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vladimir.buzalka
2025-10-22 16:45:33 +02:00
parent 6d2b4e9858
commit d8d3de7949
6 changed files with 255 additions and 81 deletions
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24
40 Fio 02 diagnostika 2.py Normal file
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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"])

117
40 Fio 03 excel.py Normal file
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#!/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)

100
40 fio 01.py
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@@ -2,11 +2,11 @@
# -*- coding: utf-8 -*-
"""
Import Fio banka CSV export (UTF-8, ; separated, quoted)
into MySQL database `fio.transactions`.
Unique key = (Číslo účtu, ID operace, ID pokynu)
Duplicates are skipped silently.
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
@@ -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()

62
40 fio 02 diagnostika.py
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@@ -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()

2
50 Dekurs.py
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@@ -26,7 +26,7 @@ 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")
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"

31
70 PDF read ZPMVCR.py Normal file
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@@ -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}")