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.gitignore vendored Normal file
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*.gpc
*.csv
.venv

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# Default ignored files
/shelf/
/workspace.xml
# Editor-based HTTP Client requests
/httpRequests/
# Datasource local storage ignored files
/dataSources/
/dataSources.local.xml

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<component name="InspectionProjectProfileManager">
<settings>
<option name="USE_PROJECT_PROFILE" value="false" />
<version value="1.0" />
</settings>
</component>

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<?xml version="1.0" encoding="UTF-8"?>
<project version="4">
<component name="Black">
<option name="sdkName" value="Python 3.13 (wise)" />
</component>
<component name="ProjectRootManager" version="2" project-jdk-name="Python 3.13 (wise)" project-jdk-type="Python SDK" />
</project>

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<?xml version="1.0" encoding="UTF-8"?>
<project version="4">
<component name="ProjectModuleManager">
<modules>
<module fileurl="file://$PROJECT_DIR$/.idea/wise.iml" filepath="$PROJECT_DIR$/.idea/wise.iml" />
</modules>
</component>
</project>

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<?xml version="1.0" encoding="UTF-8"?>
<module type="PYTHON_MODULE" version="4">
<component name="NewModuleRootManager">
<content url="file://$MODULE_DIR$">
<excludeFolder url="file://$MODULE_DIR$/.venv" />
</content>
<orderEntry type="jdk" jdkName="Python 3.13 (wise)" jdkType="Python SDK" />
<orderEntry type="sourceFolder" forTests="false" />
</component>
<component name="PyDocumentationSettings">
<option name="format" value="PLAIN" />
<option name="myDocStringFormat" value="Plain" />
</component>
</module>

