# Dollar Hunter - Multi-Source Data API (`chuckling_yarn/dollar-hunter-multi-source`) Actor Fetch structured data from GitHub, Hacker News, and Reddit. No browser needed, instant results, minimal cost. - **URL**: https://apify.com/chuckling\_yarn/dollar-hunter-multi-source.md - **Developed by:** [Jonatan J. Martinez Collymoore](https://apify.com/chuckling_yarn) (community) - **Categories:** Developer tools, News, Social media - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.01 / 1,000 results 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/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.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/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 ## Multi-Source Data API — GitHub, HN & Reddit 🚀 **Apify Actor** that fetches trending data from **GitHub**, **Hacker News**, and **Reddit** in one unified API call. Built for content curators, developer dashboard builders, news aggregators, and trend researchers. > ⚡ **Zero browser overhead** — all data comes via free REST APIs, so runs are fast and cheap. --- ### Features ✨ | Feature | Description | |---------|-------------| | **3 Sources, 1 API** | Fetch from GitHub Trending, Hacker News top stories, Reddit hot posts, or all at once | | **Smart Retry Logic** | Automatic 3-attempt retry with exponential backoff on network errors and rate limits | | **Rate Limit Handling** | Detects 429 responses and waits for `Retry-After` headers automatically | | **Parallel Fetching** | When using `all` sources, fetches in parallel for maximum speed | | **Customizable Filters** | Language filter for GitHub, subreddit selection for Reddit, time period for age | | **Input Validation** | Validates all inputs before making API calls | | **Detailed Logging** | Emoji-rich console output at every step for full transparency | --- ### Input Schema 📥 | Parameter | Type | Default | Description | |-----------|------|---------|-------------| | `source` | select | `github` | Data source: `github`, `hackernews`, `reddit`, or `all` | | `language` | string | `python` | Programming language filter for GitHub trending | | `subreddit` | string | `programming` | Subreddit to fetch hot posts from | | `maxResults` | integer | `15` | Max items per source (1–100) | | `since` | select | `24h` | Time period: `24h`, `7d`, or `30d` | #### Example input ```json { "source": "all", "language": "typescript", "subreddit": "webdev", "maxResults": 10, "since": "7d" } ```` *** ### Output Schema 📤 The actor pushes a single dataset entry with this structure: ```json { "source": "all", "totalResults": 30, "fetchedAt": "2026-07-17T12:00:00.000Z", "config": { "language": "typescript", "subreddit": "webdev", "maxResults": 10, "since": "7d" }, "results": [ { "_source": "github", "name": "vercel/ai", "stars": 12450, "forks": 1200, "description": "Build AI-powered applications...", "url": "https://github.com/vercel/ai", "language": "TypeScript", "topics": ["ai", "llm", "sdk"] }, { "_source": "hackernews", "title": "Show HN: A new open-source database", "url": "https://example.com", "score": 342, "by": "username", "type": "story", "descendants": 87 }, { "_source": "reddit", "title": "What are you building?", "url": "https://reddit.com/r/webdev/...", "score": 156, "subreddit": "webdev", "comments": 43, "author": "user123" } ] } ``` #### Result fields by source | Source | Key Fields | |--------|------------| | **GitHub** | `name`, `stars`, `forks`, `description`, `url`, `language`, `topics`, `starsToday` | | **Hacker News** | `title`, `url`, `score`, `by`, `type`, `descendants`, `time` | | **Reddit** | `title`, `url`, `permalink`, `score`, `subreddit`, `comments`, `author`, `domain` | All results include a `_source` field indicating the origin (`github`, `hackernews`, or `reddit`). When using `all` mode, results are sorted by score/stars descending. *** ### Use Cases 🎯 #### 1. Developer Dashboard Widget Display trending GitHub repos, popular HN discussions, and active Reddit threads in a single developer dashboard panel. ```json // Input: {"source": "all", "language": "javascript", "maxResults": 5, "since": "24h"} ``` #### 2. News & Content Aggregator Build a daily digest of the most important developer news across all three platforms without managing separate integrations. ```json // Input: {"source": "all", "maxResults": 20, "since": "24h"} ``` #### 3. Trend Monitoring Bot Track what's gaining traction in a specific language ecosystem (e.g., Rust) by monitoring GitHub repos, HN discussions, and Reddit posts. ```json // Input: {"source": "all", "language": "rust", "subreddit": "rust", "maxResults": 10, "since": "7d"} ``` #### 4. Social Proof & Link Curation Find high-engagement content for newsletters, social media posts, or blog references by scoring across platforms. ```json // Input: {"source": "hackernews", "maxResults": 30, "since": "24h"} ``` #### 5. Competitive Research Track what open-source projects are trending in your competitor's tech stack. ```json // Input: {"source": "github", "language": "python", "maxResults": 25, "since": "7d"} ``` #### 6. Multilingual Community Monitoring Monitor niche subreddits and language-specific GitHub repos for emerging technologies. ```json // Input: {"source": "all", "language": "kotlin", "subreddit": "androiddev", "maxResults": 10} ``` *** ### FAQ ❓ #### Q: Why is Reddit returning no data? **A:** As of mid-2023, Reddit restricts API access from many cloud IP ranges (including Apify's). The Reddit source tries multiple endpoints but will gracefully fail with a clear message if blocked. To use Reddit data reliably, consider setting up a Reddit OAuth app or running the actor from a residential IP. #### Q: Is this actor free to use? **A:** Yes! All three data sources (GitHub, HN, Reddit) use free public REST APIs. You only pay for Apify platform compute time, which is minimal since there's no browser overhead. #### Q: How many