Vlado9674+",
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||||
"database": "fio",
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"charset": "utf8mb4",
|
||||
}
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||||
|
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REPORTOVAT = {
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"VZP": "1114007221",
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"VOZP": "2010009091",
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"ČPZP": "2054108761",
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"OZP": "2070101041",
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"ZPŠ": "2090309181",
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"ZPMV": "2112108031",
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}
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|
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EXPORT_PATH = Path(r"u:\Dropbox\!!!Days\Downloads Z230") / f"Fio_report_{datetime.now():%Y-%m-%d_%H-%M-%S}.xlsx"
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||||
|
||||
|
||||
# ======== LOAD DATA ========
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||||
def load_data():
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print("🔄 Načítám data z MySQL (účet 2800046620, pro OZP jen kladné objemy)...")
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conn = pymysql.connect(**MYSQL_CONFIG)
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|
||||
sql = """
|
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SELECT *
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||||
FROM transactions
|
||||
WHERE cislo_uctu = '2800046620'
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AND (
|
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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):
|
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summary_rows = [] # to collect summary per insurer
|
||||
|
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with pd.ExcelWriter(EXPORT_PATH, engine="openpyxl") as writer:
|
||||
# --- INDIVIDUAL SHEETS ---
|
||||
for name, acc in REPORTOVAT.items():
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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,
|
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"Počet transakcí": total_count,
|
||||
"Součet objemu": round(total_sum, 2)
|
||||
})
|
||||
|
||||
# --- write detailed sheet ---
|
||||
filtered.to_excel(writer, index=False, sheet_name=name)
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print(f"✅ {name}: {len(filtered)} řádků exportováno, součet {total_sum:,.2f} Kč")
|
||||
|
||||
# --- SUMMARY SHEET ---
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||||
summary_df = pd.DataFrame(summary_rows)
|
||||
summary_df["Součet objemu"] = summary_df["Součet objemu"].map("{:,.2f} Kč".format)
|
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summary_df.to_excel(writer, index=False, sheet_name="Přehled")
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||||
print("🧾 Přidán přehledový list s celkovými součty.")
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||||
|
||||
print(f"\n📊 Hotovo! Soubor uložen jako:\n{EXPORT_PATH}")
|
||||
|
||||
|
||||
# ======== MAIN ========
|
||||
if __name__ == "__main__":
|
||||
df = load_data()
|
||||
export_to_excel(df)
|
||||
100
40 fio 01.py
100
40 fio 01.py
@@ -2,11 +2,11 @@
|
||||
# -*- coding: utf-8 -*-
|
||||
|
||||
"""
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Import Fio banka CSV export (UTF-8, ; separated, quoted)
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into MySQL database `fio.transactions`.
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|
||||
Unique key = (Číslo účtu, ID operace, ID pokynu)
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Duplicates are skipped silently.
|
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Fio CSV import → MySQL (dev version)
|
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------------------------------------
|
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- Always drops & recreates `transactions` table
|
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- Uses real CSV headers as seen in "Vyhledane pohyby (3).csv"
|
||||
- Unique key = (Číslo účtu, ID operace, ID pokynu)
|
||||
"""
|
||||
|
||||
import csv
|
||||
@@ -14,6 +14,7 @@ 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")
|
||||
@@ -33,14 +34,12 @@ MYSQL_CONFIG = {
|
||||
|
||||
# ======== HELPERS ========
|
||||
def clean(s: str):
|
||||
"""Trim and normalize text values."""
|
||||
if not s:
|
||||
return None
|
||||
return s.strip() or None
|
||||
|
||||
|
||||
def parse_date(raw: str):
|
||||
"""Convert dd.mm.yyyy → date"""
|
||||
raw = (raw or "").strip()
|
||||
if not raw:
|
||||
return None
|
||||
@@ -51,10 +50,15 @@ def parse_date(raw: str):
|
||||
|
||||
|
||||
def parse_float(raw: str):
|
||||
"""Convert comma/space separated numbers to float"""
|
||||
raw = (raw or "").replace(" ", "").replace(",", ".")
