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Search real-time news articles with date and country filtering. News mode is optimised for finding current events, breaking news, and journalism content.

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What You Can Do

  • Media monitoring - Track news coverage across topics and brands
  • Current events - Get up-to-the-minute news on any subject
  • Journalism research - Find sources and verify facts
  • PR and brand tracking - Monitor mentions and sentiment
  • Trend analysis - Identify emerging stories and patterns

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Features

Real-Time News

Access current news articles from sources worldwide.

Date Filtering

Filter by publication date for time-sensitive research.

Country Targeting

Focus on specific regions with country code filtering.

100 Results

Retrieve up to 100 results per query for comprehensive coverage.

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Quick Start

Search for news articles on any topic: 
from valyu import Valyu

valyu = Valyu()  # Uses VALYU_API_KEY from env

response = valyu.search(
    query="artificial intelligence regulation updates",
    search_type="news",
    max_num_results=20,
)

for result in response["results"]:
    print(f"Title: {result['title']}")
    print(f"Date: {result.get('publication_date', 'N/A')}")
    print(f"URL: {result['url']}")
    print("---")
Filter news by publication date range: 
from valyu import Valyu

valyu = Valyu()

response = valyu.search(
    query="climate change policy announcements",
    search_type="news",
    max_num_results=50,
    start_date="2025-01-01",
    end_date="2025-12-31",
)

print(f"Found {len(response['results'])} articles from 2025")

for result in response["results"][:5]:
    print(f"{result.get('publication_date', 'N/A')}: {result['title']}")
Focus on news from specific regions: 
from valyu import Valyu

valyu = Valyu()

# US news
us_news = valyu.search(
    query="technology startup funding rounds",
    search_type="news",
    max_num_results=30,
    country_code="US",
)

# UK news
uk_news = valyu.search(
    query="technology startup funding rounds",
    search_type="news",
    max_num_results=30,
    country_code="GB",
)

print(f"US articles: {len(us_news['results'])}")
print(f"UK articles: {len(uk_news['results'])}")
Use ISO 3166-1 alpha-2 country codes: US (United States), GB (United Kingdom), DE (Germany), FR (France), etc.

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100 Results

News mode supports up to 100 results per query. This requires the increased_max_results permission on your API key. To enable 100 results:
  1. Go to API Key Management
  2. Request the increased_max_results permission
  3. Create a new API key after approval
Without this permission, the default maximum is 20 results per query.
from valyu import Valyu

valyu = Valyu()  # Use API key with increased_max_results permission

response = valyu.search(
    query="electric vehicle market news",
    search_type="news",
    max_num_results=100,  # Requires increased_max_results permission
    start_date="2025-01-01",
    country_code="US",
)

print(f"Retrieved {len(response['results'])} news articles")

# Process all 100 results
for i, article in enumerate(response["results"], 1):
    print(f"{i}. {article['title']}")

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Use Case Examples

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Multi-Topic News Monitoring

Track multiple topics in a single monitoring workflow: 
from valyu import Valyu
from datetime import datetime, timedelta

valyu = Valyu()

def monitor_topics(topics: list, days_back: int = 7):
    """Monitor multiple news topics with date filtering."""
    end_date = datetime.now().strftime("%Y-%m-%d")
    start_date = (datetime.now() - timedelta(days=days_back)).strftime("%Y-%m-%d")
    
    results = {}
    
    for topic in topics:
        response = valyu.search(
            query=topic,
            search_type="news",
            max_num_results=20,
            start_date=start_date,
            end_date=end_date,
        )
        
        if response.get("success"):
            results[topic] = {
                "count": len(response["results"]),
                "articles": response["results"]
            }
            print(f"📰 {topic}: {len(response['results'])} articles")
    
    return results

# Monitor tech and business topics
news = monitor_topics([
    "artificial intelligence breakthroughs",
    "cryptocurrency regulation",
    "renewable energy investments",
    "tech layoffs announcements"
])

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Brand Monitoring

Track news mentions for brands or companies: 
from valyu import Valyu

valyu = Valyu()

def brand_monitoring(brand: str, competitor_brands: list = None):
    """Monitor news for a brand and its competitors."""
    
    # Main brand news
    brand_news = valyu.search(
        query=f"{brand} news announcements",
        search_type="news",
        max_num_results=50,
    )
    
    print(f"=== {brand} News ===")
    print(f"Found {len(brand_news['results'])} articles")
    
    for article in brand_news["results"][:5]:
        print(f"  - {article['title']}")
    
    # Competitor comparison
    if competitor_brands:
        print(f"\n=== Competitor Coverage ===")
        for competitor in competitor_brands:
            comp_news = valyu.search(
                query=f"{competitor} news",
                search_type="news",
                max_num_results=20,
            )
            print(f"{competitor}: {len(comp_news['results'])} articles")
    
    return brand_news

# Monitor Tesla and competitors
tesla_news = brand_monitoring(
    brand="Tesla",
    competitor_brands=["Rivian", "Lucid Motors", "Ford EV"]
)

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Breaking News Tracker

Monitor for breaking news on specific topics: 
from valyu import Valyu
from datetime import datetime

valyu = Valyu()

def breaking_news(topics: list, hours_back: int = 24):
    """Get recent breaking news on topics."""
    
    # Use today's date for recent news
    today = datetime.now().strftime("%Y-%m-%d")
    
    print(f"=== Breaking News ({today}) ===\n")
    
    for topic in topics:
        response = valyu.search(
            query=f"{topic} breaking news today",
            search_type="news",
            max_num_results=10,
            start_date=today,
            end_date=today,
        )
        
        if response.get("success") and response["results"]:
            print(f"🔴 {topic.upper()}")
            for article in response["results"][:3]:
                print(f"   • {article['title']}")
                print(f"     {article['url']}")
            print()

# Track breaking news
breaking_news([
    "stock market",
    "federal reserve",
    "technology",
    "politics"
])

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Best Practices

  1. Use date filtering - Always set start_date and end_date for time-sensitive queries
  2. Target regions - Use country_code to focus on specific markets
  3. Request 100 results - For comprehensive coverage, get the increased_max_results permission
  4. Combine with web search - Use search_type="all" when you need both news and web content
  5. Monitor regularly - Set up automated monitoring for ongoing topics
For AI agent workflows, set is_tool_call=true to optimise results for LLM consumption.

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Next Steps

Search Quickstart

Learn the basics of the DeepSearch API

Date Filtering

Advanced date filtering options

Python SDK

Full Python SDK documentation

TypeScript SDK

Full TypeScript SDK documentation