# Stock Market Scraper (`moving_beacon-owner1/my-actor-78`) Actor Scrape stock market data — the world's most popular free financial data source. Extract real-time prices, company profiles, financial statements, dividends, analyst ratings, institutional holders, and options chains for any publicly traded stock, ETF, index, or cryptocurrency - **URL**: https://apify.com/moving\_beacon-owner1/my-actor-78.md - **Developed by:** [Jamshaid Arif](https://apify.com/moving_beacon-owner1) (community) - **Categories:** Developer tools, Automation, Other - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $10.00 / 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.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 ## 📈 Stock Market Scraper **Scrape stock market data — the world's most popular free financial data source. Extract real-time prices, company profiles, financial statements, dividends, analyst ratings, institutional holders, and options chains for any publicly traded stock, ETF, index, or cryptocurrency. No API key needed. No login required. --- ### What does this actor do? This actor fetches comprehensive financial data for any ticker symbol available. It uses the `yfinance` Python library to access Yahoo's publicly available market data APIs. **Use it to:** - Track stock prices and build historical price databases - Monitor company valuations (P/E, market cap, EV/EBITDA) - Download quarterly and annual financial statements - Track dividend history for income investing research - Aggregate analyst price targets and buy/sell recommendations - Identify institutional and insider ownership changes - Fetch options chain data for derivatives research - Compare multiple stocks side-by-side --- ### Supported ticker types | Type | Example tickers | |------|----------------| | **US Stocks** | `AAPL`, `MSFT`, `GOOGL`, `TSLA`, `AMZN`, `META`, `NVDA` | | **International Stocks** | `BABA` (Alibaba), `TM` (Toyota), `SAP` (SAP SE) | | **ETFs** | `SPY`, `QQQ`, `VTI`, `ARKK`, `VOO` | | **Indices** | `^GSPC` (S&P 500), `^DJI` (Dow Jones), `^IXIC` (NASDAQ) | | **Crypto** | `BTC-USD`, `ETH-USD`, `SOL-USD`, `DOGE-USD` | | **Forex** | `EURUSD=X`, `GBPUSD=X`, `JPY=X` | | **Futures** | `GC=F` (Gold), `CL=F` (Crude Oil), `SI=F` (Silver) | --- ### How to use #### Step 1: Enter ticker symbols Type one or more ticker symbols, separated by commas: ```` AAPL, MSFT, GOOGL, TSLA, AMZN ```` #### Step 2: Select data modules Choose which data you want to scrape. You can select multiple: | Module | What you get | |--------|-------------| | **Company Info** | Name, sector, price, market cap, P/E, margins, beta, 52-week range, and 40+ metrics | | **Price History** | OHLCV candles (open, high, low, close, volume) for any period and interval | | **Financial Statements** | Income statement, balance sheet, and cash flow — annual or quarterly | | **Dividends & Splits** | Full dividend payment history and stock split history | | **Analyst Price Targets** | Consensus low, mean, median, and high price targets | | **Recommendations** | Analyst buy/hold/sell/strong buy ratings over time | | **Institutional Holders** | Top institutional investors and insider transactions | | **Options Chain** | Call and put options with strike, bid, ask, volume, open interest | #### Step 3: Run and export Click **Start**, wait for results, and export as JSON, CSV, or Excel. --- ### Input parameters #### Core settings | Field | Type | Default | Description | |-------|------|---------|-------------| | `tickers` | Text | `AAPL, MSFT, GOOGL, TSLA, AMZN` | Comma-separated ticker symbols | | `data_modules` | Multi-select | `company_info`, `price_history` | Which data to scrape (see table above) | #### Price history settings | Field | Type | Default | Description | |-------|------|---------|-------------| | `history_period` | Select | `1mo` | Time range: `1d`, `5d`, `1mo`, `3mo`, `6mo`, `1y`, `2y`, `5y`, `10y`, `ytd`, `max` | | `history_interval` | Select | `1d` | Candle size: `1m`, `5m`, `15m`, `30m`, `1h`, `1d`, `1wk`, `1mo` | > **Note:** Intraday intervals (1m–90m) only work for the last 60 days. 1-minute data is limited to the last 7 days. #### Financials settings | Field | Type | Default | Description | |-------|------|---------|-------------| | `financials_type` | Select | `annual` | `annual` or `quarterly` financial statements | #### Options settings | Field | Type | Default | Description | |-------|------|---------|-------------| | `options_expiry` | Select | `nearest` | `nearest` = closest