|
||||
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(raw)
|
||||
return float(s)
|
||||
except ValueError:
|
||||
return None
|
||||
|
||||
@@ -64,38 +68,43 @@ def get_mysql_connection():
|
||||
return pymysql.connect(**MYSQL_CONFIG)
|
||||
|
||||
|
||||
def ensure_table_exists(conn):
|
||||
"""Create table if it doesn’t exist, with unique key on (cislo_uctu, id_operace, id_pokynu)."""
|
||||
def recreate_table(conn):
|
||||
"""Drop and recreate table with schema matching CSV structure."""
|
||||
sql = f"""
|
||||
CREATE TABLE IF NOT EXISTS `{TABLE_NAME}` (
|
||||
DROP TABLE IF EXISTS `{TABLE_NAME}`;
|
||||
CREATE TABLE `{TABLE_NAME}` (
|
||||
id INT AUTO_INCREMENT PRIMARY KEY,
|
||||
datum DATE,
|
||||
castka DECIMAL(14,2),
|
||||
akce VARCHAR(100),
|
||||
objem DECIMAL(14,2),
|
||||
mena CHAR(3),
|
||||
cislo_uctu VARCHAR(40),
|
||||
id_operace VARCHAR(50),
|
||||
id_pokynu VARCHAR(50),
|
||||
protiucet VARCHAR(40),
|
||||
nazev_protiuctu VARCHAR(200),
|
||||
kod_banky VARCHAR(20),
|
||||
ks VARCHAR(20),
|
||||
vs VARCHAR(20),
|
||||
ss VARCHAR(20),
|
||||
zprava_pro_prijemce VARCHAR(500),
|
||||
poznamka VARCHAR(500),
|
||||
reference_platce VARCHAR(200),
|
||||
typ VARCHAR(100),
|
||||
upresneni VARCHAR(500),
|
||||
zadal VARCHAR(200),
|
||||
zdrojovy_ucet VARCHAR(50),
|
||||
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:
|
||||
cur.execute(sql)
|
||||
print(f"✅ Tabulka `{TABLE_NAME}` zkontrolována nebo vytvořena.")
|
||||
for stmt in sql.strip().split(";"):
|
||||
if stmt.strip():
|
||||
cur.execute(stmt)
|
||||
print(f"✅ Tabulka `{TABLE_NAME}` znovu vytvořena podle CSV struktury.")
|
||||
|
||||
|
||||
# ======== IMPORT ========
|
||||
@@ -104,35 +113,37 @@ def import_fio_csv():
|
||||
reader = csv.DictReader(f, delimiter=";", quotechar='"')
|
||||
rows = list(reader)
|
||||
|
||||
total_rows = len(rows)
|
||||
print(f"📄 Načteno {total_rows} řádků ze souboru {CSV_PATH.name}")
|
||||
total = len(rows)
|
||||
print(f"📄 Načteno {total} řádků ze souboru {CSV_PATH.name}")
|
||||
|
||||
with get_mysql_connection() as conn:
|
||||
ensure_table_exists(conn)
|
||||
recreate_table(conn)
|
||||
inserted, skipped = 0, 0
|
||||
|
||||
for i, row in enumerate(rows, start=1):
|
||||
data = {
|
||||
"datum": parse_date(row.get("Datum")),
|
||||
"castka": parse_float(row.get("Částka")),
|
||||
"akce": clean(row.get("Akce")),
|
||||
"objem": parse_float(row.get("Objem")),
|
||||
"mena": clean(row.get("Měna")),
|
||||
"cislo_uctu": clean(row.get("Číslo účtu")),
|
||||
"id_operace": clean(row.get("ID operace")),
|
||||
"id_pokynu": clean(row.get("ID pokynu")),
|
||||
"protiucet": clean(row.get("Protiúčet")),
|
||||
"nazev_protiuctu": clean(row.get("Název protiúčtu")),
|
||||
"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")),
|
||||
"reference_platce": clean(row.get("Reference plátce")),
|
||||
"typ": clean(row.get("Typ")),
|
||||
"upresneni": clean(row.get("Upřesnění")),
|
||||
"zadal": clean(row.get("Zadal")),
|
||||
"zdrojovy_ucet": clean(row.get("Zdrojový účet")),
|
||||
"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())
|
||||
@@ -146,21 +157,12 @@ def import_fio_csv():
|
||||
else:
|
||||
skipped += 1
|
||||
|
||||
# --- progress output ---
|
||||
if i % 500 == 0 or i == total_rows:
|
||||
print(f" {i}/{total_rows} zpracováno... ({inserted} vloženo, {skipped} duplicit)")
|
||||
|
||||
# summary
|
||||
with conn.cursor() as cur:
|
||||
cur.execute(f"SELECT COUNT(*) AS cnt FROM `{TABLE_NAME}`")
|
||||
total_db = cur.fetchone()["cnt"]
|
||||
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.")
