Python m2m_attribute_valueの例

コード例 #1

                                        '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_output()
launchfile_write(processor.file_to_write,
                 "3_product_import.sh",
                 python_exe='python-coverage run -a',
                 path='../')

コード例 #2

ファイル: test_product_v9.py プロジェクト: tfrancoi/odoo_csv_import

# 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='../')