# -*- 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 *
#STEP 1 : read the needed file(s)
processor = Processor('origin/supplier.csv')
##STEP 2 : Define the mapping for every object to import
mapping = {
'id': mapper.m2o(SUPPLIER_PREFIX, 'Company_ID'),
'name': mapper.val('Company_Name'),
'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),
'supplier': mapper.const('1'),
'user_id': mapper.val('Account_Manager'),
}
contact_mapping = {
'id': mapper.m2o(SUPPLIER_CONTACT_PREFIX, 'Contact Email'),
'parent_id/id': mapper.m2o(SUPPLIER_PREFIX, 'Company_ID'),
'email': mapper.val('Contact Email'),
'name': mapper.concat(' ', 'Contact First Name', 'Contact Last Name'),
'title/id': mapper.m2o(TITLE_PREFIX, 'Contact Title'),
}
title_map = {
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'),
import random
PARTNER_PREFIX = 'partner_generated'
TAG_PREFIX = 'partner_tag'
output = 'data/res.partner.generated.csv'
tag_output = 'data/res.partner.category.csv'
script = '0_partner_generated.sh'
tags = ["Tag %s" % i for i in xrange(0, 100)]
header = ['id', 'tags']
data = [[str(i), ','.join(tags[random.randint(0, 99)] for i in xrange(0, 5))]
for i in xrange(0, 1000)]
mapping = {
'id': mapper.m2o(PARTNER_PREFIX, 'id'),
'name': mapper.val('id', postprocess=lambda x: "Partner %s" % x),
'phone': mapper.val('id', postprocess=lambda x: "0032%s" % (int(x) * 11)),
'website': mapper.val('id',
postprocess=lambda x: "http://website-%s.com" % x),
'street': mapper.val('id', postprocess=lambda x: "Street %s" % x),
'city': mapper.val('id', postprocess=lambda x: "City %s" % x),
'zip': mapper.val('id', postprocess=lambda x: ("%s" % x).zfill(6)),
'country_id/id': mapper.const('base.be'),
'company_type': mapper.const('company'),
'customer': mapper.val('id', postprocess=lambda x: str(int(x) % 2)),
'supplier': mapper.val('id', postprocess=lambda x: str((int(x) + 1) % 2)),
'lang': mapper.const('English'),
'category_id/id': mapper.m2m(TAG_PREFIX, 'tags')
}
tag_mapping = {
'NL': 'base.nl',
}
PARTNER_PREFIX = "TEST_PARTNER"
# STEP 1 : read the needed file(s)
processor = Processor('origin%scontact.csv' % os.sep)
# Print o2o mapping
import pprint
pprint.pprint(processor.get_o2o_mapping())
# STEP 2 : Define the mapping for every object to import
mapping = {
'id': mapper.m2o(PARTNER_PREFIX, 'Company_ID', skip=True),
'name': mapper.val('Company_Name', skip=True),
'phone': mapper.val('Phone'),
'website': mapper.val('www'),
'street': mapper.val('address1'),
'city': mapper.val('city'),
'zip': mapper.val('zip code'),
'country_id/id': mapper.map_val('country', country_map),
'company_type': mapper.const('company'),
'customer': mapper.bool_val('IsCustomer', ['1'], ['0']),
'supplier': mapper.bool_val('IsSupplier', ['1'], ['0']),
'lang': mapper.map_val('Language', lang_map),
'image': mapper.binary("Image", "origin/img/"),
}
# Step 3: Check data quality (Optional)
processor.check(checker.cell_len_checker(30))
PRODUCT_PREFIX = "PRODUCT_PRODUCT"
CATEGORY_PREFIX = "PRODUCT_CATEGORY"
ATTRIBUTE_PREFIX = "PRODUCT_ATTRIBUTE"
ATTRIBUTE_VALUE_PREFIX = "PRODUCT_ATTRIBUTE_VALUE"
ATTRIBUTE_LINE_PREFIX = "PRODUCT_ATTRIBUTE_LINE"
context = {'create_product_variant': True, 'tracking_disable': True}
#STEP 1 : read the needed file(s)
processor = ProductProcessorV10('origin%sproduct.csv' % os.sep, delimiter=',')
#STEP 2 : Category and Parent Category
categ_parent_map = {
'id': mapper.m2o(CATEGORY_PREFIX, 'categoy'),
'name': mapper.val('categoy'),
}
categ_map = {
'id': mapper.m2o(CATEGORY_PREFIX, 'Sub Category'),
'parent_id/id': mapper.m2o(CATEGORY_PREFIX, 'categoy'),
'name': mapper.val('Sub Category'),
}
processor.process(categ_parent_map,
'data%sproduct.category.parent.csv' % os.sep, {
'worker': 1,
