28753268e6
* fix description in header, quote nonnumeric values * fix: truncate 'Buchungstext' to 60 chars
419 lines
12 KiB
Python
419 lines
12 KiB
Python
# coding: utf-8
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"""
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Provide a report and downloadable CSV according to the German DATEV format.
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- Query report showing only the columns that contain data, formatted nicely for
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dispay to the user.
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- CSV download functionality `download_datev_csv` that provides a CSV file with
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all required columns. Used to import the data into the DATEV Software.
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"""
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from __future__ import unicode_literals
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import datetime
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import json
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import zlib
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import zipfile
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import six
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from csv import QUOTE_NONNUMERIC
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from six import BytesIO
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from six import string_types
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import frappe
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from frappe import _
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import pandas as pd
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from .datev_constants import DataCategory
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from .datev_constants import Transactions
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from .datev_constants import DebtorsCreditors
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from .datev_constants import AccountNames
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from .datev_constants import QUERY_REPORT_COLUMNS
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def execute(filters=None):
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"""Entry point for frappe."""
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validate(filters)
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result = get_transactions(filters, as_dict=0)
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columns = QUERY_REPORT_COLUMNS
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return columns, result
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def validate(filters):
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"""Make sure all mandatory filters and settings are present."""
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if not filters.get('company'):
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frappe.throw(_('<b>Company</b> is a mandatory filter.'))
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if not filters.get('from_date'):
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frappe.throw(_('<b>From Date</b> is a mandatory filter.'))
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if not filters.get('to_date'):
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frappe.throw(_('<b>To Date</b> is a mandatory filter.'))
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try:
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frappe.get_doc('DATEV Settings', filters.get('company'))
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except frappe.DoesNotExistError:
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frappe.throw(_('Please create <b>DATEV Settings</b> for Company <b>{}</b>.').format(filters.get('company')))
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def get_transactions(filters, as_dict=1):
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"""
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Get a list of accounting entries.
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Select GL Entries joined with Account and Party Account in order to get the
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account numbers. Returns a list of accounting entries.
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Arguments:
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filters -- dict of filters to be passed to the sql query
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as_dict -- return as list of dicts [0,1]
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"""
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filter_by_voucher = 'AND gl.voucher_type = %(voucher_type)s' if filters.get('voucher_type') else ''
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gl_entries = frappe.db.sql("""
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SELECT
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/* either debit or credit amount; always positive */
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case gl.debit when 0 then gl.credit else gl.debit end as 'Umsatz (ohne Soll/Haben-Kz)',
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/* 'H' when credit, 'S' when debit */
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case gl.debit when 0 then 'H' else 'S' end as 'Soll/Haben-Kennzeichen',
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/* account number or, if empty, party account number */
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coalesce(acc.account_number, acc_pa.account_number) as 'Konto',
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/* against number or, if empty, party against number */
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coalesce(acc_against.account_number, acc_against_pa.account_number) as 'Gegenkonto (ohne BU-Schlüssel)',
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gl.posting_date as 'Belegdatum',
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gl.voucher_no as 'Belegfeld 1',
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LEFT(gl.remarks, 60) as 'Buchungstext',
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gl.voucher_type as 'Beleginfo - Art 1',
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gl.voucher_no as 'Beleginfo - Inhalt 1',
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gl.against_voucher_type as 'Beleginfo - Art 2',
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gl.against_voucher as 'Beleginfo - Inhalt 2'
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FROM `tabGL Entry` gl
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/* Statistisches Konto (Debitoren/Kreditoren) */
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left join `tabParty Account` pa
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on gl.against = pa.parent
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and gl.company = pa.company
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/* Kontonummer */
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left join `tabAccount` acc
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on gl.account = acc.name
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/* Gegenkonto-Nummer */
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left join `tabAccount` acc_against
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on gl.against = acc_against.name
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/* Statistische Kontonummer */
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left join `tabAccount` acc_pa
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on pa.account = acc_pa.name
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/* Statistische Gegenkonto-Nummer */
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left join `tabAccount` acc_against_pa
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on pa.account = acc_against_pa.name
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WHERE gl.company = %(company)s
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AND DATE(gl.posting_date) >= %(from_date)s
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AND DATE(gl.posting_date) <= %(to_date)s
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{}
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ORDER BY 'Belegdatum', gl.voucher_no""".format(filter_by_voucher), filters, as_dict=as_dict)
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return gl_entries
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def get_customers(filters):
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"""
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Get a list of Customers.
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Arguments:
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filters -- dict of filters to be passed to the sql query
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"""
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return frappe.db.sql("""
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SELECT
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acc.account_number as 'Konto',
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cus.customer_name as 'Name (Adressatentyp Unternehmen)',
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case cus.customer_type when 'Individual' then 1 when 'Company' then 2 else 0 end as 'Adressatentyp',
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adr.address_line1 as 'Straße',
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adr.pincode as 'Postleitzahl',
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adr.city as 'Ort',
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UPPER(country.code) as 'Land',
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adr.address_line2 as 'Adresszusatz',
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con.email_id as 'E-Mail',
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coalesce(con.mobile_no, con.phone) as 'Telefon',
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cus.website as 'Internet',
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cus.tax_id as 'Steuernummer',
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ccl.credit_limit as 'Kreditlimit (Debitor)'
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FROM `tabParty Account` par
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left join `tabAccount` acc
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on acc.name = par.account
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left join `tabCustomer` cus
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on cus.name = par.parent
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left join `tabAddress` adr
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on adr.name = cus.customer_primary_address
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left join `tabCountry` country
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on country.name = adr.country
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left join `tabContact` con
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on con.name = cus.customer_primary_contact
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left join `tabCustomer Credit Limit` ccl
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on ccl.parent = cus.name
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and ccl.company = par.company
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WHERE par.company = %(company)s
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AND par.parenttype = 'Customer'""", filters, as_dict=1)
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def get_suppliers(filters):
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"""
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Get a list of Suppliers.