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allegro.py Normal file
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import csv
import chardet
from datetime import datetime
from gpc import Data, Header, TransactionCode, CURRENCIES_GPC
from utils import extract_order_number, extract_numbers, parse_date
import mysql.connector
import re
def load_allegro_orders():
# Define your connection parameters.
conn = mysql.connector.connect(
host="afrodite.my-devbox.cloud",
port=3307,
user="vat_dev",
password="i!532&hchjJrGmTSV37i7xPfL&",
database="remotecont1"
)
# Use a cursor that returns rows as dictionaries.
cursor = conn.cursor(dictionary=True)
# Your SQL query.
query = """
SELECT o.* \
FROM rcd_orders o
WHERE o.allegro_order_id IS NOT NULL
"""
cursor.execute(query)
allegro_orders = cursor.fetchall() # results is now a list of dictionaries
cursor.close()
conn.close()
return allegro_orders
def search_allegro_order(allegro_id):
global allegro_orders
for order in allegro_orders:
if order["allegro_login"] == allegro_id:
return order["orders_id"]
return 0
def convert_csv_to_gpc(csv_file_path, gpc_file_path, account_number, currency, mapping):
gpc_lines = {
"payu": [],
"przelewy24": [],
"allegro finance": []
}
account_numbers = {
"payu": 4113600111,
"przelewy24": 4113600222,
"allegro finance": 4113600333
}
# Create and add the header
header = Header(
account=4113600111,
account_name=currency.ljust(20),
old_date=datetime.strptime("01-03-20", "%d-%m-%y"),
old_balance=78449,
old_sign='+',
new_balance=6215449,
new_sign='+',
turnover_debet=6585600,
turnover_debet_sign='0',
turnover_credit=127226,
turnover_credit_sign='0',
transaction_list_no=3,
date=datetime.now()
)
gpc_lines["payu"].append(header.to_string())
# Create and add the header
header = Header(
account=4113600222,
account_name=currency.ljust(20),
old_date=datetime.strptime("01-03-20", "%d-%m-%y"),
old_balance=78449,
old_sign='+',
new_balance=6215449,
new_sign='+',
turnover_debet=6585600,
turnover_debet_sign='0',
turnover_credit=127226,
turnover_credit_sign='0',
transaction_list_no=3,
date=datetime.now()
)
gpc_lines["przelewy24"].append(header.to_string())
# Create and add the header
header = Header(
account=4113600333,
account_name=currency.ljust(20),
old_date=datetime.strptime("01-03-20", "%d-%m-%y"),
old_balance=78449,
old_sign='+',
new_balance=6215449,
new_sign='+',
turnover_debet=6585600,
turnover_debet_sign='0',
turnover_credit=127226,
turnover_credit_sign='0',
transaction_list_no=3,
date=datetime.now()
)
gpc_lines["allegro finance"].append(header.to_string())
if mapping['forced_encoding'] is not None:
detected_encoding = mapping['forced_encoding']
print(f"Forced encoding: {detected_encoding}")
else:
with open(csv_file_path, 'rb') as f:
rawdata = f.read(1024) # Read a small part of the file
result = chardet.detect(rawdata)
detected_encoding = result['encoding']
print(f"Detected encoding: {detected_encoding}")
with open(csv_file_path, mode='r', encoding=detected_encoding) as csv_file:
reader = csv.DictReader(csv_file, delimiter=mapping['delimiter']) if mapping['is_dict_mapping'] else csv.reader(csv_file, delimiter=mapping['delimiter'])
if not mapping['is_dict_mapping']:
next(reader)
for row in reader:
source_name = row[mapping['source_name']]
reference = search_allegro_order(source_name.split(";")[0].strip()) if ";" in row[mapping['source_name']] else 0
transaction_id = reference
direction = row[mapping['direction']].lower() if mapping['direction'] is not None else None
payer_account = extract_numbers(row[mapping['payer_account']].replace("Rachunek nadawcy: ", "").replace(" ", ""))[:16].ljust(16) if mapping['payer_number_exists'] else 0
if payer_account != 0:
if payer_account.strip() == "":
payer_account = 0
value_str = row[mapping['source_amount']]
match = re.search(r'[-+]?\d*\.?\d+', value_str)
if match:
source_amount = float(match.group(0)) * 100
else:
source_amount = 0.0
created_on = parse_date(row[mapping['created_on']])
# Determine transaction type
if(direction is None):
if source_amount > 0:
transaction_code = TransactionCode.CREDIT
else:
transaction_code = TransactionCode.DEBET
else:
if direction == "out":
transaction_code = TransactionCode.DEBET
else:
transaction_code = TransactionCode.CREDIT
# Convert currency
currency_code = CURRENCIES_GPC.get("CZK", "0000")
# Create GPC Data object
gpc_data = Data(
account=account_numbers[row[mapping['wallet_source']].lower()],
payer_account=0,
no=reference,
balance=source_amount,
code=transaction_code,
variable=reference,
constant_symbol=0,
bank_code=0,
specific_symbol=0,
client_name= "VAT VATu" if row[mapping['payment_type']] == "wypłata środków" else "",
currency=currency_code,
date=created_on
)
gpc_lines[row[mapping['wallet_source']].lower()].append(gpc_data.to_string())
with open("allegro_payu.gpc", mode='w', encoding='utf-8') as gpc_file:
gpc_file.writelines(gpc_lines["payu"])
with open("allegro_przelewy.gpc", mode='w', encoding='utf-8') as gpc_file:
gpc_file.writelines(gpc_lines["przelewy24"])
with open("allegro_finance.gpc", mode='w', encoding='utf-8') as gpc_file:
gpc_file.writelines(gpc_lines["allegro finance"])
print(f"GPC file successfully created: allegro_payu.gpc")
print(f"GPC file successfully created: allegro_przelewy.gpc")
print(f"GPC file successfully created: allegro_finance.gpc")
# Example mappings
mapping_allegro = {
'transaction_id': 2,
'reference': None,
'direction': None,
'source_name': 5,
'source_amount': 8,
'source_currency': 4,
'payer_account': None,
'created_on': 0,
'payment_type': 3,
'wallet_source': 4,
'acc_sum': 9,
'delimiter': ",",
'is_dict_mapping': False,
'use_transaction_id': False,
'payer_number_exists': False,
'use_source_name': False,
'forced_encoding': None
}
allegro_orders = load_allegro_orders()
# Example usage:
convert_csv_to_gpc("allegro_payments.csv", "allegro_payments.gpc", account_number=3214724742, currency="PLN", mapping=mapping_allegro)

