# GitHub Trending & Topic Scraper (`viralanalyzer/github-trending-by-topic`) Actor Scrapes GitHub trending repositories by language and date, or searches popular repositories by technical topic (LLM, AI, Agents) with high-speed hybrid extraction. - **URL**: https://apify.com/viralanalyzer/github-trending-by-topic.md - **Developed by:** [viralanalyzer](https://apify.com/viralanalyzer) (community) - **Categories:** Developer tools - **Stats:** 2 total users, 1 monthly users, 50.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## 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 ## GitHub Trending & Topic Scraper 🚀 **GitHub Trending & Topic Scraper** is a high-speed, lightweight developer tool designed to track emerging technology trends, popular repositories, and daily/weekly/monthly trending charts on GitHub. It works **100% anonymously** without requiring any GitHub OAuth credentials or personal access tokens, ensuring absolute safety for your accounts. --- ### 🌟 Key Features 1. **Dual Mode Extraction**: - **Trending Mode**: Scrape the official GitHub Trending page (`https://github.com/trending`) filtered by programming language and timeframe (daily, weekly, monthly). - **Topic Mode**: Fetch the most popular and starred repositories for specific technical keywords or topics (e.g. `llm`, `generative-ai`, `agents`, `react`). 2. **Hybrid Evasion Architecture**: - Uses `got-scraping` dynamic browser fingerprinting to prevent bot detection. - Built-in automatic API search query execution, with a robust **Cheerio HTML scraper fallback** if GitHub's search API rate limits are reached. 3. **Optimized and Cost-Effective**: - Fast, serverless, and runs on only 256MB RAM. - Leverages Pay-Per-Event (PPE) charging, making it extremely cost-effective. --- ### 💰 Pricing — Pay-Per-Event (PPE) This actor is charged dynamically based on the volume of data delivered to you: - **$0.01 USD** per repository scraped (`repo-scraped` event). - Owner runs skip billing automatically. --- ### 📥 Input Parameters | Parameter | Type | Default | Description | | :--- | :--- | :--- | :--- | | `mode` | String | `trending` | Scraping mode: `trending` or `topic`. | | `language` | String | `""` | Programming language (e.g. `python`, `typescript`) for trending mode. | | `since` | String | `daily` | Time window: `daily`, `weekly`, or `monthly` for trending mode. | | `topic` | String | `"llm"` | Technical topic keyword for topic mode. | | `maxItems` | Integer | `25` | Max number of repositories to return (5–200). | | `proxyConfiguration` | Object | `{"useApifyProxy": true}` | Proxy configuration. | --- ### 📤 Output Structure Each item in the dataset contains the following parsed fields: ```json { "repoName": "DeepSeek-V3", "owner": "deepseek-ai", "url": "https://github.com/deepseek-ai/DeepSeek-V3", "description": "DeepSeek-V3 is a strong Mixture-of-Experts language model.", "language": "Python", "stars": 42890, "forks": 3890, "starsAdded": 2840, "scrapedAt": "2026-05-24T19:20:00.000Z" } ```` *** ### 🇵🇹 Versão em Português **GitHub Trending & Topic Scraper** é uma ferramenta leve e de alta velocidade para monitorar tendências tecnológicas emergentes e repositórios populares no GitHub. #### Recursos: - **Modo Trending**: Coleta a página oficial de tendências (`https://github.com/trending`) filtrada por linguagem e período de tempo (diário, semanal ou mensal). - **Modo Topic**: Extrai os repositórios mais populares e estrelados para tópicos específicos (ex: `llm`, `agents`, `react`). - **Segurança Total**: Executa 100% de forma anônima, sem requerer logins ou chaves de API do GitHub. - **Cobrança PPE Econômica**: Apenas **$0.01 USD** por repositório entregue. # Actor input Schema ## `mode` (type: `string`): Choose between official daily/weekly/monthly trending charts or searching popular repositories by topic/technology keyword. ## `language` (type: `string`): Optional programming language to filter official trending charts (e.g. javascript, python, go, rust). Only used in 'trending' mode. ## `since` (type: `string`): Time window for official trending charts. Only used in 'trending' mode. ## `topic` (type: `string`): Technology topic or keyword to search (e.g. llm, generative-ai, agents, machine-learning). Only used in 'topic' mode. ## `maxItems` (type: `integer`): Maximum number of repositories to scrape. ## `proxyConfiguration` (type: `object`): GitHub reads are lightweight, but using a proxy is recommended to avoid rate limits. ## Actor input object example ```json { "mode": "trending", "language": "", "since": "daily", "topic": "llm", "maxItems": 25, "proxyConfiguration": { "useApifyProxy": true } } ``` # Actor output Schema ## `results` (type: `string`): Dataset of all results; each item follows the dataset schema. # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = {}; // Run the Actor and wait for it to finish const run = await client.actor("viralanalyzer/github-trending-by-topic").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${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 = {} # Run the Actor and wait for it to finish run = client.actor("viralanalyzer/github-trending-by-topic").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 '{}' | apify call viralanalyzer/github-trending-by-topic --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=viralanalyzer/github-trending-by-topic", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "GitHub Trending & Topic Scraper", "description": "Scrapes GitHub trending repositories by language and date, or searches popular repositories by technical topic (LLM, AI, Agents) with high-speed hybrid extraction.", "version": "1.0", "x-build-id": "qKueR4JdergxcVFYB" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/viralanalyzer~github-trending-by-topic/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-viralanalyzer-github-trending-by-topic", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/viralanalyzer~github-trending-by-topic/runs": { "post": { "operationId": "runs-sync-viralanalyzer-github-trending-by-topic", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/viralanalyzer~github-trending-by-topic/run-sync": { "post": { "operationId": "run-sync-viralanalyzer-github-trending-by-topic", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "required": [ "mode", "maxItems" ], "properties": { "mode": { "title": "Scraping Mode", "enum": [ "trending", "topic" ], "type": "string", "description": "Choose between official daily/weekly/monthly trending charts or searching popular repositories by topic/technology keyword.", "default": "trending" }, "language": { "title": "Programming Language", "type": "string", "description": "Optional programming language to filter official trending charts (e.g. javascript, python, go, rust). Only used in 'trending' mode.", "default": "" }, "since": { "title": "Trending Period", "enum": [ "daily", "weekly", "monthly" ], "type": "string", "description": "Time window for official trending charts. Only used in 'trending' mode.", "default": "daily" }, "topic": { "title": "Topic Keyword", "type": "string", "description": "Technology topic or keyword to search (e.g. llm, generative-ai, agents, machine-learning). Only used in 'topic' mode.", "default": "llm" }, "maxItems": { "title": "Maximum Repositories", "minimum": 5, "maximum": 200, "type": "integer", "description": "Maximum number of repositories to scrape.", "default": 25 }, "proxyConfiguration": { "title": "Proxy Configuration", "type": "object", "description": "GitHub reads are lightweight, but using a proxy is recommended to avoid rate limits.", "default": { "useApifyProxy": true } } } }, "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 } } } } } } } } } } ```