5457db0601
* remove uses of six.py2 in codebase * changes based on pr feedback * Update amazon_mws_api.py Co-authored-by: Ankush Menat <ankush@iwebnotes.com>
176 lines
5.4 KiB
Python
176 lines
5.4 KiB
Python
# coding: utf-8
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from __future__ import unicode_literals
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import datetime
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import zipfile
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from csv import QUOTE_NONNUMERIC
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from six import BytesIO
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import six
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import frappe
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import pandas as pd
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from frappe import _
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from .datev_constants import DataCategory
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def get_datev_csv(data, filters, csv_class):
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"""
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Fill in missing columns and return a CSV in DATEV Format.
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For automatic processing, DATEV requires the first line of the CSV file to
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hold meta data such as the length of account numbers oder the category of
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the data.
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Arguments:
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data -- array of dictionaries
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filters -- dict
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csv_class -- defines DATA_CATEGORY, FORMAT_NAME and COLUMNS
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"""
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empty_df = pd.DataFrame(columns=csv_class.COLUMNS)
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data_df = pd.DataFrame.from_records(data)
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result = empty_df.append(data_df, sort=True)
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if csv_class.DATA_CATEGORY == DataCategory.TRANSACTIONS:
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result['Belegdatum'] = pd.to_datetime(result['Belegdatum'])
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if csv_class.DATA_CATEGORY == DataCategory.ACCOUNT_NAMES:
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result['Sprach-ID'] = 'de-DE'
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data = result.to_csv(
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# Reason for str(';'): https://github.com/pandas-dev/pandas/issues/6035
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sep=str(';'),
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# European decimal seperator
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decimal=',',
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# Windows "ANSI" encoding
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encoding='latin_1',
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# format date as DDMM
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date_format='%d%m',
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# Windows line terminator
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line_terminator='\r\n',
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# Do not number rows
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index=False,
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# Use all columns defined above
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columns=csv_class.COLUMNS,
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# Quote most fields, even currency values with "," separator
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quoting=QUOTE_NONNUMERIC
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)
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data = data.encode('latin_1', errors='replace')
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header = get_header(filters, csv_class)
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header = ';'.join(header).encode('latin_1', errors='replace')
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# 1st Row: Header with meta data
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# 2nd Row: Data heading (Überschrift der Nutzdaten), included in `data` here.
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# 3rd - nth Row: Data (Nutzdaten)
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return header + b'\r\n' + data
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def get_header(filters, csv_class):
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description = filters.get('voucher_type', csv_class.FORMAT_NAME)
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company = filters.get('company')
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datev_settings = frappe.get_doc('DATEV Settings', {'client': company})
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default_currency = frappe.get_value('Company', company, 'default_currency')
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coa = frappe.get_value('Company', company, 'chart_of_accounts')
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coa_short_code = '04' if 'SKR04' in coa else ('03' if 'SKR03' in coa else '')
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header = [
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# DATEV format
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# "DTVF" = created by DATEV software,
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# "EXTF" = created by other software
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'"EXTF"',
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# version of the DATEV format
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# 141 = 1.41,
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# 510 = 5.10,
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# 720 = 7.20
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'700',
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csv_class.DATA_CATEGORY,
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'"%s"' % csv_class.FORMAT_NAME,
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# Format version (regarding format name)
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csv_class.FORMAT_VERSION,
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# Generated on
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datetime.datetime.now().strftime('%Y%m%d%H%M%S') + '000',
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# Imported on -- stays empty
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'',
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# Origin. Any two symbols, will be replaced by "SV" on import.
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'"EN"',
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# I = Exported by
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'"%s"' % frappe.session.user,
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# J = Imported by -- stays empty
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'',
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# K = Tax consultant number (Beraternummer)
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datev_settings.get('consultant_number', '0000000'),
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# L = Tax client number (Mandantennummer)
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datev_settings.get('client_number', '00000'),
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# M = Start of the fiscal year (Wirtschaftsjahresbeginn)
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frappe.utils.formatdate(filters.get('fiscal_year_start'), 'yyyyMMdd'),
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# N = Length of account numbers (Sachkontenlänge)
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str(filters.get('account_number_length', 4)),
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# O = Transaction batch start date (YYYYMMDD)
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frappe.utils.formatdate(filters.get('from_date'), 'yyyyMMdd') if csv_class.DATA_CATEGORY == DataCategory.TRANSACTIONS else '',
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# P = Transaction batch end date (YYYYMMDD)
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frappe.utils.formatdate(filters.get('to_date'), 'yyyyMMdd') if csv_class.DATA_CATEGORY == DataCategory.TRANSACTIONS else '',
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# Q = Description (for example, "Sales Invoice") Max. 30 chars
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'"{}"'.format(_(description)) if csv_class.DATA_CATEGORY == DataCategory.TRANSACTIONS else '',
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# R = Diktatkürzel
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'',
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# S = Buchungstyp
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# 1 = Transaction batch (Finanzbuchführung),
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# 2 = Annual financial statement (Jahresabschluss)
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'1' if csv_class.DATA_CATEGORY == DataCategory.TRANSACTIONS else '',
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# T = Rechnungslegungszweck
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# 0 oder leer = vom Rechnungslegungszweck unabhängig
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# 50 = Handelsrecht
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# 30 = Steuerrecht
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# 64 = IFRS
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# 40 = Kalkulatorik
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# 11 = Reserviert
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# 12 = Reserviert
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'0' if csv_class.DATA_CATEGORY == DataCategory.TRANSACTIONS else '',
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# U = Festschreibung
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# TODO: Filter by Accounting Period. In export for closed Accounting Period, this will be "1"
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'0',
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# V = Default currency, for example, "EUR"
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'"%s"' % default_currency if csv_class.DATA_CATEGORY == DataCategory.TRANSACTIONS else '',
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# reserviert
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'',
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# Derivatskennzeichen
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'',
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# reserviert
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'',
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# reserviert
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'',
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# SKR
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'"%s"' % coa_short_code,
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# Branchen-Lösungs-ID
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'',
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# reserviert
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'',
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# reserviert
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'',
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# Anwendungsinformation (Verarbeitungskennzeichen der abgebenden Anwendung)
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''
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]
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return header
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def zip_and_download(zip_filename, csv_files):
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"""
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Put CSV files in a zip archive and send that to the client.
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Params:
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zip_filename Name of the zip file
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csv_files list of dicts [{'file_name': 'my_file.csv', 'csv_data': 'comma,separated,values'}]
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"""
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zip_buffer = BytesIO()
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zip_file = zipfile.ZipFile(zip_buffer, mode='w', compression=zipfile.ZIP_DEFLATED)
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for csv_file in csv_files:
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zip_file.writestr(csv_file.get('file_name'), csv_file.get('csv_data'))
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zip_file.close()
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frappe.response['filecontent'] = zip_buffer.getvalue()
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frappe.response['filename'] = zip_filename
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frappe.response['type'] = 'binary'
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