📈 Google Trends Daily & Real-Time Search Trends Scraper

A high-performance Apify Actor built in Python to extract trending search queries, search traffic estimates, related news headlines, and direct Google Search URLs via official Google Trends RSS feeds.

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🌟 Key Features

• ⚡ Ultra Fast (<2 Seconds): Hits Google Trends' official RSS feeds directly via httpx async requests and parses XML natively using xml.etree.ElementTree. Zero browser overhead (~128MB RAM footprint).
• 🌍 Multi-Country Support: Pass any list of 2-letter ISO country codes (e.g. US, GB, FR, DE, IN, JP, BR).
• 🔥 Traffic Estimates & News Headlines: Extract approximate search volume (e.g., 500,000+), picture URLs, and associated news articles with source links and snippets.
• 📊 Store-Ready Dataset: Automatically pushes Pydantic-validated dataset records with built-in tabular overview support.

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📥 Input Parameters

The Actor accepts the following input settings in JSON format:

Parameter	Type	Default	Description
geos	array	["US", "GB", "FR", "DE"]	List of 2-letter ISO country codes to scrape trends from.
maxItemsPerGeo	integer	50	Maximum number of trending queries to extract per selected country.

Example Input JSON

{
  "geos": ["US", "GB", "JP"],
  "maxItemsPerGeo": 25
}

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📤 Output Format

Each item pushed to the output dataset follows a structured schema:

{
  "query": "Super Bowl 2026",
  "geo": "US",
  "approx_traffic": "2,000,000+",
  "search_url": "https://www.google.com/search?q=Super+Bowl+2026",
  "published_at": "Tue, 25 Aug 2026 08:00:00 +0000",
  "description": "Trending search query in the United States",
  "picture_url": "https://t0.gstatic.com/images?q=tbn:...",
  "articles": [
    {
      "title": "Super Bowl 2026 updates and highlights",
      "url": "https://news.example.com/sports/super-bowl-2026",
      "source": "ESPN",
      "snippet": "Everything you need to know about Super Bowl 2026...",
      "image_url": "https://t0.gstatic.com/images?q=tbn:..."
    }
  ]
}

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🚀 Running Locally

Step 1: Install Dependencies

$pip install -r requirements.txt

Step 2: Run the Actor

$python -m src.main

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🐳 Docker Support

To build and run containerized:

docker build -t google-trends-scraper .
docker run -it google-trends-scraper