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Trendspyg

Free, open-source Python library for Google Trends data - pytrends alternative with 188K+ configuration options.

Install / Use

/learn @flack0x/Trendspyg
About this skill

Quality Score

0/100

Supported Platforms

Universal

README

trendspyg

PyPI version PyPI Downloads Python 3.8+ Tests License: MIT

Python library for downloading real-time Google Trends data. A modern alternative to the archived pytrends.

Installation

pip install trendspyg

# With async support
pip install trendspyg[async]

# With CLI
pip install trendspyg[cli]

# All features
pip install trendspyg[all]

Quick Start

RSS Feed (Fast - 0.2s)

from trendspyg import download_google_trends_rss

# Get current trends with news articles
trends = download_google_trends_rss(geo='US')

for trend in trends[:3]:
    print(f"{trend['trend']} - {trend['traffic']}")
    if trend['news_articles']:
        print(f"  {trend['news_articles'][0]['headline']}")

CSV Export (Comprehensive - 10s)

from trendspyg import download_google_trends_csv

# Get 480+ trends with filtering (requires Chrome)
df = download_google_trends_csv(
    geo='US',
    hours=168,            # Past 7 days
    category='sports',
    output_format='dataframe'
)

Async (Parallel Fetching)

import asyncio
from trendspyg import download_google_trends_rss_batch_async

async def main():
    results = await download_google_trends_rss_batch_async(
        ['US', 'GB', 'CA', 'DE', 'JP'],
        max_concurrent=5
    )
    for country, trends in results.items():
        print(f"{country}: {len(trends)} trends")

asyncio.run(main())

CLI

trendspyg rss --geo US
trendspyg csv --geo US-CA --category sports --hours 168
trendspyg list --type countries

Data Sources

| Feature | RSS | CSV | |---------|-----|-----| | Speed | 0.2s | ~10s | | Trends | ~20 | 480+ | | News articles | Yes | No | | Time filtering | No | Yes (4h/24h/48h/7d) | | Category filter | No | Yes (20 categories) | | Requires Chrome | No | Yes |

Features

  • 125 countries + 51 US states
  • 20 categories (sports, tech, health, etc.)
  • 4 time periods (4h, 24h, 48h, 7 days)
  • 4 output formats (dict, DataFrame, JSON, CSV)
  • Async support for parallel fetching
  • Built-in caching (5-min TTL)
  • CLI for terminal access

Caching

from trendspyg import clear_rss_cache, get_rss_cache_stats

# Results are cached for 5 minutes by default
trends = download_google_trends_rss(geo='US')  # Network call
trends = download_google_trends_rss(geo='US')  # From cache

# Bypass cache
trends = download_google_trends_rss(geo='US', cache=False)

# Check cache stats
print(get_rss_cache_stats())

# Clear cache
clear_rss_cache()

Documentation

Requirements

  • Python 3.8+
  • Chrome browser (for CSV export only)

License

MIT License - see LICENSE for details.

Links

Related Skills

View on GitHub
GitHub Stars27
CategoryDevelopment
Updated20h ago
Forks4

Languages

Python

Security Score

90/100

Audited on Apr 8, 2026

No findings