|
||||
print(f"📊 Celkem v databázi: {total_db} záznamů.")
|
||||
|
||||
|
||||
# ======== MAIN ========
|
||||
if __name__ == "__main__":
|
||||
if not CSV_PATH.exists():
|
||||
raise SystemExit(f"❌ Soubor {CSV_PATH} nenalezen.")
|
||||
import_fio_csv()
|
||||
|
||||
@@ -2,46 +2,46 @@
|
||||
# -*- coding: utf-8 -*-
|
||||
|
||||
"""
|
||||
Diagnostický test: načti Fio CSV a ověř parsování datumu.
|
||||
Nenačítá se do MySQL – pouze vypíše výsledek.
|
||||
Quick, verified dump of all Fio transactions from MySQL → Excel.
|
||||
Column names are exactly as in DB.
|
||||
"""
|
||||
|
||||
import csv
|
||||
from datetime import datetime
|
||||
import pandas as pd
|
||||
import pymysql
|
||||
from pymysql.cursors import DictCursor
|
||||
from pathlib import Path
|
||||
from datetime import datetime
|
||||
|
||||
# ✅ Tvoje cesta k souboru
|
||||
CSV_PATH = Path(r"u:\Dropbox\!!!Days\Downloads Z230\Vyhledane pohyby (1).csv")
|
||||
# ======== CONFIG ========
|
||||
MYSQL_CONFIG = {
|
||||
"host": "192.168.1.76",
|
||||
"port": 3307,
|
||||
"user": "root",
|
||||
"password": "Vlado9674+",
|
||||
"database": "fio",
|
||||
"charset": "utf8mb4",
|
||||
|
||||
}
|
||||
|
||||
def parse_czech_date(s: str):
|
||||
"""Očistí řetězec a zkusí dd.mm.yyyy."""
|
||||
if not s:
|
||||
return None
|
||||
s = s.strip().replace("\u00A0", "").replace("\ufeff", "")
|
||||
try:
|
||||
return datetime.strptime(s, "%d.%m.%Y").date()
|
||||
except Exception:
|
||||
return None
|
||||
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)
|
||||
|
||||
def main():
|
||||
with open(CSV_PATH, "r", encoding="utf-8-sig", newline="") as f:
|
||||
reader = csv.DictReader(f, delimiter=";", quotechar='"')
|
||||
rows = list(reader)
|
||||
print(f"✅ Načteno {len(df)} transakcí z MySQL.")
|
||||
|
||||
print(f"Načteno {len(rows)} řádků.\n")
|
||||
print("Ukázka prvních 10 řádků s hodnotou Datum:\n")
|
||||
|
||||
for i, row in enumerate(rows[:10], start=1):
|
||||
raw = row.get("Datum")
|
||||
parsed = parse_czech_date(raw)
|
||||
print(f"{i:02d}. raw={repr(raw)} -> parsed={parsed}")
|
||||
|
||||
input("\n🔸 Stiskni Enter pro pokračování nebo ukončení... ")
|
||||
# Save to Excel
|
||||
df.to_excel(EXPORT_PATH, index=False)
|
||||
print(f"📊 Excel export hotov:\n{EXPORT_PATH}")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
if not CSV_PATH.exists():
|
||||
raise SystemExit(f"❌ Soubor {CSV_PATH} nenalezen.")
