# GitHub Trending Repositories Scraper (`taizen/github-trending-scraper`) Actor Scrapes GitHub trending repositories by programming language and time range (daily, weekly, monthly). Extracts repo name, description, language, stars, forks, and stars gained today. - **URL**: https://apify.com/taizen/github-trending-scraper.md - **Developed by:** [Adnane Saber](https://apify.com/taizen) (community) - **Categories:** Agents, Social media, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.03 / 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/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. 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. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use 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 ## JavaScript Crawlee & CheerioCrawler Actor Template This template example was built with [Crawlee](https://crawlee.dev/) to scrape data from a website using [Cheerio](https://cheerio.js.org/) wrapped into [CheerioCrawler](https://crawlee.dev/api/cheerio-crawler/class/CheerioCrawler). ### Quick Start Once you've installed the dependencies, start the Actor: ```bash apify run ```` Once your Actor is ready, you can push it to the Apify Console: ```bash apify login # first, you need to log in if you haven't already done so apify push ``` ### Project Structure ```text .actor/ ├── actor.json # Actor config: name, version, env vars, runtime settings ├── dataset_schema.json # Structure and representation of data produced by an Actor ├── input_schema.json # Input validation & Console form definition └── output_schema.json # Specifies where an Actor stores its output src/ └── main.js # Actor entry point and orchestrator storage/ # Local storage (mirrors Cloud during development) ├── datasets/ # Output items (JSON objects) ├── key_value_stores/ # Files, config, INPUT └── request_queues/ # Pending crawl requests Dockerfile # Container image definition ``` For more information, see the [Actor definition](https://docs.apify.com/platform/actors/development/actor-definition) documentation. ### How it works This code is a JavaScript script that uses Cheerio to scrape data from a website. It then stores the website titles in a dataset. - The crawler starts with URLs provided from the input `startUrls` field defined by the input schema. Number of scraped pages is limited by `maxPagesPerCrawl` field from the input schema. - The crawler uses `requestHandler` for each URL to extract the data from the page with the Cheerio library and to save the title and URL of each page to the dataset. It also logs out each result that is being saved. ### What's included - **[Apify SDK](https://docs.apify.com/sdk/js)** - toolkit for building [Actors](https://apify.com/actors) - **[Crawlee](https://crawlee.dev/)** - web scraping and browser automation library - **[Input schema](https://docs.apify.com/platform/actors/development/input-schema)** - define and easily validate a schema for your Actor's input - **[Dataset](https://docs.apify.com/sdk/python/docs/concepts/storages#working-with-datasets)** - store structured data where each object stored has the same attributes - **[Cheerio](https://cheerio.js.org/)** - a fast, flexible & elegant library for parsing and manipulating HTML and XML - **[Proxy configuration](https://docs.apify.com/platform/proxy)** - rotate IP addresses to prevent blocking ### Resources - [Quick Start](https://docs.apify.com/platform/actors/development/quick-start) guide for building your first Actor - [Video tutorial](https://www.youtube.com/watch?v=yTRHomGg9uQ) on building a scraper using CheerioCrawler - [Written tutorial](https://docs.apify.com/academy/web-scraping-for-beginners/challenge) on building a scraper using CheerioCrawler - [Web scraping with Cheerio in 2023](https://blog.apify.com/web-scraping-with-cheerio/) - How to [scrape a dynamic page](https://blog.apify.com/what-is-a-dynamic-page/) using Cheerio - [Integration with Zapier](https://apify.com/integrations), Make, Google Drive and others - [Video guide on getting data using Apify API](https://www.youtube.com/watch?v=ViYYDHSBAKM) ### Creating Actors with templates [How to create Apify Actors with web scraping code templates](https://www.youtube.com/watch?v=u-i-Korzf8w) ### Getting started For complete information [see this article](https://docs.apify.com/platform/actors/development#build-actor-locally). To run the Actor use the following command: ```bash apify run ``` ### Deploy to Apify #### Connect Git repository to Apify If you've created a Git repository for the project, you can easily connect to Apify: 1. Go to [Actor creation page](https://console.apify.com/actors/new) 2. Click on **Link Git Repository** button #### Push project on your local machine to Apify You can also deploy the project on your local machine to Apify without the need for the Git repository. 1. Log in to Apify. You will need to provide your [Apify API Token](https://console.apify.com/account/integrations) to complete this action. ```bash apify login ``` 2. Deploy your Actor. This command will deploy and build the Actor on the Apify Platform. You can find your newly created Actor under [Actors -> My Actors](https://console.apify.com/actors?tab=my). ```bash apify push ``` ### Documentation reference To learn more about Apify and Actors, take a look at the following resources: - [Apify SDK for JavaScript documentation](https://docs.apify.com/sdk/js) - [Apify SDK for Python documentation](https://docs.apify.com/sdk/python) - [Apify Platform documentation](https://docs.apify.com/platform) - [Join our developer community on Discord](https://discord.com/invite/jyEM2PRvMU) # Actor input Schema ## `languages` (type: `array`): List of programming languages to scrape trending repositories for. Leave empty to scrape all languages. ## `timeRange` (type: `string`): The time period for trending repositories. ## `maxResultsPerPage` (type: `integer`): Maximum number of repositories to return per language page. GitHub displays up to 25 trending repos per page. ## Actor input object example ```json { "languages": [ "javascript", "python", "go" ], "timeRange": "daily", "maxResultsPerPage": 25 } ``` # 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 '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "languages": [ "javascript", "python", "go" ] }; // Run the Actor and wait for it to finish const run = await client.actor("taizen/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 '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "languages": [ "javascript", "python", "go", ] } # Run the Actor and wait for it to finish run = client.actor("taizen/github-trending-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "languages": [ "javascript", "python", "go" ] }' | apify call taizen/github-trending-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=taizen/github-trending-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "GitHub Trending Repositories Scraper", "description": "Scrapes GitHub trending repositories by programming language and time range (daily, weekly, monthly). Extracts repo name, description, language, stars, forks, and stars gained today.", "version": "0.1", "x-build-id": "wmeQxPi7wCchxxPmT" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/taizen~github-trending-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-taizen-github-trending-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/taizen~github-trending-scraper/runs": { "post": { "operationId": "runs-sync-taizen-github-trending-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/taizen~github-trending-scraper/run-sync": { "post": { "operationId": "run-sync-taizen-github-trending-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "languages": { "title": "Programming Languages", "type": "array", "description": "List of programming languages to scrape trending repositories for. Leave empty to scrape all languages.", "items": { "type": "string" } }, "timeRange": { "title": "Time Range", "enum": [ "daily", "weekly", "monthly" ], "type": "string", "description": "The time period for trending repositories.", "default": "daily" }, "maxResultsPerPage": { "title": "Max Results Per Page", "minimum": 1, "maximum": 25, "type": "integer", "description": "Maximum number of repositories to return per language page. GitHub displays up to 25 trending repos per page.", "default": 25 } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```