Tool to load bank data and convert it to a monthly overview.
Work in progress. Currently a startup file will look like this:
By default the tool wil look for a base folder along the following structure:
import logging
from pathlib import Path
from bankparser.helpers import get_bank_data
from bankparser.post_processors.extract import Extract
from bankparser.post_processors.label import Label
from bankparser.readers.parse_ing import IngParser
from bankparser.readers.parse_rabo import RaboParser
from bankparser.readers.parser import save_file
from bankparser.reports.monthly_report import make_report
LOGGER = logging.getLogger(__name__)
def make_report_location(base_banking_folder: Path, year: str):
return base_banking_folder.joinpath(
"output/report_{}.txt".format(year)
)
if __name__ == "__main__":
bank_data = get_bank_data()
base_banking_folder = Path(
"~/base_bank_data_folder"
)
# CSV data containing ING bank csv data.
csv_ing_folder = base_banking_folder.joinpath("csv\\ing")
LOGGER.info("ING_FOLDER: %s", csv_ing_folder)
ing_parser = IngParser(bank_data, csv_ing_folder, skip_lines=1)
ing_parser.process_folder()
# CSV data containing Rabo bank transaction data.
csv_rabo_folder = base_banking_folder.joinpath("csv\\rabo")
LOGGER.info("RABO Folder: %s", csv_rabo_folder)
rabo_parser = RaboParser(bank_data, csv_rabo_folder, skip_lines=1)
rabo_parser.process_folder()
# The location to store one big dict containing all above banking data.
out_location = base_banking_folder.joinpath("output/out.json")
LOGGER.info("OUTPUT_FILE: %s", out_location)
save_file(out_location, bank_data)
# A post processor modifying the data dict.
labeller = Label(bank_data, base_banking_folder)
labeller.setup()
labeller.process()
extractor = Extract(bank_data,base_banking_folder)
extractor.setup()
extractor.process()
# Output file contain the year.
make_report(bank_data, "2018",
make_report_location(base_banking_folder, "2018"))