|
||||
main()
|
||||
dump_all_transactions()
|
||||
|
||||
35
50 Dekurs.py
35
50 Dekurs.py
@@ -20,26 +20,20 @@ from pathlib import Path
|
||||
from striprtf.striprtf import rtf_to_text
|
||||
from openpyxl.styles import Font, Alignment, PatternFill, Border, Side
|
||||
from openpyxl.utils import get_column_letter
|
||||
from Functions import get_medicus_connection
|
||||
|
||||
# ================== CONFIGURATION ==================
|
||||
FDB_PATH = r"z:\Medicus 3\data\MEDICUS.FDB"
|
||||
EXPORT_DIR = Path(r"u:\Dropbox\!!!Days\Downloads Z230")
|
||||
|
||||
# calculate last 2 months dynamically
|
||||
DATE_FROM = (datetime.now() - timedelta(days=365)).strftime("%Y-%m-%d")
|
||||
# calculate last 2 months dynamically (now set to 10 days for testing)
|
||||
DATE_FROM = (datetime.now() - timedelta(days=10)).strftime("%Y-%m-%d")
|
||||
|
||||
timestamp = datetime.now().strftime("%Y-%m-%d_%H-%M-%S")
|
||||
xlsx_path = EXPORT_DIR / f"{timestamp}_Dekurz (poslední rok).xlsx"
|
||||
|
||||
# ================== FIREBIRD CONNECTION ==================
|
||||
conn = fb.connect(
|
||||
host="192.168.1.4",
|
||||
port=3050,
|
||||
database=FDB_PATH,
|
||||
user="SYSDBA",
|
||||
password="masterkey",
|
||||
charset="WIN1250",
|
||||
)
|
||||
conn = get_medicus_connection()
|
||||
|
||||
def query_df(sql, params=None):
|
||||
cur = conn.cursor()
|
||||
@@ -85,21 +79,29 @@ def safe_rtf_to_text(x):
|
||||
|
||||
df["DEKURS"] = df["DEKURS"].apply(safe_rtf_to_text)
|
||||
|
||||
df.replace({r'(\r\n|\r|\n)': r'\r\n'}, regex=True, inplace=True)
|
||||
df.replace({r'[\ud800-\udfff\x00-\x08\x0B-\x0C\x0E-\x1F\x7F]+': ''},
|
||||
regex=True, inplace=True)
|
||||
df.replace({r'(\r\n){2,}': r'\r\n', r'(\r\n)+$': ''},
|
||||
regex=True, inplace=True)
|
||||
# --- Normalize and clean newlines ---
|
||||
df["DEKURS"] = (
|
||||
df["DEKURS"]
|
||||
.replace(r"(\r\n|\r|\n)+", "\n", regex=True) # unify newlines
|
||||
.replace(r"\n{2,}", "\n", regex=True) # collapse multiple blank lines
|
||||
.str.strip() # trim leading/trailing blanks
|
||||
)
|
||||
|
||||
# --- Remove invalid control characters ---
|
||||
df.replace({r"[\ud800-\udfff\x00-\x08\x0B-\x0C\x0E-\x1F\x7F]+": ""}, regex=True, inplace=True)
|
||||
|
||||
# --- Merge patient name ---
|
||||
df["PACIENT"] = df["PRIJMENI"].fillna("") + ", " + df["JMENO"].fillna("")
|
||||
df.drop(columns=["PRIJMENI", "JMENO"], inplace=True)
|
||||
|
||||
# --- Rename and format columns ---
|
||||
df.rename(columns={"ZKRATKA": "LEKAR", "VYKONY_DNE": "VYKONY DNE"}, inplace=True)
|
||||
df["DATUM"] = pd.to_datetime(df["DATUM"], errors="coerce").dt.date
|
||||
df.drop(columns=[c for c in df.columns if "ASCII" in c.upper()], inplace=True, errors="ignore")
|
||||
|
||||
desired_order = ["DATUM", "RODCIS", "PACIENT", "LEKAR", "VYKONY DNE", "DEKURS"]
|
||||
df = df[[c for c in desired_order if c in df.columns]]
|
||||
|
||||
# ================== CLEANUP OLD FILES ==================
|
||||
for old_file in EXPORT_DIR.glob("*Dekurz (poslední rok)*.xlsx"):
|
||||
try:
|
||||
@@ -107,11 +109,12 @@ for old_file in EXPORT_DIR.glob("*Dekurz (poslední rok)*.xlsx"):
|
||||
print(f"🧹 Deleted old file: {old_file.name}")
|
||||
except Exception as e:
|
||||
print(f"⚠️ Could not delete {old_file.name}: {e}")
|
||||
|
||||
# ================== EXPORT TO EXCEL ==================
|
||||
with pd.ExcelWriter(xlsx_path, engine="openpyxl") as writer:
|
||||
df.to_excel(writer, index=False, sheet_name="Dekurz")
|
||||
ws = writer.sheets["Dekurz"]
|
||||
|
||||
ws.freeze_panes = "F2" #zamčení prvního řádku a sloupců A:F
|
||||
# ----- Bright yellow header -----
|
||||
header_fill = PatternFill(start_color="FFFF00", end_color="FFFF00", fill_type="solid")
|
||||
for cell in ws[1]:
|
||||
|
||||
@@ -7,14 +7,10 @@ Show decoded physician notes (RTF → plain text) directly in console.