'batch_size': 5,
'model': 'product.category'
}, 'set')
processor.process(categ_map, 'data%sproduct.category.csv' % os.sep, {
TEMPLATE_PREFIX = "PRODUCT_TEMPLATE"
PRODUCT_PREFIX = "PRODUCT_PRODUCT"
CATEGORY_PREFIX = "PRODUCT_CATEGORY"
ATTRIBUTE_PREFIX = "PRODUCT_ATTRIBUTE"
ATTRIBUTE_VALUE_PREFIX = "PRODUCT_ATTRIBUTE_VALUE"
# Define the context that will be used
context = {'create_product_variant': True, 'tracking_disable': True}
# STEP 1 : read the needed file(s)
processor = ProductProcessorV9('origin%sproduct.csv' % os.sep, delimiter=',')
# STEP 2 : Category and Parent Category
categ_parent_map = {
'id': mapper.m2o(CATEGORY_PREFIX, 'categoy'),
'name': mapper.val('categoy'),
}
categ_map = {
'id': mapper.m2o(CATEGORY_PREFIX, 'Sub Category'),
'parent_id/id': mapper.m2o(CATEGORY_PREFIX, 'categoy'),
'name': mapper.val('Sub Category'),
}
processor.process(categ_parent_map,
'data%sproduct.category.parent.csv' % os.sep, {
'worker': 1,
'batch_size': 5,
'model': 'product.category'
}, 'set')
processor.process(categ_map, 'data%sproduct.category.csv' % os.sep, {
PRODUCT_PREFIX = "PRODUCT_PRODUCT"
CATEGORY_PREFIX = "PRODUCT_CATEGORY"
ATTRIBUTE_PREFIX = "PRODUCT_ATTRIBUTE"
ATTRIBUTE_VALUE_PREFIX = "PRODUCT_ATTRIBUTE_VALUE"
ATTRIBUTE_LINE_PREFIX = "PRODUCT_ATTRIBUTE_LINE"
context = {'create_product_variant': True, 'tracking_disable': True}
# STEP 1 : read the needed file(s)
processor = ProductProcessorV10('origin%sproduct.csv' % os.sep, delimiter=',')
# STEP 2 : Category and Parent Category
categ_parent_map = {
'id': mapper.m2o(CATEGORY_PREFIX, 'categoy'),
'name': mapper.val('categoy'),
}
categ_map = {
'id': mapper.m2o(CATEGORY_PREFIX, 'Sub Category'),
'parent_id/id': mapper.m2o(CATEGORY_PREFIX, 'categoy'),
'name': mapper.val('Sub Category'),
}
processor.process(categ_parent_map, 'data%sproduct.category.parent.csv' % os.sep, {'worker': 1, 'batch_size': 5,
'model': 'product.category'}, 'set')
processor.process(categ_map, 'data%sproduct.category.csv' % os.sep, {'worker': 1, 'batch_size': 20}, 'set')
# STEP 3 : Product Template mapping
template_map = {
'id': mapper.m2o(TEMPLATE_PREFIX, 'ref'),
'US': 'base.us',
'NL': 'base.nl',
}
PARTNER_PREFIX = "TEST_PARTNER"
# STEP 1 : read the needed file(s)
processor = Processor('origin%scontact.csv' % os.sep)
# Print o2o mapping
import pprint
pprint.pprint(processor.get_o2o_mapping())
# STEP 2 : Define the mapping for every object to import
mapping = {
'id': mapper.m2o(PARTNER_PREFIX, 'Company_ID', skip=True),
'name': mapper.val('Company_Name', skip=True),
'phone': mapper.val('Phone'),
'website': mapper.val('www'),
'street': mapper.val('address1'),
'city': mapper.val('city'),
'zip': mapper.val('zip code'),
'country_id/id': mapper.map_val('country', country_map),
'company_type': mapper.const('company'),
'customer': mapper.bool_val('IsCustomer', ['1'], ['0']),
'supplier': mapper.bool_val('IsSupplier', ['1'], ['0']),
'lang': mapper.map_val('Language', lang_map),
'image': mapper.binary("Image", "origin/img/"),
}
# Step 3: Check data quality (Optional)
processor.check(checker.cell_len_checker(30))
TEMPLATE_PREFIX = "PRODUCT_TEMPLATE"
PRODUCT_PREFIX = "PRODUCT_PRODUCT"
CATEGORY_PREFIX = "PRODUCT_CATEGORY"
ATTRIBUTE_PREFIX = "PRODUCT_ATTRIBUTE"
ATTRIBUTE_VALUE_PREFIX = "PRODUCT_ATTRIBUTE_VALUE"
# Define the context that will be used
context = {'create_product_variant': True, 'tracking_disable': True}
# STEP 1 : read the needed file(s)
processor = ProductProcessorV9('origin%sproduct.csv' % os.sep, delimiter=',')
# STEP 2 : Category and Parent Category
categ_parent_map = {
'id': mapper.m2o(CATEGORY_PREFIX, 'categoy'),
'name': mapper.val('categoy'),
}
categ_map = {
'id': mapper.m2o(CATEGORY_PREFIX, 'Sub Category'),