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gpc.py Normal file
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from datetime import datetime
from enum import Enum
class RecordType(str, Enum):
HEADER = "074"
ITEM = "075"
class TransactionCode(int, Enum):
DEBET = 1 # 1 = položka debet
CREDIT = 2 # 2 = položka kredit
STORNO_DEBET = 4 # 4 = storno položky debet
STORNO_CREDIT = 5 # 5 = storno položky kredit
CURRENCIES_GPC = {
"AUD": "0036", "CAD": "0124", "CNY": "0156", "CZK": "0203", "DKK": "0208",
"EUR": "0978", "GBP": "0826", "HRK": "0191", "HUF": "0348", "CHF": "0756",
"JPY": "0392", "NOK": "0578", "PLN": "0985", "RON": "0946", "RUB": "0643",
"SEK": "0752", "TRY": "0949", "USD": "0840"
}
class BaseRecord:
def __init__(self, record_type: RecordType, account: int):
self.record_type = record_type
self.account = account
class Header(BaseRecord):
def __init__(self, account: int, account_name: str, old_date: datetime, old_balance: int,
old_sign: str, new_balance: int, new_sign: str, turnover_debet: int,
turnover_debet_sign: str, turnover_credit: int, turnover_credit_sign: str,
transaction_list_no: int, date: datetime):
super().__init__(RecordType.HEADER, account)
self.account_name = account_name[:20].ljust(20)
self.old_date = old_date.strftime("%d%m%y")
self.old_balance = old_balance
self.old_sign = old_sign
self.new_balance = new_balance
self.new_sign = new_sign
self.turnover_debet = turnover_debet
self.turnover_debet_sign = turnover_debet_sign
self.turnover_credit = turnover_credit
self.turnover_credit_sign = turnover_credit_sign
self.transaction_list_no = transaction_list_no
self.date = date.strftime("%d%m%y")
def to_string(self):
return (f"074{str(self.account)[:16].zfill(16)}{str(self.account_name)[:20].zfill(20)}"
f"{self.old_date}{self.old_balance:014}{self.old_sign}"
f"{self.new_balance:014}{self.new_sign}"
f"{int(self.turnover_debet):014}{self.turnover_debet_sign}"
f"{int(self.turnover_credit):014}{self.turnover_credit_sign}"
f"{self.transaction_list_no:03}{self.date}{' '.ljust(14)}\r\n")
class Data(BaseRecord):
def __init__(self, account: int, payer_account: int, no: int, balance: float, code: TransactionCode,
variable: int, constant_symbol: int, bank_code: int, specific_symbol: int,
client_name: str, currency: str, date: datetime):
super().__init__(RecordType.ITEM, account)
self.payer_account = payer_account
self.no = no
self.balance = abs(balance)
self.code = code
self.variable = variable
self.constant_symbol = constant_symbol
self.bank_code = bank_code
self.specific_symbol = specific_symbol
self.client_name = client_name
self.currency = currency
self.date = date.strftime("%d%m%y")
def to_string(self):
return (f"{self.record_type.value:03}{str(self.account)[:16].zfill(16)}{str(self.payer_account).rjust(16, '0')[:16]}"
f"{str(self.no)[:13].zfill(13)}{int(self.balance):012}{self.code.value:1}{self.variable:010}"
f"{self.constant_symbol:010}{self.specific_symbol:010}"
f"{'0'*6}{str(self.client_name)[:20].ljust(20)}{'0'}{self.currency}{self.date}\r\n")