expiry only, `all` = all available dates (up to 5) | --- ### Input examples #### Example 1: Quick stock comparison — FAANG companies ```json { "tickers": "AAPL, AMZN, GOOGL, META, NFLX", "data_modules": ["company_info"], } ```` #### Example 2: Full analysis of a single stock ```json { "tickers": "NVDA", "data_modules": [ "company_info", "price_history", "financials", "dividends", "analyst_targets", "recommendations", "holders" ], "history_period": "1y", "history_interval": "1d", "financials_type": "quarterly" } ``` #### Example 3: Crypto price history ```json { "tickers": "BTC-USD, ETH-USD, SOL-USD", "data_modules": ["company_info", "price_history"], "history_period": "3mo", "history_interval": "1d" } ``` #### Example 4: Dividend research for income stocks ```json { "tickers": "JNJ, PG, KO, PEP, MCD, T, VZ", "data_modules": ["company_info", "dividends"] } ``` #### Example 5: Options data for a volatile stock ```json { "tickers": "TSLA", "data_modules": ["company_info", "options"], "options_expiry": "all" } ``` #### Example 6: Intraday 5-minute candles (last 5 days) ```json { "tickers": "SPY", "data_modules": ["price_history"], "history_period": "5d", "history_interval": "5m" } ``` *** ### Output format Each record in the dataset has a `type` field indicating the data module. One ticker with multiple modules produces multiple records. #### Company Info record ```json { "type": "company_info", "ticker": "AAPL", "name": "Apple Inc.", "sector": "Technology", "industry": "Consumer Electronics", "country": "United States", "website": "https://www.apple.com", "employees": 161000, "description": "Apple Inc. designs, manufactures, and markets smartphones...", "price": 228.50, "currency": "USD", "previous_close": 227.10, "change": 1.40, "change_pct": "+0.62%", "day_high": 230.00, "day_low": 226.80, "52w_high": 260.10, "52w_low": 164.08, "volume": 54123456, "market_cap": 3510000000000, "market_cap_fmt": "$3.51T", "pe_ratio": 37.2, "forward_pe": 31.5, "price_to_book": 62.4, "dividend_yield": 0.0044, "beta": 1.24, "profit_margin": 0.267, "return_on_equity": 1.572, "debt_to_equity": 151.86, "free_cash_flow": 111500000000, "scraped_at": "2026-04-05T12:00:00+00:00" } ``` #### Price History record ```json { "type": "price_history", "ticker": "AAPL", "period": "1mo", "interval": "1d", "candles": 22, "stats": { "period_high": 230.50, "period_low": 210.30, "period_open": 215.00, "period_close": 228.50, "period_change": 6.28, "total_volume": 1234567890 }, "data": [ { "Date": "2026-03-05T00:00:00", "Open": 215.00, "High": 217.30, "Low": 214.50, "Close": 216.80, "Volume": 58123456 } ] } ``` #### Financial Statements record ```json { "type": "financials", "ticker": "AAPL", "frequency": "annual", "income_statement": [ { "Date": "2025-09-30", "Total Revenue": 400000000000, "...": "..." } ], "balance_sheet": [ { "Date": "2025-09-30", "Total Assets": 350000000000, "...": "..." } ], "cash_flow": [ { "Date": "2025-09-30", "Free Cash Flow": 111500000000, "...": "..." } ] } ``` #### Analyst Price Targets record ```json { "type": "analyst_targets", "ticker": "AAPL", "data": { "current": 228.50, "low": 180.00, "high": 300.00, "mean": 248.75, "median": 250.00 } } ``` #### Options Chain record ```json { "type": "options", "ticker": "TSLA", "available_expiries": ["2026-04-11", "2026-04-18", "2026-04-25"], "fetched_expiries": 1, "chains": [ { "expiry_date": "2026-04-11", "calls_count": 45, "puts_count": 45, "calls": [ { "strike": 250.0, "lastPrice": 12.50, "bid": 12.30, "ask": 12.70, "volume": 5432, "openInterest": 12345 } ], "puts": [ { "strike": 250.0, "lastPrice": 8.20, "bid": 8.00, "ask": 8.40, "volume": 3210, "openInterest": 9876 } ] } ] } ``` *** ### What each metric means #### Valuation metrics | Metric | What it tells you | |--------|------------------| | `pe_ratio` | Price-to-Earnings — how much investors pay per dollar of earnings | | `forward_pe` | P/E based on estimated future earnings | | `peg_ratio` | P/E adjusted for growth — under 1.0 may suggest undervaluation | | `price_to_book` | Price vs. book value — common in bank/financial analysis | | `ev_to_ebitda` | Enterprise Value to EBITDA — industry-standard valuation metric | | `market_cap` | Total market value of outstanding shares | #### Profitability metrics | Metric | What it tells you | |--------|------------------| | `profit_margin` | Net income as a % of revenue | | `operating_margin` | Operating income as a % of revenue | | `return_on_equity` | How efficiently the company uses shareholder