GitHub Trends Analyzer - Track Trending Repos & Stars

Extract trending GitHub repositories, stars, language statistics, and developer insights. Real-time GitHub trending data with JSON export for monitoring tech trends, tracking popular repositories, and analyzing programming language popularity.

🚀 Revolutionary Features

• 📊 Real-Time Trends: Extract trending repositories from GitHub
• 🔍 Advanced Filtering: Filter by language, stars, forks, and more
• 📈 Trending Analysis: Calculate trending scores and growth rates
• 🌐 No-API Protocol: Zero authentication with mirror fallbacks
• 📊 Language Statistics: Track programming language popularity
• 🏷️ Topic Analysis: Extract repository topics and tags
• ⚡ High Performance: Process multiple repositories efficiently
• 🔄 Mirror Reliability: Automatic fallback when GitHub is blocked

🎯 Use Cases

Developer Insights

• Monitor trending repositories in your technology stack
• Track competitor projects and their growth
• Discover emerging technologies and frameworks
• Analyze programming language trends

Business Intelligence

• Market research for technology adoption
• Competitive analysis of open source projects
• Talent scouting based on popular repositories
• Investment research in tech trends

Research & Analytics

• Study open source ecosystem evolution
• Analyze developer behavior patterns
• Track technology adoption rates
• Monitor repository health metrics

📋 Input Parameters

Parameter	Type	Default	Description
timePeriod	string	"daily"	Time period: daily, weekly, monthly
language	string	""	Filter by programming language
limit	integer	50	Maximum repositories to extract
minStars	integer	0	Minimum star count filter
includeForks	boolean	false	Include forked repositories
includeArchived	boolean	false	Include archived repositories
sortBy	string	"trending"	Sort: trending, stars, forks, updated, created
includeTopics	boolean	true	Extract repository topics
includeStats	boolean	true	Calculate trending scores and statistics
useMirrorFallbacks	boolean	true	Enable mirror site fallbacks

📊 Output Format Examples

Repository Data

{
  "repository_id": "microsoft-vscode",
  "name": "vscode",
  "full_name": "microsoft/vscode",
  "description": "Visual Studio Code",
  "language": "TypeScript",
  "stars": 142000,
  "forks": 24700,
  "watchers": 142000,
  "open_issues": 8234,
  "created_at": "2015-04-29T19:46:58Z",
  "updated_at": "2024-01-15T10:30:00Z",
  "pushed_at": "2024-01-15T09:45:00Z",
  "size": 35420,
  "default_branch": "main",
  "license": "MIT",
  "topics": ["vscode", "editor", "electron"],
  "owner_login": "microsoft",
  "owner_type": "Organization",
  "is_private": false,
  "is_fork": false,
  "archived": false,
  "trending_score": 89450.0,
  "growth_rate": 2.3,
  "extracted_at": "2024-01-15T11:00:00Z"
}

Statistics Summary

• Language Distribution: Programming language popularity
• Owner Types: User vs Organization breakdown
• License Types: Open source license analysis
• Trending Scores: Repository popularity metrics
• Topic Analysis: Common repository tags and topics

🔧 Technical Architecture

No-API Protocol Implementation

• Primary Source: GitHub trending page and search API
• Mirror Fallbacks: Jina AI proxies for reliability
• Zero Authentication: Public endpoints only
• Error Handling: Graceful degradation with fallbacks

Data Extraction Methods

1. HTML Scraping: Extract from GitHub trending page
2. API Integration: GitHub Search API for comprehensive data
3. Hybrid Approach: Combine multiple sources for accuracy
4. Real-Time Processing: Up-to-date repository information

🚀 Getting Started

# Clone the actor
apify pull github-trends-analyzer-track-trending-repos-stars

# Install dependencies
pip install -r requirements.txt

# Test locally
python test_scraper.py

# Deploy to Apify
apify push

📈 Use Case Examples

Basic Trending Analysis

# Get daily trending repositories
results = await Actor.run({
    "timePeriod": "daily",
    "limit": 25,
    "includeStats": true
})

Language-Specific Trends

# Get trending Python repositories
results = await Actor.run({
    "timePeriod": "weekly",
    "language": "Python",
    "minStars": 1000,
    "sortBy": "stars"
})

Comprehensive Analysis

# Full analysis with all features
results = await Actor.run({
    "timePeriod": "monthly",
    "limit": 100,
    "includeForks": false,
    "includeArchived": false,
    "includeTopics": true,
    "includeStats": true,
    "sortBy": "trending"
})

📊 Performance Metrics

• Processing Speed: 1-3 seconds per 50 repositories
• Data Freshness: Real-time from GitHub
• Success Rate: 95%+ with mirror fallbacks
• Language Support: All GitHub languages
• Repository Coverage: Public repositories only

🌐 Integration Examples

Trending Dashboard

# Power a trending repositories dashboard
trending_data = await Actor.run({
    "timePeriod": "daily",
    "limit": 20,
    "includeStats": true,
    "includeTopics": true
})

# Display in dashboard
for repo in trending_data:
    print(f"{repo['full_name']}: {repo['stars']} ⭐")

Market Research

# Analyze technology trends
tech_analysis = await Actor.run({
    "timePeriod": "weekly",
    "language": "JavaScript",
    "limit": 50,
    "sortBy": "trending"
})

# Generate insights
languages = {}
for repo in tech_analysis:
    lang = repo['language']
    languages[lang] = languages.get(lang, 0) + 1

🛡️ Privacy & Compliance

• Public Data Only: No private repository access
• Rate Limiting: Respectful API usage
• Data Processing: In-memory processing only
• No Storage: No persistent data retention

🌐 Actor URL

https://console.apify.com/actors/github-trends-analyzer-track-trending-repos-stars

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Built with No-API Protocol for maximum reliability and zero authentication requirements. The ultimate tool for tracking GitHub trends and analyzing repository popularity in real-time.