|
||||
|
||||
import fdb
|
||||
from striprtf.striprtf import rtf_to_text
|
||||
from Functions import get_medicus_connection
|
||||
|
||||
# ===== connection =====
|
||||
con = fdb.connect(
|
||||
dsn='localhost:z:\\Medicus 3\\data\\medicus.fdb',
|
||||
user='sysdba',
|
||||
password='masterkey',
|
||||
charset='WIN1250'
|
||||
)
|
||||
con = get_medicus_connection()
|
||||
cur = con.cursor()
|
||||
|
||||
# ===== pick a few recent records =====
|
||||
|
||||
31
70 PDF read ZPMVCR.py
Normal file
31
70 PDF read ZPMVCR.py
Normal file
@@ -0,0 +1,31 @@
|
||||
|
||||
import pdfplumber
|
||||
import pandas as pd
|
||||
from pathlib import Path
|
||||
|
||||
pdf_path = Path(r"u:\Dropbox\!!!Days\Downloads Z230\prehled 09_2025 zpmvcr.pdf")
|
||||
xlsx_path = pdf_path.with_suffix(".xlsx")
|
||||
|
||||
all_tables = []
|
||||
|
||||
with pdfplumber.open(pdf_path) as pdf:
|
||||
for i, page in enumerate(pdf.pages, start=1):
|
||||
tables = page.extract_tables()
|
||||
if not tables:
|
||||
continue
|
||||
table = tables[0]
|
||||
# Convert to DataFrame, first row = header
|
||||
df = pd.DataFrame(table[1:], columns=table[0])
|
||||
df["page"] = i
|
||||
all_tables.append(df)
|
||||
|
||||
if not all_tables:
|
||||
print("❌ No tables found.")
|
||||
else:
|
||||
df_all = pd.concat(all_tables, ignore_index=True)
|
||||
print("✅ Combined shape:", df_all.shape)
|
||||
print(df_all.head())
|
||||
|
||||
# Save to Excel
|
||||
df_all.to_excel(xlsx_path, index=False)
|
||||
print(f"💾 Saved to: {xlsx_path}")
|
||||
111
80 CtiKapitaceZTabulkyFAK.py
Normal file
111
80 CtiKapitaceZTabulkyFAK.py
Normal file
@@ -0,0 +1,111 @@
|
||||
import re
|
||||
import pandas as pd
|
||||
import firebirdsql as fb
|
||||
from datetime import datetime, timedelta
|
||||
from pathlib import Path
|
||||
from striprtf.striprtf import rtf_to_text
|
||||
from openpyxl.styles import Font, Alignment, PatternFill, Border, Side
|
||||
from openpyxl.utils import get_column_letter
|
||||
import textwrap
|
||||
|
||||
# ================== CONFIGURATION ==================
|
||||
FDB_PATH = r"z:\Medicus 3\data\MEDICUS.FDB"
|
||||
EXPORT_DIR = Path(r"u:\Dropbox\!!!Days\Downloads Z230")
|
||||
|
||||
# ================== FIREBIRD CONNECTION ==================
|
||||
conn = fb.connect(
|
||||
host="192.168.1.4",
|
||||
port=3050,
|
||||
database=FDB_PATH,
|
||||
user="SYSDBA",
|
||||
password="masterkey",
|
||||
charset="WIN1250",
|
||||
)
|
||||
|
||||
def query_df(sql, params=None):
|
||||
cur = conn.cursor()
|
||||
cur.execute(sql, params or ())
|
||||
rows = cur.fetchall()
|
||||
cols = [d[0].strip().lower() for d in cur.description] # 👈 normalize
|
||||
return pd.DataFrame(rows, columns=cols)
|
||||
# ================== QUERY ==================
|
||||
sql = """
|
||||
SELECT id, cisfak, poj, datkapod, datkapdo, kapdetail
|
||||
FROM fak
|
||||
WHERE EXTRACT(YEAR FROM datkapod) = 2025