equity | | `return_on_assets` | How efficiently the company uses its total assets | #### Risk metrics | Metric | What it tells you | |--------|------------------| | `beta` | Stock volatility relative to the market (1.0 = same as market) | | `debt_to_equity` | Total debt divided by shareholder equity | | `current_ratio` | Ability to pay short-term obligations (above 1.0 is healthy) | | `short_ratio` | Days to cover all short positions — high values may signal short squeeze risk | *** ### How much does it cost to run? This actor is lightweight — it fetches data via API calls, no browser rendering needed. | Tickers | Modules | Estimated time | Apify credits | |---------|---------|---------------|---------------| | 5 tickers | Company Info only | ~15 seconds | < $0.01 | | 5 tickers | All 8 modules | ~2 minutes | ~$0.01 | | 20 tickers | Info + History | ~1 minute | ~$0.01 | | 50 tickers | Info + Financials | ~5 minutes | ~$0.02 | | 100 tickers | Company Info only | ~3 minutes | ~$0.02 | *** ### Scheduling and integrations #### Daily price tracking Set up a **scheduled run** in Apify Console to scrape prices every trading day. Combine with Google Sheets to build an auto-updating stock tracker. **Example schedule:** Every weekday at 4:30 PM ET (after market close): ```json { "tickers": "AAPL, MSFT, GOOGL, TSLA, AMZN, NVDA, META", "data_modules": ["company_info"], } ``` #### Weekly portfolio analysis Schedule a weekend run with full financials: ```json { "tickers": "VTI, BND, VXUS, VNQ", "data_modules": ["company_info", "price_history", "dividends"], "history_period": "1mo" } ``` #### Connect via API (Python) ```python from apify_client import ApifyClient client = ApifyClient("YOUR_API_TOKEN") run = client.actor("your-username/yahoo-finance-scraper").call(run_input={ "tickers": "AAPL, MSFT, GOOGL", "data_modules": ["company_info", "price_history"], "history_period": "3mo", }) dataset = client.dataset(run["defaultDatasetId"]) items = dataset.list_items().items ## Filter for company info records companies = [i for i in items if i.get("type") == "company_info"] for c in companies: print(f"{c['ticker']}: ${c['price']} | {c['market_cap_fmt']} | P/E: {c['pe_ratio']}") ``` #### Available export formats After each run, download your data from the dataset tab: - **JSON** — Best for programmatic use and integrations - **CSV** — Best for spreadsheets and quick analysis - **Excel (.xlsx)** — Best for sharing with non-technical stakeholders - **Google Sheets** — Auto-sync with the Apify integration *** ### Tips and best practices - **Start with `company_info` only** to verify your tickers work, then add more modules. - **Use `price_history` with `1d` interval** for most analysis. Intraday data (1m, 5m) is only available for the last 7–60 days. - **Quarterly financials** give more recent data; annual gives a cleaner trend view. - **Crypto tickers** use the format `BTC-USD`, `ETH-USD` — you'll get price history but not financials. - **Index tickers** start with `^` (e.g., `^GSPC` for S\&P 500) — limited to price data only. - **Options data** can be large — use `nearest` expiry unless you need the full chain. - **If a module returns an error** for a ticker, the actor continues with the next module/ticker. Check the `error` field in the output. ### Disclaimer This actor is for **educational and research purposes only**. It is not financial advice. Always do your own research before making investment decisions. *** ### Changelog #### v1.0.0 (2026-04-05) - Initial release - 8 data modules: company info, price history, financials, dividends, analyst targets, recommendations, holders, options - Support for stocks, ETFs, indices, crypto, forex, and futures - Batch processing for multiple tickers - Clean JSON output with formatted market cap, change %, and NaN handling - Period stats computed for price history (high, low, change %) # Actor input Schema ## `tickers` (type: `string`): Comma-separated stock ticker symbols. Examples: AAPL, MSFT, GOOGL, TSLA, AMZN, BTC-USD, ETH-USD, ^GSPC (S\&P 500), ^DJI (Dow Jones), SPY (ETF). ## `data_modules` (type: `array`): Select which data modules to include for each ticker. ## `history_period` (type: `string`): Time period for price history. Only used if 'Price History' is selected. ## `history_interval` (type: `string`): Candle interval. Intraday intervals (1m–90m) only available for last 60 days. 1m data only for last 7 days. ## `financials_type` (type: `string`): Annual or quarterly financials. Only used if 'Financial Statements' is selected. ## `options_expiry` (type: `string`): Which options expiry date to scrape. 