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paynl_aviza.py Normal file
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import csv
import pandas as pd
import chardet
from datetime import datetime
from gpc import Data, Header, TransactionCode, CURRENCIES_GPC
from utils import extract_order_number, extract_numbers, parse_date
def load_bank_transactions(csv_file):
"""
Loads the bank transactions CSV file into a DataFrame and returns it.
:param csv_file: Path to the bank transactions CSV file.
:return: A pandas DataFrame containing the transactions.
"""
df = pd.read_csv(csv_file, delimiter=';', dtype=str)
# Ensure the required column exists
if 'Zpráva pro příjemce' not in df.columns:
raise ValueError("The CSV file does not contain the required column 'Zpráva pro příjemce'.")
return df
def search_bank_transaction(df, search_string):
"""
Searches for a given string in the 'Zpráva pro příjemce' column of the loaded DataFrame.
:param df: Pandas DataFrame containing bank transactions.
:param search_string: String to search for in the 'Zpráva pro příjemce' column.
:return: The first matching row as a dictionary or None if not found.
"""
matching_row = df[df['Zpráva pro příjemce'].str.contains(search_string, na=False, case=False)]
return matching_row.iloc[0].to_dict() if not matching_row.empty else None
def convert_csv_to_gpc(csv_file_path, gpc_file_path, account_number, currency, mapping):
gpc_lines = []
global transactions_df
if mapping['forced_encoding'] is not None:
detected_encoding = mapping['forced_encoding']
print(f"Forced encoding: {detected_encoding}")
else:
with open(csv_file_path, 'rb') as f:
rawdata = f.read(1024) # Read a small part of the file
result = chardet.detect(rawdata)
detected_encoding = result['encoding']
print(f"Detected encoding: {detected_encoding}")
with open(csv_file_path, mode='r', encoding=detected_encoding) as csv_file:
reader = csv.DictReader(csv_file, delimiter=mapping['delimiter']) if mapping['is_dict_mapping'] else csv.reader(csv_file, delimiter=mapping['delimiter'])
if not mapping['is_dict_mapping']:
next(reader)
total_payout = 0.0
first = True
clearing_id = ""
for row in reader:
if first:
clearing_id = row[mapping['CLEARING_ID']]
first = False
reference = extract_order_number(row[mapping['reference']])
transaction_id = extract_numbers(row[mapping['transaction_id']]) if mapping['use_transaction_id'] else reference
direction = row[mapping['direction']].lower() if mapping['direction'] is not None else None
source_name = row[mapping['source_name']].replace("Nazwa nadawcy: ", "")[:20].ljust(20) if mapping['use_source_name'] else ""
payer_account = extract_numbers(row[mapping['payer_account']].replace("Rachunek nadawcy: ", "").replace(" ", ""))[:16].ljust(16) if mapping['payer_number_exists'] else 0
if payer_account != 0:
if payer_account.strip() == "":
payer_account = 0
source_amount = float(row[mapping['source_amount']].replace(',', '.')) * 100 # Convert to cents
created_on = parse_date(row[mapping['created_on']])
# Determine transaction type
if(direction is None):
if source_amount > 0:
