import json
import re

# --- Start of your main Zapier Code logic ---

# 1. Parse the entire JSON string response body from the Zapier input
# Assumes input is mapped to 'response'
data = json.loads(input_data['response']) 

# Contentstack returns the list of documents under the 'entries' key
documents = data.get('entries', []) 
output = []

for doc in documents:
    # 2. Extract core fields from the Contentstack entry
    # Contentstack uses 'uid' for the entry ID
    doc_id = doc.get('uid')
    title = doc.get('title', 'Untitled Entry')
    
    # Contentstack provides a relative 'url' field for the entry's path
    slug = doc.get('url')

    # 3. Extract Image URL
    # !! IMPORTANT: Change 'image' to your actual image field name
    image_url = None
    image_field = doc.get('featured_image') # e.g., 'main_image', 'featured_image'
    
    # Check if the field exists, is an object, and has a 'url' key
    if image_field and isinstance(image_field, dict) and 'url' in image_field:
        image_url = image_field.get('url')

    # 4. Concatenate the Contentstack Rich Text (RTE) Body
    rte_field = doc.get('body') # <--- CHECK YOUR RTE FIELD NAME HERE
    
    # Check if the body field is a dictionary (the full RTE object)
    if not isinstance(rte_field, dict):
        final_body = ""
        # Skip if the body field is missing or not the expected RTE object

    else:
        # The main content array is inside the 'children' key of the 'doc' type
        rte_blocks = rte_field.get('children', []) 
        concatenated_body = ""

        # Helper function to extract text from a child node
        def extract_text(node):
            if isinstance(node, dict):
                if 'text' in node:
                    return node['text']
                if 'children' in node:
                    # Recursively process children
                    return "".join(extract_text(child) for child in node['children'])
            return ""

        for block in rte_blocks:
            block_type = block.get('type')
            
            # Process Paragraphs and Headings
            if block_type in ['p', 'h1', 'h2', 'h3', 'h4', 'h5', 'h6']:
                # The text is inside the 'children' of the block
                text = extract_text(block)
                if text:
                    concatenated_body += text + " "
            
            # Process Lists (Ordered or Unordered)
            elif block_type in ['ol', 'ul']:
                # Iterate through list items (li)
                for list_item in block.get('children', []):
                    if list_item.get('type') == 'li':
                        text = extract_text(list_item)
                        # Add a bullet and the text
                        prefix = "* "
                        if text:
                            concatenated_body += prefix + text + " "
                concatenated_body += " "

        final_body = concatenated_body.strip().replace('\n', ' ') \
                             .replace('"', "'") \
                             .replace('“', "'") \
                             .replace('”', "'") \
                             .replace("‘", "'") \
                             .replace("’", "'")

    # 5. Get SEO data
    seo_data = doc.get('seo', [])
    seo_keywords = ''
    if isinstance(seo_data, dict):
        if 'keywords' in seo_data:
            seo_keywords = seo_data.get('keywords', '')

    # 6. Create the new structured item
    processed_item = {
        "id": doc_id,
        "title": title,
        "slug": slug,
        "image_url": image_url,
        "concatenated_body": final_body,
        "seo_keywords": seo_keywords
    }
    output.append(processed_item)

# Zapier expects a list of dictionaries for the output and will process each item in a single run
return output

mutation {
  updateProducts(products: [
    {
      productId: ""
      url: ""
      imageUrl: ""
      priceCurrencyCode: "USD"
      name: ""
      attributes: [
        {
          key: "contentType"
          value: "article"
        },
        {
          key: "body"
          value: ""
        }
        {
          key: "keywords"
          value: ""
        }
      ]
      price: 1
      listPrice: 1
      inventoryLevel:1
      availability:"InStock"
    }
  ]) {
    result {
      errors {
        field
        message
      }
      data {
        productId
      }
    }
  }
}

mutation {
  updateProducts(products: [
    {
      productId: ""
      """
            Other fields from the mutation above
      """
      priceCurrencyCode: "USD"
      price: 1
      listPrice: 1
      inventoryLevel: 1
      availability: "InStock"
      variation_id: "GENERAL"
      variations: [
            {
                  variant_id: "LOYAL" 
            },
            {
                  variant_id: "WHOLESALE" 
            }
      ]
    }
  ]) {
    result {
      errors {
        field
        message
      }
      data {
        productId
      }
    }
  }
}