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Arguments:
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filters -- dict of filters to be passed to the sql query
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"""
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return frappe.db.sql("""
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SELECT
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acc.account_number as 'Konto',
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sup.supplier_name as 'Name (Adressatentyp Unternehmen)',
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case sup.supplier_type when 'Individual' then '1' when 'Company' then '2' else '0' end as 'Adressatentyp',
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adr.address_line1 as 'Straße',
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adr.pincode as 'Postleitzahl',
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adr.city as 'Ort',
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UPPER(country.code) as 'Land',
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adr.address_line2 as 'Adresszusatz',
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con.email_id as 'E-Mail',
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coalesce(con.mobile_no, con.phone) as 'Telefon',
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sup.website as 'Internet',
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sup.tax_id as 'Steuernummer',
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case sup.on_hold when 1 then sup.release_date else null end as 'Zahlungssperre bis'
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FROM `tabParty Account` par
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left join `tabAccount` acc
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on acc.name = par.account
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left join `tabSupplier` sup
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on sup.name = par.parent
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left join `tabDynamic Link` dyn_adr
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on dyn_adr.link_name = sup.name
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and dyn_adr.link_doctype = 'Supplier'
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and dyn_adr.parenttype = 'Address'
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left join `tabAddress` adr
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on adr.name = dyn_adr.parent
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and adr.is_primary_address = '1'
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left join `tabCountry` country
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on country.name = adr.country
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left join `tabDynamic Link` dyn_con
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on dyn_con.link_name = sup.name
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and dyn_con.link_doctype = 'Supplier'
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and dyn_con.parenttype = 'Contact'
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left join `tabContact` con
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on con.name = dyn_con.parent
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and con.is_primary_contact = '1'
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WHERE par.company = %(company)s
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AND par.parenttype = 'Supplier'""", filters, as_dict=1)
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def get_account_names(filters):
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return frappe.get_list("Account",
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fields=["account_number as Konto", "name as Kontenbeschriftung"],
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filters={"company": filters.get("company"), "is_group": "0"})
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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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if not six.PY2:
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data = data.encode('latin_1')
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header = get_header(filters, csv_class)
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header = ';'.join(header).encode('latin_1')
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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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coa = frappe.get_value("Company", filters.get("company"), "chart_of_accounts")
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description = filters.get("voucher_type", csv_class.FORMAT_NAME)
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coa_used = "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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frappe.get_value("DATEV Settings", filters.get("company"), "consultant_number"),
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# L = Tax client number (Mandantennummer)
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frappe.get_value("DATEV Settings", filters.get("company"), "client_number"),
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# M = Start of the fiscal year (Wirtschaftsjahresbeginn)
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frappe.utils.formatdate(frappe.defaults.get_user_default("year_start_date"), "yyyyMMdd"),
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# N = Length of account numbers (Sachkontenlänge)
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'4',
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# O = Transaction batch start date (YYYYMMDD)
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frappe.utils.formatdate(filters.get('from_date'), "yyyyMMdd"),
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# P = Transaction batch end date (YYYYMMDD)
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frappe.utils.formatdate(filters.get('to_date'), "yyyyMMdd"),
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# Q = Description (for example, "Sales Invoice") Max. 30 chars
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'"{}"'.format(_(description)),
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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',
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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"' % frappe.get_value("Company", filters.get("company"), "default_currency"),
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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_used,
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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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@frappe.whitelist()
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def download_datev_csv(filters=None):
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"""
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Provide accounting entries for download in DATEV format.
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Validate the filters, get the data, produce the CSV file and provide it for
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download. Can be called like this:
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GET /api/method/erpnext.regional.report.datev.datev.download_datev_csv
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Arguments / Params:
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filters -- dict of filters to be passed to the sql query
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"""
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if isinstance(filters, string_types):
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filters = json.loads(filters)
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validate(filters)
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# This is where my zip will be written
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zip_buffer = BytesIO()
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# This is my zip file
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datev_zip = zipfile.ZipFile(zip_buffer, mode='w', compression=zipfile.ZIP_DEFLATED)
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transactions = get_transactions(filters)
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transactions_csv = get_datev_csv(transactions, filters, csv_class=Transactions)
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datev_zip.writestr('EXTF_Buchungsstapel.csv', transactions_csv)
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account_names = get_account_names(filters)
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account_names_csv = get_datev_csv(account_names, filters, csv_class=AccountNames)
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datev_zip.writestr('EXTF_Kontenbeschriftungen.csv', account_names_csv)
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customers = get_customers(filters)
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customers_csv = get_datev_csv(customers, filters, csv_class=DebtorsCreditors)
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datev_zip.writestr('EXTF_Kunden.csv', customers_csv)
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suppliers = get_suppliers(filters)
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suppliers_csv = get_datev_csv(suppliers, filters, csv_class=DebtorsCreditors)
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datev_zip.writestr('EXTF_Lieferanten.csv', suppliers_csv)
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# You must call close() before exiting your program or essential records will not be written.
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datev_zip.close()
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frappe.response['filecontent'] = zip_buffer.getvalue()
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frappe.response['filename'] = 'DATEV.zip'
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frappe.response['type'] = 'binary'
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