transaction_code = TransactionCode.CREDIT
else:
transaction_code = TransactionCode.DEBET
else:
if direction == "out":
transaction_code = TransactionCode.DEBET
else:
transaction_code = TransactionCode.CREDIT
# Convert currency
currency_code = CURRENCIES_GPC.get("CZK", "0000")
# Create GPC Data object
gpc_data = Data(
account=account_number,
payer_account=payer_account,
no=transaction_id,
balance=source_amount,
code=transaction_code,
variable=int(reference) if reference.isdigit() else 0,
constant_symbol=0,
bank_code=0,
specific_symbol=0,
client_name=source_name,
currency=currency_code,
date=created_on
)
gpc_lines.append(gpc_data.to_string())
total_payout += source_amount
# add fees
# fees_data = Data(
# account=account_number,
# payer_account=0,
# no=0,
# balance=total_fees,
# code=transaction_code,
# variable=0,
# constant_symbol=0,
# bank_code=0,
# specific_symbol=0,
# client_name="",
# currency=CURRENCIES_GPC.get("CZK", "0000"),
# date=created_on
# )
#
# gpc_lines.append(gpc_data.to_string())
corresponding_transaction = search_bank_transaction(transactions_df, clearing_id)
# vyuctovani row
payout_data = Data(
account=account_number,
payer_account=0,
no=0,
balance=total_payout,
code=TransactionCode.DEBET,
variable=666111222,
# variable=corresponding_transaction['Zpráva pro příjemce'].split(',')[-1].strip(),
constant_symbol=0,
bank_code=0,
specific_symbol=0,
client_name="",
currency=CURRENCIES_GPC.get("CZK", "0000"),
date=parse_date(corresponding_transaction['Datum'])
)
gpc_lines.append(payout_data.to_string())
# Create and add the header
header = Header(
account=account_number,
account_name=currency.ljust(20),
old_date=datetime.strptime("01-03-20", "%d-%m-%y"),
old_balance=0,
old_sign='+',
new_balance=0,
new_sign='+',
turnover_debet=total_payout,
turnover_debet_sign='0',
turnover_credit=total_payout,
turnover_credit_sign='0',
transaction_list_no=3,
date=datetime.now()
)
gpc_lines.insert(0, header.to_string())
with open(gpc_file_path, mode='w', encoding='utf-8') as gpc_file:
gpc_file.writelines(gpc_lines)
print(f"GPC file successfully created: {gpc_file_path}")
# Example mappings
mapping_paynl = {
'transaction_id': 'PAYMENT_SESSION_ID',
'reference': 'EXTRA_1',
'direction': None,
'source_name': 'CONSUMER_NAME',
'source_amount': 'TURNOVER_TOTAL',
'source_currency': '',
'payer_account': 'PAYMENT_SESSION_ID',
'created_on': 'TRANSACTION_DATE',
'CLEARING_ID': 'CLEARING_ID',
'fees': 'COSTS',
'delimiter': ";",
'is_dict_mapping': True,
'use_transaction_id': True,
'payer_number_exists': False,
'use_source_name': False,
'forced_encoding': None
}
transactions_df = load_bank_transactions("bank_statement.csv")
# Example usage:
convert_csv_to_gpc("Specification clearing 2024-05-10.csv", "avizo_paynl_test.gpc", account_number=2801379531, currency="EUR", mapping=mapping_paynl)
# convert_csv_to_gpc("pko_input.csv", "pko_output.gpc", account_number=95102013900000630206821286, currency="PLN", mapping=mapping_pko)
# convert_csv_to_gpc("sparkasse_input.csv", "sparkasse_output.gpc", account_number=95850503000221267034, currency="EUR", mapping=mapping_sparkasse)

