Trends

trends = await location.get_trends()

trends = await client.get_trends('trending')

trends = await client.get_place_trends(woeid)

locations = await client.get_available_locations()

# Get tweets from a trending topic
trends = await client.get_trends('trending', count=10)

for trend in trends[:3]:  # Top 3 trends
    print(f"\nTrend: {trend.name}")
    
    # Search for tweets about this trend
    tweets = await client.search_tweet(trend.name, 'Latest', count=20)
    
    print(f"Found {len(tweets)} recent tweets")
    for tweet in tweets[:5]:
        print(f"  @{tweet.user.screen_name}: {tweet.text[:60]}...")

import asyncio
from datetime import datetime

async def track_trends(duration_minutes=60, interval_minutes=5):
    """Track how trends change over time."""
    trend_history = []
    iterations = duration_minutes // interval_minutes
    
    for i in range(iterations):
        timestamp = datetime.now()
        trends = await client.get_trends('trending', count=10)
        
        trend_names = [t.name for t in trends]
        trend_history.append({
            'timestamp': timestamp,
            'trends': trend_names
        })
        
        print(f"[{timestamp}] Top trend: {trends[0].name}")
        
        if i < iterations - 1:
            await asyncio.sleep(interval_minutes * 60)
    
    return trend_history

# Track trends for 1 hour, checking every 5 minutes
history = await track_trends()

# Get place trends (includes tweet volume)
trends = await client.get_place_trends(1)  # Worldwide

# Sort by tweet volume
sorted_trends = sorted(
    [t for t in trends['trends'] if t.tweet_volume],
    key=lambda x: x.tweet_volume,
    reverse=True
)

print("Trends by Tweet Volume:")
for i, trend in enumerate(sorted_trends[:10], 1):
    print(f"{i}. {trend.name} - {trend.tweet_volume:,} tweets")

from collections import Counter

# Get trends and analyze their contexts
trends = await client.get_trends('trending', count=50)

# Count trends by domain context
contexts = [t.domain_context for t in trends if t.domain_context]
context_counts = Counter(contexts)

print("Trend Contexts:")
for context, count in context_counts.most_common():
    print(f"{context}: {count} trends")

# Find trends with grouped trends
trends_with_groups = [t for t in trends if t.grouped_trends]

print(f"\nTrends with related topics: {len(trends_with_groups)}")
for trend in trends_with_groups[:5]:
    print(f"\n{trend.name}")
    print(f"  Related: {', '.join(trend.grouped_trends)}")

import json

async def create_trend_dashboard():
    """Create a comprehensive trend dashboard."""
    dashboard = {
        'timestamp': datetime.now().isoformat(),
        'categories': {}
    }
    
    categories = ['trending', 'news', 'sports', 'entertainment']
    
    for category in categories:
        trends = await client.get_trends(category, count=10)
        dashboard['categories'][category] = [
            {
                'name': t.name,
                'context': t.domain_context,
                'related': t.grouped_trends
            }
            for t in trends
        ]
    
    # Save to file
    with open('trend_dashboard.json', 'w', encoding='utf-8') as f:
        json.dump(dashboard, f, indent=2, ensure_ascii=False)
    
    print("Dashboard created: trend_dashboard.json")
    return dashboard

dashboard = await create_trend_dashboard()