# Nasdaq Stock Screener Scraper (`automation-lab/nasdaq-stock-screener-scraper`) Actor πŸ“Š Screen Nasdaq's public US stock universe by exchange, sector, industry, country, ticker, company, and market cap. Export typed records to JSON, CSV, or Excel. - **URL**: https://apify.com/automation-lab/nasdaq-stock-screener-scraper.md - **Developed by:** [Stas Persiianenko](https://apify.com/automation-lab) (community) - **Categories:** Business - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per event This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. 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 ## Nasdaq Stock Screener Scraper Export Nasdaq's public US stock screener as clean, typed dataβ€”without an API key, browser, or manual spreadsheet work. **Nasdaq Stock Screener Scraper** downloads the current Nasdaq, NYSE, and AMEX stock universe, applies your filters, and saves normalized records to an Apify dataset. Use it for daily stock-universe refreshes, sector lists, company enrichment, quant research, market maps, and watchlist automation. - πŸ›οΈ Screen Nasdaq, NYSE, AMEX, or all three exchanges - πŸ”Ž Filter by ticker, company, sector, industry, country, and market cap - πŸ“Š Export price, change, volume, market cap, IPO year, and classification data - πŸ”— Keep canonical Nasdaq URLs and raw source values for traceability - ⚑ Run through the Console, API, schedules, webhooks, or Apify MCP ### What does Nasdaq Stock Screener Scraper do? The Actor calls Nasdaq's public stock-screener data surface and converts formatted market values into machine-friendly numbers. For every matching stock, it can return: - ticker symbol and company name; - listing exchange; - last sale price, net change, and percent change; - trading volume and market capitalization; - country, IPO year, sector, and industry; - canonical Nasdaq stock URL; - original formatted market values; - UTC collection timestamp. The Actor uses one exchange-specific request per selected exchange. That approach keeps exchange attribution accurate even though the raw stock rows do not contain an exchange field. ### Who is it for? #### Investors and analysts Refresh sector lists, compare company universes, and create repeatable screens without downloading CSV files by hand. #### Quant and data teams Feed a normalized US equity universe into notebooks, warehouses, factor pipelines, validation jobs, or instrument-master tables. #### Market researchers Build market maps by country, sector, industry, IPO year, volume, or capitalization. #### Lead and enrichment teams Turn public-company tickers into company lists with classification and source URLs for downstream enrichment. #### AI and automation builders Give agents a structured, bounded stock-screening tool through the Apify API or MCP server. ### Why use this Nasdaq stock scraper? - **No API key:** the useful source is publicly accessible. - **Source-specific:** records come from Nasdaq's own public screener surface. - **Typed numbers:** currency signs, commas, and percent signs are removed from normalized fields. - **Raw values retained:** audit the original source formatting when needed. - **Fail-closed filters:** records with unknown market cap do not pass numeric boundaries. - **Bounded runs:** `maxRecords` controls output volume and cost. - **Automation-ready:** schedule runs and connect datasets to webhooks, Zapier, Make, or cloud storage. ### What Nasdaq stock data can you extract? | Field | Type | Description | |---|---|---| | `symbol` | string | Stock ticker | | `companyName` | string | Nasdaq company/security name | | `exchange` | string | `nasdaq`, `nyse`, or `amex` | | `lastSale` | number | Normalized last sale price | | `netChange` | number | Net price change | | `percentChange` | number | Percentage price change | | `volume` | number | Reported trading volume | | `marketCap` | number | Market capitalization in USD | | `country` | string | Issuer country when supplied | | `ipoYear` | number | IPO year when supplied | | `sector` | string | Nasdaq sector classification | | `industry` | string | Nasdaq industry classification | | `url` | string | Canonical Nasdaq stock page | | `rawLastSale` | string | Original formatted price | | `rawPercentChange` | string | Original formatted percentage | | `collectedAt` | string | ISO 8601 UTC timestamp | Optional source fields are omitted when Nasdaq does not supply a useful value; the Actor does not invent data. ### How to scrape the Nasdaq stock screener 1. Open the Actor in Apify Console. 2. Choose one exchange or **All US exchanges**. 3. Add optional company, sector, industry, country, or market-cap filters. 4. Set a maximum number of stock records. 5. Click **Start**. 6. Open the Dataset tab to preview results. 7. Export JSON, CSV, Excel, XML, or RSS, or consume the dataset API. Start with 25 records to validate a workflow, then increase the limit for production refreshes. ### Input parameters | Input | