Facebook Ad Library Suggestions Actor

This APIFY actor fetches brand suggestions from Facebook Ad Library based on a provided brand name. It uses Facebook's GraphQL API to search for brand pages and returns detailed information about each match.

Input

The actor accepts a single input parameter:

{
    "brand_name": "string"  // The brand name to search for
}

Output

The actor returns data in the APIFY dataset with the following structure:

{
    "suggestions": [
        {
            "adlibrary_url": "string",
            "brand_name": "string",
            "category": "string",
            "avatar_url": "string",
            "likes": "number",
            "verification": "string",
            "page_alias": "string",
            "ig_username": "string",
            "ig_followers": "number",
            "ig_verification": "string"
        }
    ],
    "metadata": {
        "timestamp": "string",
        "brand_name": "string",
        "total_results": "number"
    }
}

Error Handling

If an error occurs, the actor will store an error object in the dataset:

{
    "error": "string",
    "raw_response": "string",
    "timestamp": "string"
}

Development

Local Development

1. Install dependencies:

$pip install -r requirements.txt

2. Run tests:

$python test_local.py "Brand Name"

Docker Development

1. Build the Docker image:

$docker build -t facebook-ad-library-suggestions .

2. Run the container:

$docker run -it --rm facebook-ad-library-suggestions

APIFY Integration

Running on APIFY

1. Push the actor to APIFY:

$apify push

2. Run the actor:

$apify run -p "{\"brand_name\": \"Nike\"}"

Environment Variables

The actor supports the following environment variables:

• APIFY_PROXY_URL: Proxy URL for requests
• APIFY_PROXY_USERNAME: Proxy username
• APIFY_PROXY_PASSWORD: Proxy password

Notes

• The actor uses Facebook's Ad Library API
• Results are limited to the Indian market (country code: IN)
• The actor includes retry logic for failed requests
• Rate limiting is implemented to avoid API restrictions