results can I fetch? **A:** Up to 100 per source. Using `all` mode with `maxResults: 100` fetches up to 300 total items (100 from each source). #### Q: What happens if one source fails? **A:** In `all` mode, each source is fetched independently. If one fails (e.g., GitHub rate limited), the other two still return data. Failures are logged clearly. #### Q: Does the actor handle API rate limits? **A:** Yes! It automatically detects 429 (Too Many Requests) responses and respects `Retry-After` headers with exponential backoff. GitHub rate limit remaining is logged after each request. #### Q: What time period options are available? **A:** `24h` (last 24 hours), `7d` (last 7 days), or `30d` (last 30 days). This primarily affects GitHub's search query; HN and Reddit always return their current top/hot lists. #### Q: Can I run this on a schedule? **A:** Absolutely. Set up an Apify schedule (e.g., every 6 hours) to build a continuous data pipeline for dashboards or monitoring. #### Q: What's in the `_source` field? **A:** Every result includes `_source` set to `"github"`, `"hackernews"`, or `"reddit"` so you can easily filter or tag items by origin in downstream processing. *** ### Pricing 💰 This actor uses **free REST APIs** — no paid API keys required. Apify platform charges are based on compute time only, which is typically **under 3 seconds per run** (~$0.001 USD per run on Apify). Scheduled runs at any interval are cost-effective. *** ### Technical Notes 🔧 - **Runtime:** Node.js 20 (Playwright image — retained for compatibility, but Playwright is not used) - **Retry Strategy:** 3 attempts with exponential backoff (1s → 2s → 4s, capped at 15s) - **Timeout:** 30s per individual request - **Edge Cases Handled:** - Empty responses from any source - Network timeouts and connection resets - Rate limiting (429) with Retry-After support - Missing fields in API responses (graceful fallback to defaults) - Invalid subreddit names (returns empty array) - Malformed JSON responses (caught and logged) - Partial failures in `all` mode (other sources still return data) *** *Built with ❤️ for the Dollar Hunter project — set & forget income through automation.* # Actor input Schema ## `source` (type: `string`): Which source(s) to fetch data from. Choose 'github' for trending repos, 'hackernews' for top stories, 'reddit' for hot posts, or 'all' to combine all three sources. ## `language` (type: `string`): Programming language filter for GitHub trending repositories. Examples: python, javascript, typescript, rust, go, java, swift, kotlin, cpp, ruby ## `subreddit` (type: `string`): Subreddit to fetch hot posts from. Popular choices: programming, python, javascript, rust, golang, webdev, datascience, machinelearning, devops ## `maxResults` (type: `integer`): Maximum number of results to return per source (1-100). When using 'all', up to this many items are fetched from each source then combined and sorted. ## `since` (type: `string`): Time period filter applied to GitHub trending repositories. '24h' = last day, '7d' = last week, '30d' = last month. ## Actor input object example ```json { "source": "github", "language": "python", "subreddit": "programming", "maxResults": 15, "since": "24h" } ``` # 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("chuckling_yarn/dollar-hunter-multi-source").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("chuckling_yarn/dollar-hunter-multi-source").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 chuckling_yarn/dollar-hunter-multi-source --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=chuckling_yarn/dollar-hunter-multi-source", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Dollar Hunter - Multi-Source Data API", "description": "Fetch structured data from GitHub, Hacker News, and Reddit. No browser needed, instant results, minimal cost.", "version": "2.0", "x-build-id": "gcu2tSzOfDzId9y3c" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/chuckling_yarn~dollar-hunter-multi-source/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-chuckling_yarn-dollar-hunter-multi-source", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/chuckling_yarn~dollar-hunter-multi-source/runs": { "post": { "operationId": "runs-sync-chuckling_yarn-dollar-hunter-multi-source", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/chuckling_yarn~dollar-hunter-multi-source/run-sync": { "post": { "operationId": "run-sync-chuckling_yarn-dollar-hunter-multi-source", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "source": { "title": "Data Source", "enum": [ "github", "hackernews", "reddit", "all" ], "type": "string", "description": "Which source(s) to fetch data from. Choose 'github' for trending repos, 'hackernews' for top stories, 'reddit' for hot posts, or 'all' to combine all three sources.", "default": "github" }, "language": { "title": "GitHub Language Filter", "type": "string", "description": "Programming language filter for GitHub trending repositories. Examples: python, javascript, typescript, rust, go, java, swift, kotlin, cpp, ruby", "default": "python" }, "subreddit": { "title": "Reddit Subreddit", "type": "string", "description": "Subreddit to fetch hot posts from. Popular choices: programming, python, javascript, rust, golang, webdev, datascience, machinelearning, devops", "default": "programming" }, "maxResults": { "title": "Max Results", "minimum": 1, "maximum": 100, "type": "integer", "description": "Maximum number of results to return per source (1-100). When using 'all', up to this many items are fetched from each source then combined and sorted.", "default": 15 }, "since": { "title": "Time Period", "enum": [ "24h", "7d", "30d" ], "type": "string", "description": "Time period filter applied to GitHub trending repositories. '24h' = last day, '7d' = last week, '30d' = last month.", "default": "24h" } } }, "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 } } } } } } } } } } ```