> ## Documentation Index
> Fetch the complete documentation index at: https://docs.lobstr.io/llms.txt
> Use this file to discover all available pages before exploring further.

# Add Tasks

> Add TripAdvisor restaurant search URLs as tasks for scraping restaurant listings

Add TripAdvisor restaurant search URLs to your squid for scraping restaurant listings. The scraper extracts restaurant details including ratings, reviews, contact information, price ranges, location coordinates, and Michelin status from TripAdvisor's restaurant directory.

## Headers

<ParamField header="Authorization" type="string" required>
  Your API authentication token. Value: `Token YOUR_API_KEY`
</ParamField>

<ParamField header="Content-Type" type="string" required>
  Request body format. Value: `application/json`
</ParamField>

## Task Format

Each task should contain a URL from a TripAdvisor restaurant search results page. Search for restaurants by location on TripAdvisor, then use those search URLs as tasks.

## Supported URL Formats

The scraper supports TripAdvisor restaurant search URLs from various regional domains:

<Tip>
  Apply filters on TripAdvisor (cuisine type, price range, ratings) before copying the URL to get more targeted restaurant results.
</Tip>

<Note>
  TripAdvisor uses location IDs (g-codes) in URLs. Each city or region has a unique g-code that you can find by searching on the website.
</Note>

## Code Examples

<CodeGroup>
  ```bash cURL theme={null}
  curl -X POST "https://api.lobstr.io/v1/tasks" \
    -H "Authorization: Token YOUR_API_KEY" \
    -H "Content-Type: application/json" \
    -d '{
      "squid": "YOUR_SQUID_HASH",
      "tasks": [
        {
          "url": "https://www.tripadvisor.fr/Restaurants-g187147-Paris_Ile_de_France.html"
        }
      ]
    }'
  ```

  ```python Python theme={null}
  import requests

  API_KEY = "YOUR_API_KEY"
  BASE_URL = "https://api.lobstr.io/v1"
  headers = {"Authorization": f"Token {API_KEY}"}

  squid_id = "YOUR_SQUID_HASH"

  # Add TripAdvisor restaurant search URLs as tasks
  response = requests.post(f"{BASE_URL}/tasks",
      headers=headers,
      json={
          "squid": squid_id,
          "tasks": [
              {"url": "https://www.tripadvisor.fr/Restaurants-g187147-Paris_Ile_de_France.html"},
              {"url": "https://www.tripadvisor.com/Restaurants-g60763-New_York_City_New_York.html"}
          ]
      }
  )

  data = response.json()
  print(f"Added {len(data['tasks'])} tasks")
  print(f"Duplicates skipped: {data['duplicated_count']}")

  for task in data["tasks"]:
      print(f"  Task ID: {task['id']}")
      print(f"  URL: {task['params']['url']}")
  ```
</CodeGroup>

## Response

```json 200 theme={null}
{
  "duplicated_count": 0,
  "tasks": [
    {
      "id": "82367f24d9450b2222080eed91662968",
      "created_at": "2025-07-17T09:06:47.287893",
      "is_active": true,
      "params": {
        "url": "https://www.tripadvisor.fr/Restaurants-g187147-Paris_Ile_de_France.html"
      },
      "module": 115,
      "object": "task"
    }
  ]
}
```