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', {})
