return 'IT{}'.format(val) if val[:2] == 'IT': if len(val) == 13 and val[:3].isdigit(): return val.upper() if val[:2] in ('GB', 'EE', 'LT'): return val return '' # STEP 1 : read the needed file(s) processor = Processor('../data/NOMIN.CSV', conf_file=CONNECTION_FILE, delimiter=",") # STEP 2 : Define the mapping for every object to import mapping = { 'id': mapper.m2o_map(PARTNER_PREFIX, mapper.val('CODICE')), 'name': mapper.val('DESCRIZION', skip=True), 'street': mapper.val('INDIRIZZO'), 'city': mapper.val('COMUNE'), 'zip': mapper.val('CAP'), 'country_id/id': mapper.val('PAESE', postprocess=postprocess_country_id), 'state_id/id': mapper.val('PROVINCIA', postprocess=postprocess_country_state_id), 'vat': mapper.val('PARTITA_IV', postprocess=postprocess_vat), 'phone': mapper.val('TELEFONO1'), 'email': mapper.val('E_MAIL'), # OTHER 'lang': mapper.val('PAESE', postprocess=postprocess_lang), 'customer': mapper.const('1'), 'supplier': mapper.const('1'),
'value_ids/id': mapper.m2o_att(ATTRIBUTE_VALUE_PREFIX, attribute_list) # TODO } processor.process_attribute_mapping(attribue_value_mapping, line_mapping, attribute_list, ATTRIBUTE_PREFIX, 'data/', { 'worker': 3, 'batch_size': 50, 'context': context }) # STEP 5: Product Variant product_mapping = { 'id': mapper.m2o_map(PRODUCT_PREFIX, mapper.concat('_', 'barcode', 'Color', 'Gender', 'Size_H', 'Size_W'), skip=True), 'barcode': mapper.val('barcode'), 'product_tmpl_id/id': mapper.m2o(TEMPLATE_PREFIX, 'ref'), 'attribute_value_ids/id': mapper.m2m_attribute_value(ATTRIBUTE_VALUE_PREFIX, 'Color', 'Gender', 'Size_H', 'Size_W'), } processor.process( product_mapping, 'data%sproduct.product.csv' % os.sep, { 'worker': 3, 'batch_size': 50, 'groupby': 'product_tmpl_id/id', 'context': context
from odoo_csv_tools.lib import mapper from odoo_csv_tools.lib.transform import Processor from datetime import datetime processor = Processor('client_file.csv', delimiter=';') res_partner_mapping = { 'id': mapper.m2o_map('my_import_res_partner', mapper.concat('_', 'Firstname', 'Lastname', 'Birthdate')), 'name': mapper.concat(' ', 'Firstname', 'Lastname'), 'birthdate': mapper.val('Birthdate', postprocess=lambda x: datetime.strptime(x, "%d/%m/%y").strftime( "%Y-%m-%d 00:00:00")), } processor.process( res_partner_mapping, 'res.partner.csv', { 'model': 'res.partner', 'context': "{'tracking_disable': True}", 'worker': 2, 'batch_size': 20 }) processor.write_to_file("res_partner.sh", python_exe='', path='')
# STEP 4: Attribute List attribute_list = ['Color', 'Gender', 'Size_H', 'Size_W'] attribue_value_mapping = { 'id': mapper.m2o_att(ATTRIBUTE_VALUE_PREFIX, attribute_list), # TODO 'name': mapper.val_att(attribute_list), # TODO 'attribute_id/id': mapper.m2o_att_name(ATTRIBUTE_PREFIX, attribute_list), } line_mapping = { 'product_tmpl_id/id': mapper.m2o(TEMPLATE_PREFIX, 'ref'), 'attribute_id/id': mapper.m2o_att_name(ATTRIBUTE_PREFIX, attribute_list), 'value_ids/id': mapper.m2o_att(ATTRIBUTE_VALUE_PREFIX, attribute_list) # TODO } processor.process_attribute_mapping(attribue_value_mapping, line_mapping, attribute_list, ATTRIBUTE_PREFIX, 'data/', {'worker': 3, 'batch_size': 50, 'context': context}) # STEP 5: Product Variant product_mapping = { 'id': mapper.m2o_map(PRODUCT_PREFIX, mapper.concat('_', 'barcode', 'Color', 'Gender', 'Size_H', 'Size_W'), skip=True), 'barcode': mapper.val('barcode'), 'product_tmpl_id/id': mapper.m2o(TEMPLATE_PREFIX, 'ref'), 'attribute_value_ids/id': mapper.m2m_attribute_value(ATTRIBUTE_VALUE_PREFIX, 'Color', 'Gender', 'Size_H', 'Size_W'), } processor.process(product_mapping, 'data%sproduct.product.csv' % os.sep, {'worker': 3, 'batch_size': 50, 'groupby': 'product_tmpl_id/id', 'context': context}, 'set') # Step 6: Define output and import parameter processor.write_to_file("3_product_import.sh", python_exe=EXEC, path='../')
# -*- coding: utf-8 -*- import os from odoo_csv_tools.lib import mapper from odoo_csv_tools.lib.transform import Processor from datetime import datetime from prefix import * #STEP 1 : read the needed file(s) processor = Processor('origin%scontact.csv' % os.sep) ##STEP 2 : Define the mapping for every object to import mapping = { 'id': mapper.m2o_map(CLIENT_PREFIX, mapper.concat('_', 'Client Name', 'zip code')), 'name': mapper.val('Client Name', skip=True), 'phone': mapper.val('Phone'), 'street': mapper.val('address1'), 'city': mapper.val('city'), 'zip': mapper.val('zip code'), 'country_id/id': mapper.map_val('country', country_map), 'customer': mapper.const('1'), 'lang': mapper.map_val('Language', lang_map),
# -*- coding: utf-8 -*- from odoo_csv_tools.lib import mapper from odoo_csv_tools.lib.transform import Processor from datetime import datetime from prefix import SUPPLIER_PREFIX, MESSAGE_PREFIX, SUPPLIER_CONTACT_PREFIX #STEP 1 : read the needed file(s) processor = Processor('origin/message.csv') ##STEP 2 : Define the mapping for every object to import mapping = { 'id': mapper.m2o_map(MESSAGE_PREFIX, mapper.concat("_", 'Company_ID', 'Date')), 'res_external_id': mapper.m2o(SUPPLIER_PREFIX, 'Company_ID'), 'author_id/id': mapper.m2o(SUPPLIER_CONTACT_PREFIX, 'from'), 'email_from': mapper.val('from'), 'subject': mapper.val('subject'), 'body': mapper.val('body'), 'date': mapper.val('Date', postprocess=lambda x: datetime.strptime(x, "%d/%m/%y %H:%M:%S"). strftime("%Y-%m-%d %H:%M:%S")), } #Step 4: Process data processor.process(mapping, 'data/mail.message.csv', {})