GitHub Trending Radar — Fast Growth Repos & Stars Deltas

Discover fast-growing GitHub repositories with real star-gain deltas across programming languages and topics. Unlike static trending snapshots, this Actor preserves snapshots between runs so you see exactly how many stars each repo gained over time.

Designed for open-source intelligence newsletters, venture capital scouts, tech talent recruiters, and automated engineering radars.

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What this Actor does

This Actor monitors GitHub Trending feeds and historical snapshots to surface momentum:

• Star Gain Deltas: Calculates absolute (starsGained) and percentage (starsGainedPct) growth between runs using Apify Key-Value Store snapshots.
• Language Filtering: Filter trending repos by programming language (e.g. python, typescript, rust, go, or all).
• Time Window Flexibility: Select daily, weekly, or monthly trending windows.
• Enriched Project Metadata: Repo name, maintainer, description, primary language, repository URL, topic tags, and fork counts.

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Why use this Actor

• Deltas, Not Just Static Lists: Standard GitHub trending scrapers simply copy the current page. This Actor tells you the real velocity by comparing against historical snapshots.
• Lightweight & High-Speed: Operates via efficient HTML extraction with zero heavy browser overhead.
• Perfect for Scheduled Automation: Schedule daily or weekly runs in the Apify Console and trigger webhooks (Slack, Discord, Email) when a breakthrough repository surges.
• RAG & Agent Ready: Normalized JSON schema ready for LLMs to generate weekly dev digests or VC deal-flow summaries.

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Features

• Multi-Language sweeps: Process multiple programming languages in a single run.
• Automated Snapshot Persistence: Automatically manages rolling Key-Value Store entries to calculate growth deltas.
• Pay-Per-Event Economy: Minimal footprint — pay only $0.0003 per trending repo discovered.

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Use cases

• VC & Tech Investors: Identify breakaway open-source developer tooling before it hits Hacker News or tech Twitter.
• Developer Newsletters: Automate "Trending Projects of the Week" writeups with accurate star growth counts.
• Competitive Tracking: Monitor growth trajectories of competing open-source libraries in your domain.
• Talent Discovery: Spot new repositories gaining fast adoption to connect with promising maintainers.

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Input

Field	Type	Description	Default	Example
languages	Array of Strings	Filter by programming languages. Leave empty for all languages.	["python", "typescript"]	["rust", "go", "python"]
since	String (Select)	Trending time window: daily, weekly, or monthly.	"daily"	"daily"
maxRepos	Integer	Maximum repositories to return per language (1 to 100).	25	25
storeSnapshot	Boolean	Save snapshot to Apify Key-Value Store for next-run delta calculation.	true	true

Example input

{
  "languages": ["python", "typescript", "rust"],
  "since": "daily",
  "maxRepos": 25,
  "storeSnapshot": true
}

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Output

Every trending repository is output as an individual item into your default dataset.

Field Definitions

• rank (Integer): Position rank on the trending leaderboard.
• repo (String): Repository name.
• owner (String): Owner username or organization.
• description (String): Project description.
• url (String): Direct GitHub repository URL.
• language (String | null): Primary language.
• stars (Integer): Total current stargazers.
• starsGained (Integer): Stars gained during the period or since last snapshot.
• starsGainedPct (Float | null): Percentage growth in stars since last snapshot.
• forks (Integer): Fork count.
• topics (Array of Strings): Topic tags.
• since (String): Time window (daily, weekly, monthly).
• snapshotDate (ISO Date): Extraction timestamp.
• starsLastSnapshot (Integer | null): Previous star count recorded in the key-value store.

Example output

{
  "rank": 1,
  "repo": "open-webui",
  "owner": "open-webui",
  "description": "User-friendly AI Interface (Supports Ollama, OpenAI API, and more)",
  "url": "https://github.com/open-webui/open-webui",
  "language": "python",
  "stars": 54200,
  "starsGained": 1240,
  "starsGainedPct": 2.34,
  "forks": 6100,
  "topics": ["ai", "chatgpt", "llm", "ollama", "python"],
  "since": "daily",
  "snapshotDate": "2026-09-28T03:59:02.523Z",
  "starsLastSnapshot": 52960
}

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Pricing (Pay-Per-Event)

Event Name	Price (USD)	Charged When
actor-start	$0.01	Charged once when run initializes
trend-item	$0.0003	Charged per trending repository item delivered

Example cost: Scanning 3 languages for 25 trending repos each (75 items) costs $0.01 (start) + (75 × $0.0003 = $0.0225) = $0.0325 total.

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API usage

Python

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_API_TOKEN")

run = client.actor("lovely_radiologist/github-trending-radar").call(run_input={
    "languages": ["python", "rust"],
    "since": "daily"
})

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(f"#{item['rank']} {item['owner']}/{item['repo']} (+{item['starsGained']} stars)")

Node.js

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_APIFY_API_TOKEN' });

const run = await client.actor('lovely_radiologist/github-trending-radar').call({
    languages: ['typescript', 'python'],
    since: 'daily'
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(`Found ${items.length} trending repos`);

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Limitations

• Delta Baseline: On your very first run, starsLastSnapshot will be initialized. Delta percentages calculate from the second run onwards.
• GitHub Trending Surface: Reflects repositories highlighted by GitHub's public trending algorithm.

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FAQ

Can I schedule this to run automatically?

Yes. Go to the Schedules tab in your Apify Console and set a daily schedule (e.g. 0 8 * * * at 8:00 AM UTC).

What happens if a language has fewer repos trending?

The Actor cleanly returns all available trending repositories for that language without failing.

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Support & Related Actors

• GitHub Repository Insights — Deep-dive repo health, dependencies, and contributor metrics for trending repos.
• GitHub Organization / Team Scraper — Profile the entire team behind a top project.
• Hugging Face Daily Trends Tracker — Track trending machine learning models and Open LLM leaderboards.