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requirements.txt Normal file
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chardet~=5.2.0
mysql-connector-python~=9.2.0
pandas~=2.2.3

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utils.py Normal file
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import re
from datetime import datetime
def extract_numbers(text: str) -> str:
"""Extracts only digits from the given string."""
return ''.join(re.findall(r'\d+', text))
def extract_order_number(reference: str) -> str:
"""Extracts a 6-digit order number from the reference field.
If no 6-digit number is found, returns "0".
"""
match = re.search(r'\b\d{6}\b', reference)
return match.group(0) if match else "0"
def parse_date(date_str):
"""Tries multiple date formats to handle different CSV structures."""
date_formats = [
"%Y-%m-%d %H:%M:%S", # 2025-02-06 10:35:44
"%d.%m.%Y %H:%M", # 31.12.2024 21:17
"%Y-%m-%d", # 2025-02-06
"%d-%m-%Y", # 06-02-2025
"%d.%m.%Y", # 06.02.2025
"%d.%m.%y" # 06.02.25
]
for fmt in date_formats:
try:
return datetime.strptime(date_str, fmt)
except ValueError:
continue # Try the next format
raise ValueError(f"Unsupported date format: {date_str}") # Raise error if none match

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wise.py Normal file
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import csv
import chardet
from datetime import datetime
from gpc import Data, Header, TransactionCode, CURRENCIES_GPC
from utils import extract_order_number, extract_numbers, parse_date
def convert_csv_to_gpc(csv_file_path, gpc_file_path, account_number, currency, mapping):
gpc_lines = []
# Create and add the header
header = Header(
account=account_number,
account_name=currency.ljust(20),
old_date=datetime.strptime("01-03-20", "%d-%m-%y"),
old_balance=78449,
old_sign='+',
new_balance=6215449,
new_sign='+',
turnover_debet=6585600,
turnover_debet_sign='0',
turnover_credit=127226,
turnover_credit_sign='0',
transaction_list_no=3,
date=datetime.now()
)
gpc_lines.append(header.to_string())
if mapping['forced_encoding'] is not None:
detected_encoding = mapping['forced_encoding']
print(f"Forced encoding: {detected_encoding}")
else:
with open(csv_file_path, 'rb') as f:
rawdata = f.read(1024) # Read a small part of the file
result = chardet.detect(rawdata)
detected_encoding = result['encoding']
print(f"Detected encoding: {detected_encoding}")
with open(csv_file_path, mode='r', encoding=detected_encoding) as csv_file:
reader = csv.DictReader(csv_file, delimiter=mapping['delimiter']) if mapping['is_dict_mapping'] else csv.reader(csv_file, delimiter=mapping['delimiter'])
if not mapping['is_dict_mapping']:
next(reader)
for row in reader:
reference = extract_order_number(row[mapping['reference']])
transaction_id = extract_numbers(row[mapping['transaction_id']]) if mapping['use_transaction_id'] else reference
direction = row[mapping['direction']].lower() if mapping['direction'] is not None else None
source_name = row[mapping['source_name']].replace("Nazwa nadawcy: ", "")[:20].ljust(20) if mapping['use_source_name'] else ""
payer_account = extract_numbers(row[mapping['payer_account']].replace("Rachunek nadawcy: ", "").replace(" ", ""))[:16].ljust(16) if mapping['payer_number_exists'] else 0
if payer_account != 0:
if payer_account.strip() == "":
payer_account = 0
source_amount = float(row[mapping['source_amount']].replace(',', '.')) * 100 # Convert to cents
created_on = parse_date(row[mapping['created_on']])
# Determine transaction type
if(direction is None):
if source_amount > 0:
transaction_code = TransactionCode.CREDIT
else:
transaction_code = TransactionCode.DEBET
else:
if direction == "out":
transaction_code = TransactionCode.DEBET
else:
transaction_code = TransactionCode.CREDIT
# Convert currency
currency_code = CURRENCIES_GPC.get("CZK", "0000")
# Create GPC Data object
gpc_data = Data(
account=account_number,
payer_account=payer_account,
no=transaction_id,
balance=source_amount,
code=transaction_code,
variable=int(reference) if reference.isdigit() else 0,
constant_symbol=0,
bank_code=0,
specific_symbol=0,
client_name=source_name,
currency=currency_code,
date=created_on
)
gpc_lines.append(gpc_data.to_string())
with open(gpc_file_path, mode='w', encoding='utf-8') as gpc_file:
gpc_file.writelines(gpc_lines)
print(f"GPC file successfully created: {gpc_file_path}")
# Example mappings
mapping_wise = {
'transaction_id': 'ID',
'reference': 'Reference',
'direction': 'Direction',
'source_name': 'Source name',
'source_amount': 'Source amount (after fees)',
'source_currency': 'Source currency',
'payer_account': 'Source currency',
'created_on': 'Created on',
'delimiter': ",",
'is_dict_mapping': True,
'use_transaction_id': False,
'payer_number_exists': False,
'use_source_name': False,
'forced_encoding': None
}
mapping_pko = {
'transaction_id': 2,
'reference': 9,
'direction': None,
'source_name': 7,
'source_amount': 3,
'source_currency': 4,
'payer_account': 6,
'created_on': 1,
'delimiter': ",",
'is_dict_mapping': False,
'use_transaction_id': False,
'payer_number_exists': True,
'use_source_name': False,
'forced_encoding': 'iso-8859-2'
}
mapping_sparkasse = {
'transaction_id': 7,
'reference': 4,
'direction': None,
'source_name': 11,
'source_amount': 14,
'source_currency': 15,
'payer_account': 12,
'created_on': 1,
'delimiter': ";",
'is_dict_mapping': False,
'use_transaction_id': False,
'payer_number_exists': True,
'use_source_name': False,
'forced_encoding': None
}
# Example usage:
convert_csv_to_gpc("leden-2025-huf.csv", "wise-huf-2025.gpc", account_number=330005602964780100, currency="HUF", mapping=mapping_wise)
# convert_csv_to_gpc("pko_input.csv", "pko_output.gpc", account_number=95102013900000630206821286, currency="PLN", mapping=mapping_pko)
# convert_csv_to_gpc("sparkasse_input.csv", "sparkasse_output.gpc", account_number=95850503000221267034, currency="EUR", mapping=mapping_sparkasse)