'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'),
'name': mapper.m2m_value_list('tags'),
'parent_id/id': mapper.const('base.res_partner_category_0'),
}
processor = transform.Processor(header=header, data=data)
processor.process(tag_mapping,
tag_output, {
'worker': 1,
'batch_size': 10,
'model': 'res.partner.category',
},
m2m=True)
processor.process(mapping, output, {
'worker': 4,
'batch_size': 100,
'context': context
}, 'set')
#STEP 4: Attribute List
attribute_list = ['Color', 'Gender', 'Size_H', 'Size_W']
processor.process_attribute_data(attribute_list, ATTRIBUTE_PREFIX,
'data%sproduct.attribute.csv' % os.sep, {
'worker': 4,
'batch_size': 10,
'context': context
})
#STEP 5: Attribute Value
attribue_value_mapping = {
'id':
mapper.m2m_id_list(
ATTRIBUTE_VALUE_PREFIX,
*[mapper.concat_field_value_m2m('_', f) for f in attribute_list]),
'name':
mapper.m2m_value_list(*attribute_list),
'attribute_id/id':
mapper.m2m_id_list(ATTRIBUTE_PREFIX,
*[mapper.field(f) for f in attribute_list]),
}
processor.process(attribue_value_mapping,
'data%sproduct.attribute.value.csv' % os.sep, {
'worker': 3,
'batch_size': 50,
'context': context,
'groupby': 'attribute_id/id'
},
m2m=True)
'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'),
'name': mapper.m2m_value_list('tags'),
'parent_id/id': mapper.const('base.res_partner_category_0'),
}
processor = transform.Processor(header=header, data=data)
processor.process(tag_mapping, tag_output, {
'worker': 1,
'batch_size': 10,
'model': 'res.partner.category',
}, m2m=True)
processor.process(mapping, output, {
'worker': 4,
'batch_size': 100,
'model': 'res.partner',
})
'lang':
mapper.map_val('Language', lang_map),
'image':
mapper.binary("Image", "origin/img/"),
'create_uid':
mapper.val('Create BY'),
'create_date':
mapper.val('Create ON',
postprocess=lambda x: datetime.strptime(x, "%d/%m/%y").strftime(
"%Y-%m-%d 00:00:00")),
'category_id/id':
mapper.m2m(PARTNER_CATEGORY_PREFIX, 'Tag', 'Fidelity Grade'),
}
tag_mapping = {
'id': mapper.m2m_id_list(PARTNER_CATEGORY_PREFIX, 'Tag'),
'name': mapper.m2m_value_list('Tag'),
}
grade_mapping = {
'id': mapper.m2m_id_list(PARTNER_CATEGORY_PREFIX, 'Fidelity Grade'),
'name': mapper.m2m_value_list('Fidelity Grade'),
}
#Step 4: Process data
processor.process(tag_mapping,
'data%sres.partner.category.csv' % os.sep, {},
m2m=True)
processor.process(grade_mapping,
'data%sres.partner.category.grade.csv' % os.sep,
{'model': 'res.partner.category'},
'standard_price': mapper.num('cost'),
'lst_price': mapper.num('public_price'),
'default_code': mapper.val('ref'),
'name': mapper.val('name'),
}
processor.process(template_map, 'data%sproduct.template.csv' % os.sep, {'worker': 4, 'batch_size': 10,
'context': context}, 'set')
# STEP 4: Attribute List
attribute_list = ['Color', 'Gender', 'Size_H', 'Size_W']
processor.process_attribute_data(attribute_list, ATTRIBUTE_PREFIX, 'data%sproduct.attribute.csv' % os.sep,
{'worker': 4, 'batch_size': 10,
'context': context})
# STEP 5: Attribute Value
attribue_value_mapping = {
'id': mapper.m2m_id_list(ATTRIBUTE_VALUE_PREFIX, *[mapper.concat_field_value_m2m('_', f) for f in attribute_list]),
'name': mapper.m2m_value_list(*attribute_list),
'attribute_id/id': mapper.m2m_id_list(ATTRIBUTE_PREFIX, *[mapper.field(f) for f in attribute_list]),
}
processor.process(attribue_value_mapping, 'data%sproduct.attribute.value.csv' % os.sep, {'worker': 3, 'batch_size': 50,
'context': context,
'groupby': 'attribute_id/id'},
m2m=True)
# STEP 6: Attribute Value Line
line_mapping = {
'id': mapper.m2m_id_list(ATTRIBUTE_LINE_PREFIX,
*[mapper.concat_mapper_all('_', mapper.field(f), mapper.val('ref')) for f in
attribute_list]),
'product_tmpl_id/id': mapper.m2o(TEMPLATE_PREFIX, 'ref'),
'attribute_id/id': mapper.m2m_id_list(ATTRIBUTE_PREFIX, *[mapper.field(f) for f in attribute_list]),