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In this example, we want to import the product 'Wallpaper'.

import requests
import json

def get_product_type_code():
    url_get_product_type = 'https://pim-client.wizart.ai/api/v2.1/import/product-types'
    headers = {
       'Authorization': access_token
    }

    response = requests.get(url_get_product_type, headers=headers)

    if response.status_code == 200:
       get_product_types = requests.get(url_get_product_type, headers=headers)
       product_types = json.loads(get_product_types.content.decode('utf8').replace("'", '"'))
       for each_product_type in product_types['data']:
           if each_product_type['attributes']['name'] == 'Wallpaper':
              wallpaper_code = each_product_type['attributes']['code']
    else:
       print(f"Error: {response.status_code} - {response.text}")
    return wallpaper_code
    
product_code = get_product_type_code()

def get_default_csv():
    url_default_csv = f'https://pim-client.wizart.ai/api/v2.1/data-mappings/default/{product_code}'
    headers = {
       'Authorization': access_token
    }

    response = requests.get(url_default_csv, headers=headers)

    if response.status_code == 200:
        get_default_csv = requests.get(url_default_csv, headers=headers)
        default_csv = get_default_csv.content.decode("utf-8")
        csv_columns = default_csv.split(',')
    else:
       print(f"Error: {response.status_code} - {response.text}")
    return csv_columns
    
empty_csv_file = get_default_csv()

def transform_custom_data_to_pim_csv():
    #the process where you transform columns from your data storage into a format required for loading into a PIM system.
    #to merge columns, use the obtained empty_csv_file with all the relevant columns required for loading into the PIM system.
    return csv_data_for_import

def import_to_pim():
    url = f'https://pim-client.wizart.ai/api/v2.1/product-type/{product_code}/import'
    headers = {
        'Authorization': access_token
    }
    files = {
        'data': open('/path/to/file', 'rb'),
        'archive': open('/path/to/file', 'rb')
    }

    response = requests.post(url, headers=headers, files=files)
    
import_to_pim()

The get_product_type_code() function retrieves the product type code for a specific product type (in this case, 'Wallpaper') from the PIM system. It sends a GET request to the /import/product-types endpoint, using the provided access_token for authorization. If the request is successful, the product types are obtained from the response, and the code for the 'Wallpaper' product type is extracted.
The get_default_csv() function retrieves the default CSV mapping for the product type identified by product_code. It sends a GET request to the /data-mappings/default/{product_code} endpoint, again using the access_token. If the request is successful, the default CSV content is obtained from the response and split into individual columns.
The transform_custom_data_to_pim_csv() function is a placeholder that represents the process of transforming columns from your data storage into the format required for loading into the PIM system. It mentions merging the columns using the empty_csv_file obtained from the get_default_csv() function. The actual implementation of this transformation process is not provided in the code.
The import_to_pim() function performs the actual import of data to the PIM system. It sends a POST request to the /product-type/{product_code}/import endpoint, including the access_token in the headers and files to be uploaded (data and archive). The file paths should be updated accordingly.
The import_to_pim() function is called at the end to initiate the data import process to the PIM system.

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