'parent_id/id': mapper.m2o(CATEGORY_PREFIX, 'categoy'),
'name': mapper.val('Sub Category'),
}
processor.process(categ_parent_map, 'data%sproduct.category.parent.csv' % os.sep,
{'worker': 1, 'batch_size': 5, 'model': 'product.category'}, 'set')
processor.process(categ_map, 'data%sproduct.category.csv' % os.sep, {'worker': 1, 'batch_size': 20}, 'set')
# STEP 3 : Product Template mapping
template_map = {
'id': mapper.m2o(TEMPLATE_PREFIX, 'ref'),
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='')
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),
'image':
EXEC = sys.argv[1]
PARTNER_PREFIX = 'partner_generated'
TAG_PREFIX = 'partner_tag'
output = 'data/res.partner.generated.csv'
tag_output = 'data/res.partner.category.csv'
script = '0_partner_generated.sh'
tags = ["Tag %s" % i for i in range(0, 100)]
header = ['id', 'tags']
data = [[str(i), ','.join(tags[random.randint(0, 99)] for i in range(0, 5))] for i in range(0, 200)]
mapping = {
'id': mapper.m2o(PARTNER_PREFIX, 'id'),
'name': mapper.val('id', postprocess=lambda x: "Partner %s" % x),
'phone': mapper.val('id', postprocess=lambda x: "0032%s" % (int(x) * 11)),
'website': mapper.val('id', postprocess=lambda x: "http://website-%s.com" % x),
'street': mapper.val('id', postprocess=lambda x: "Street %s" % x),
'city': mapper.val('id', postprocess=lambda x: "City %s" % x),
'zip': mapper.val('id', postprocess=lambda x: ("%s" % x).zfill(6)),
'country_id/id': mapper.const('base.be'),
'company_type': mapper.const('company'),
'customer': mapper.val('id', postprocess=lambda x: str(int(x) % 2)),
'supplier': mapper.val('id', postprocess=lambda x: str((int(x) + 1) % 2)),
'lang': mapper.const('English'),
'category_id/id': mapper.m2m(TAG_PREFIX, 'tags')
}
tag_mapping = {
'id': mapper.m2m_id_list(TAG_PREFIX, 'tags'),
# -*- coding: utf-8 -*-
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(
'my_import_res_partner',
mapper.concat('_', 'name', 'Birthdate', 'phone', 'email', 'website')),
'name':
mapper.val('id', postprocess=lambda x: "Partner %s" % x),
'birthdate':
mapper.val('Birthdate',
postprocess=lambda x: datetime.strftime(x, "%d/%m/%y").strftime(
"%Y-%m-%d 00:00:))")),
'phone':
mapper.val('phone', postprocess=lambda x: "855%s" % (int(x) * 10)),
'email':
mapper.val('email', postprocess=lambda x: "Email %s" % x),
'website':
mapper.val('website', postprocess=lambda x: "website %s" % x)
}
processor.process(
res_partner_mapping, 'res.partner.csv', {
'model': 'res.partner',
'context': "{'tracking_disable': True}",
PRODUCT_PREFIX = "PRODUCT_PRODUCT"
CATEGORY_PREFIX = "PRODUCT_CATEGORY"
ATTRIBUTE_PREFIX = "PRODUCT_ATTRIBUTE"
ATTRIBUTE_VALUE_PREFIX = "PRODUCT_ATTRIBUTE_VALUE"
ATTRIBUTE_LINE_PREFIX = "PRODUCT_ATTRIBUTE_LINE"
context = {'create_product_variant': True, 'tracking_disable': True}
# STEP 1 : read the needed file(s)
processor = ProductProcessorV10('origin%sproduct.csv' % os.sep, delimiter=',')
# STEP 2 : Category and Parent Category
categ_parent_map = {
'id': mapper.m2o(CATEGORY_PREFIX, 'categoy'),
'name': mapper.val('categoy'),
}
categ_map = {
'id': mapper.m2o(CATEGORY_PREFIX, 'Sub Category'),
'parent_id/id': mapper.m2o(CATEGORY_PREFIX, 'categoy'),
'name': mapper.val('Sub Category'),
}
processor.process(categ_parent_map, 'data%sproduct.category.parent.csv' % os.sep, {'worker': 1, 'batch_size': 5,
'model': 'product.category'}, 'set')
processor.process(categ_map, 'data%sproduct.category.csv' % os.sep, {'worker': 1, 'batch_size': 20}, 'set')
# STEP 3 : Product Template mapping
template_map = {
'id': mapper.m2o(TEMPLATE_PREFIX, 'ref'),
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', {})
#Step 5: Define output and import parameter
processor.write_to_file("3_supplier_message.sh", python_exe='', path='')