|
||||
AND EXTRACT(MONTH FROM datkapod) = 9
|
||||
AND poj = '211'
|
||||
"""
|
||||
df = query_df(sql)
|
||||
|
||||
# print(df.columns.tolist())
|
||||
# print(df.head())
|
||||
|
||||
# Display the first KAPDETAIL text, wrapped nicely
|
||||
kap_text = df.loc[0, 'kapdetail']
|
||||
# print("\n".join(textwrap.wrap(kap_text, width=100)))
|
||||
|
||||
# ========== SOURCE STRING ==========
|
||||
text = kap_text
|
||||
|
||||
# Extract triplets: patientid;age|price;
|
||||
pattern = r"(\d{4});(\d{1,3})\|([\d.]+);"
|
||||
matches = re.findall(pattern, text)
|
||||
|
||||
# Create dataframe
|
||||
dfdavka = pd.DataFrame(matches, columns=["patientid", "age", "price"])
|
||||
|
||||
# ✅ Fix small typo: use dfdavka (not df) for conversions
|
||||
dfdavka["patientid"] = dfdavka["patientid"].astype(int)
|
||||
dfdavka["age"] = dfdavka["age"].astype(int)
|
||||
dfdavka["price"] = dfdavka["price"].astype(float)
|
||||
|
||||
# ========== LOAD KAR ==========
|
||||
sql = "SELECT idpac, rodcis FROM kar"
|
||||
dfkar = query_df(sql)
|
||||
|
||||
# ========== MERGE ==========
|
||||
dfmerged = pd.merge(dfdavka, dfkar, left_on="patientid", right_on="idpac", how="left")
|
||||
|
||||
# Optional: reorder columns
|
||||
dfmerged = dfmerged[["patientid", "rodcis", "age", "price"]]
|
||||
|
||||
print(dfmerged.head())
|
||||
print(dfmerged.info())
|
||||
|
||||
# ========== OPTIONAL EXPORT ==========
|
||||
# outfile = EXPORT_DIR / "kapdetail_merged.xlsx"
|
||||
# dfmerged.to_excel(outfile, index=False)
|
||||
# print(f"✅ Exported to {outfile}")
|
||||
|
||||
|
||||
|
||||
# ========== 1️⃣ Load Excel and prepare dfpoj ==========
|
||||
xlsx_path = Path(r"u:\Dropbox\!!!Days\Downloads Z230\prehled 09_2025 zpmvcr.xlsx")
|
||||
df = pd.read_excel(xlsx_path)
|
||||
|
||||
print("Columns in Excel:", df.columns.tolist())
|
||||
|
||||
# Select 2nd column (index 1)
|
||||
dfpoj = df.iloc[:, [1]].copy()
|
||||
dfpoj.columns = ["rodcis"] # give proper name
|
||||
dfpoj["rodcis"] = dfpoj["rodcis"].astype(str).str.strip()
|
||||
|
||||
print(dfpoj.head())
|
||||
|
||||
# ========== 2️⃣ Compare dfmerged vs dfpoj ==========
|
||||
dfmerged["rodcis"] = dfmerged["rodcis"].astype(str).str.strip()
|
||||
|
||||
# Find those in dfmerged but not in dfpoj
|
||||
df_missing = dfmerged[~dfmerged["rodcis"].isin(dfpoj["rodcis"])].copy()
|
||||
|
||||
print(f"❌ Počet pacientů v dfmerged, kteří NEJSOU v dfpoj: {len(df_missing)}")
|
||||
print(df_missing.head())
|
||||
|
||||
# ========== 3️⃣ (Optional) Export differences ==========
|
||||
EXPORT_DIR = Path(r"u:\Dropbox\!!!Days\Downloads Z230")
|
||||
timestamp = datetime.now().strftime("%Y-%m-%d_%H-%M-%S")
|
||||
xlsx_out = EXPORT_DIR / f"chybějící_pacienti_{timestamp}.xlsx"
|
||||
|
||||
df_missing.to_excel(xlsx_out, index=False)
|
||||
print(f"✅ Výsledek uložen do {xlsx_out}")
|
||||
Reference in New Issue
Block a user