# GitHub Trending Scraper (`pink_fence/github-trending-scraper`) Actor

Scrape GitHub Trending repos — name, description, stars, forks, language and contributors. Filter by programming language and time range: daily, weekly or monthly. No API key needed. Clean JSON output.

- **URL**: https://apify.com/pink\_fence/github-trending-scraper.md
- **Developed by:** [Moritz Knopp](https://apify.com/pink_fence) (community)
- **Categories:** Developer tools
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.00005 / actor start

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## GitHub Trending Scraper

This Apify Actor scrapes the GitHub Trending page and returns structured data for each trending repository, including rank, stars, forks, language, description, and contributor usernames. You can filter results by programming language and trending period (daily, weekly, or monthly).

### Input Parameters

| Field | Type | Required | Default | Description |
| --- | --- | --- | --- | --- |
| language | string | No | "" | Programming language filter e.g. python, javascript, rust. Leave empty for all languages. |
| since | string | No | "daily" | Time range for trending repos. Allowed values: daily, weekly, monthly. |

### Output Fields

| Field | Type | Description |
| --- | --- | --- |
| rank | integer | Rank position on the Trending page (usually 1-25). |
| repoName | string | Repository name in owner/repo format. |
| repoUrl | string | Full GitHub URL to the repository. |
| description | string | Repository description text. |
| language | string | Main programming language (can be empty). |
| totalStars | integer | Total GitHub stars for the repository. |
| starsToday | integer | Stars gained today (or in the selected period label on GitHub UI). |
| forks | integer | Number of forks. |
| contributors | array of strings | GitHub usernames shown in the Built by section. |

### Example Input

```json
{
  "language": "python",
  "since": "weekly"
}
```

### Example Output

```json
[
  {
    "rank": 1,
    "repoName": "acme-ai/fast-trainer",
    "repoUrl": "https://github.com/acme-ai/fast-trainer",
    "description": "High-performance model training toolkit for Python.",
    "language": "Python",
    "totalStars": 15432,
    "starsToday": 983,
    "forks": 1275,
    "contributors": ["janedoe", "mario", "sunnydev"]
  },
  {
    "rank": 2,
    "repoName": "data-labs/stream-inspector",
    "repoUrl": "https://github.com/data-labs/stream-inspector",
    "description": "Inspect and replay streaming datasets with one command.",
    "language": "Go",
    "totalStars": 8410,
    "starsToday": 522,
    "forks": 604,
    "contributors": ["kevinq", "linhtran"]
  }
]
```

# Actor input Schema

## `language` (type: `string`):

Programming language filter e.g. python, javascript, rust. Leave empty for all languages.

## `since` (type: `string`):

Time range for trending repos

## Actor input object example

```json
{
  "language": "",
  "since": "daily"
}
```

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {};

// Run the Actor and wait for it to finish
const run = await client.actor("pink_fence/github-trending-scraper").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {}

# Run the Actor and wait for it to finish
run = client.actor("pink_fence/github-trending-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{}' |
apify call pink_fence/github-trending-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,pink_fence/github-trending-scraper"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/fdxVajdwb0A10XZEh/builds/701GMybvBJNH9hGOR/openapi.json