'nearest' = closest expiry, 'all' = all available expiry dates. Only used if 'Options Chain' is selected. ## `proxy_configuration` (type: `object`): Proxy settings. Yahoo Finance may rate-limit heavy usage. ## Actor input object example ```json { "tickers": "AAPL, MSFT, GOOGL, TSLA, AMZN", "data_modules": [ "company_info", "price_history" ], "history_period": "1mo", "history_interval": "1d", "financials_type": "annual", "options_expiry": "nearest" } ``` # 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, MSFT, GOOGL, TSLA, AMZN", "data_modules": [ "company_info", "price_history" ] }; // Run the Actor and wait for it to finish const run = await client.actor("moving_beacon-owner1/my-actor-78").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, MSFT, GOOGL, TSLA, AMZN", "data_modules": [ "company_info", "price_history", ], } # Run the Actor and wait for it to finish run = client.actor("moving_beacon-owner1/my-actor-78").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, MSFT, GOOGL, TSLA, AMZN", "data_modules": [ "company_info", "price_history" ] }' | apify call moving_beacon-owner1/my-actor-78 --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=moving_beacon-owner1/my-actor-78", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Stock Market Scraper", "description": "Scrape stock market data — the world's most popular free financial data source. Extract real-time prices, company profiles, financial statements, dividends, analyst ratings, institutional holders, and options chains for any publicly traded stock, ETF, index, or cryptocurrency", "version": "0.0", "x-build-id": "dMjOfFCn7mgVkWTff" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/moving_beacon-owner1~my-actor-78/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-moving_beacon-owner1-my-actor-78", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/moving_beacon-owner1~my-actor-78/runs": { "post": { "operationId": "runs-sync-moving_beacon-owner1-my-actor-78", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/moving_beacon-owner1~my-actor-78/run-sync": { "post": { "operationId": "run-sync-moving_beacon-owner1-my-actor-78", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": "Ticker Symbols", "type": "string", "description": "Comma-separated stock ticker symbols. Examples: AAPL, MSFT, GOOGL, TSLA, AMZN, BTC-USD, ETH-USD, ^GSPC (S&P 500), ^DJI (Dow Jones), SPY (ETF).", "default": "AAPL, MSFT, GOOGL, TSLA, AMZN" }, "data_modules": { "title": "Data to Scrape", "type": "array", "description": "Select which data modules to include for each ticker.", "items": { "type": "string", "enum": [ "company_info", "price_history", "financials", "dividends", "analyst_targets", "recommendations", "holders", "options" ], "enumTitles": [ "Company Info (sector, market cap, P/E, beta, etc.)", "Price History (OHLCV candles)", "Financial Statements (income, balance sheet, cash flow)", "Dividends & Splits History", "Analyst Price Targets", "Analyst Recommendations", "Institutional & Insider Holders", "Options Chain (calls & puts)" ] }, "default": [ "company_info", "price_history" ] }, "history_period": { "title": "Price History Period", "enum": [ "1d", "5d", "1mo", "3mo", "6mo", "1y", "2y", "5y", "10y", "ytd", "max" ], "type": "string", "description": "Time period for price history. Only used if 'Price History' is selected.", "default": "1mo" }, "history_interval": { "title": "Price History Interval", "enum": [ "1m", "5m", "15m", "30m", "1h", "1d", "1wk", "1mo" ], "type": "string", "description": "Candle interval. Intraday intervals (1m–90m) only available for last 60 days. 1m data only for last 7 days.", "default": "1d" }, "financials_type": { "title": "Financial Statements Type", "enum": [ "annual", "quarterly" ], "type": "string", "description": "Annual or quarterly financials. Only used if 'Financial Statements' is selected.", "default": "annual" }, "options_expiry": { "title": "Options Expiry", "enum": [ "nearest", "all" ], "type": "string", "description": "Which options expiry date to scrape. 'nearest' = closest expiry, 'all' = all available expiry dates. Only used if 'Options Chain' is selected.", "default": "nearest" }, "proxy_configuration": { "title": "Proxy Configuration", "type": "object", "description": "Proxy settings. Yahoo Finance may rate-limit heavy usage." } } }, "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 } } } } } } } } } } ```