# 📈 Stock Market Scraper — Real-Time Prices & Trends (`nexgendata/stock-market-scraper`) Actor Scrape real-time stock prices, market trends, company financials, analyst recommendations, and historical data. Supports any ticker symbol. Perfect for portfolio tracking, market research, and trading analysis. - **URL**: https://apify.com/nexgendata/stock-market-scraper.md - **Developed by:** [Stephan Corbeil](https://apify.com/nexgendata) (community) - **Categories:** AI, Automation - **Stats:** 2 total users, 1 monthly users, 0.0% 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 ### What does Stock Market Scraper do? Stock Market Scraper extracts financial data from Yahoo Finance including stock prices, market trends, company financials, analyst recommendations, historical data, and key statistics for any publicly traded company. ### Why use Stock Market Scraper? Manually tracking financial data across hundreds of stocks is impractical. This scraper delivers structured financial data on demand, making it easy to build financial models, track portfolios, or power investment research workflows. ### Use cases - **Investment Research**: Analyze P/E ratios, revenue growth, and financial metrics across companies - **Portfolio Monitoring**: Track stock prices and key metrics for your investment portfolio - **Financial Modeling**: Feed real-time financial data into spreadsheets and models - **Market Screening**: Screen stocks by financial criteria like market cap, P/E ratio, or dividend yield - **Academic Research**: Collect historical stock data for financial analysis and backtesting ### Input parameters | Parameter | Type | Description | |-----------|------|-------------| | `tickers` | Array | Stock ticker symbols (e.g., ["AAPL", "GOOGL", "MSFT"]) | | `maxResults` | Number | Maximum results per ticker (default: 1) | ### Output example ```json { "ticker": "AAPL", "name": "Apple Inc.", "price": 178.72, "change": 2.34, "changePercent": 1.32, "marketCap": "2.78T", "peRatio": 28.5, "dividendYield": "0.55%", "52WeekHigh": 199.62, "52WeekLow": 124.17 } ```` ### Pricing Pay-Per-Event pricing: $1.00 per 1,000 results. Platform fee: $0.005 per start. *** ### 💻 Code Example — Python ```python from apify_client import ApifyClient client = ApifyClient("YOUR_APIFY_TOKEN") run = client.actor("nexgendata/stock-market-scraper").call(run_input={ ## Fill in the input shape from the actor's input_schema }) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) ``` ### 🌐 Code Example — cURL ```bash curl -X POST "https://api.apify.com/v2/acts/nexgendata~stock-market-scraper/run-sync-get-dataset-items?token=YOUR_TOKEN" \ -H "Content-Type: application/json" \ -d '{ /* input schema */ }' ``` ### ❓ FAQ **Q: How do I get started?** Sign up at [apify.com](https://www.apify.com/?fpr=2ayu9b), grab your API token from Settings → Integrations, and run the actor via the Apify console, API, Python SDK, or any integration (Zapier, Make.com, n8n). **Q: What's the typical cost per run?** See the pricing section below. Most runs finish under $0.10 for typical batches. **Q: Is this actor maintained?** Yes. NexGenData maintains 140+ Apify actors and ships updates regularly. Bug reports via the Apify console issues tab get responses within 24 hours. **Q: Can I use the output commercially?** Yes — you own the output data. Check the target site's Terms of Service for any usage restrictions on the scraped content itself. **Q: How do I handle rate limits?** Apify manages concurrency and retries automatically. For very large batches (10K+ items), run multiple smaller jobs in parallel instead of one mega-job for better reliability. ### 💰 Pricing Pay-per-event pricing — you only pay for what you actually extract. - **Actor Start:** $0.0001 - **result:** $0.0050 ### 🔗 Related NexGenData Actors - [RAG Web Browser](https://apify.com/nexgendata/rag-web-browser?fpr=2ayu9b) - [AI Web Scraper](https://apify.com/nexgendata/ai-web-scraper?fpr=2ayu9b) - [Hacker News Scraper](https://apify.com/nexgendata/hacker-news-scraper?fpr=2ayu9b) ### 🚀 Apify Affiliate Program New to Apify? Sign up with our [referral link](https://www.apify.com/?fpr=2ayu9b) — you get free platform credits on signup, and you help fund the maintenance of this actor fleet. *** *Built and maintained by [NexGenData](https://apify.com/nexgendata?fpr=2ayu9b) — 140+ actors covering scraping, enrichment, MCP servers, and automation.* # Actor input Schema ## `tickers` (type: `array`): List of stock ticker symbols (e.g., AAPL, GOOGL, MSFT) ## Actor input object example ```json { "tickers": [ "AAPL", "GOOGL" ] } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "tickers": [ "AAPL", "GOOGL" ] }; // Run the Actor and wait for it to finish const run = await client.actor("nexgendata/stock-market-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${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 = { "tickers": [ "AAPL", "GOOGL", ] } # Run the Actor and wait for it to finish run = client.actor("nexgendata/stock-market-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 '{ "tickers": [ "AAPL", "GOOGL" ] }' | apify call nexgendata/stock-market-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=nexgendata/stock-market-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "📈 Stock Market Scraper — Real-Time Prices & Trends", "description": "Scrape real-time stock prices, market trends, company financials, analyst recommendations, and historical data. Supports any ticker symbol. Perfect for portfolio tracking, market research, and trading analysis.", "version": "0.0", "x-build-id": "5OXxy8WgyyPMeOLH9" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/nexgendata~stock-market-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-nexgendata-stock-market-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/nexgendata~stock-market-scraper/runs": { "post": { "operationId": "runs-sync-nexgendata-stock-market-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/nexgendata~stock-market-scraper/run-sync": { "post": { "operationId": "run-sync-nexgendata-stock-market-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "required": [ "tickers" ], "properties": { "tickers": { "title": "Stock Tickers", "type": "array", "description": "List of stock ticker symbols (e.g., AAPL, GOOGL, MSFT)", "items": { "type": "string" } } } }, "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 } } } } } } } } } } ```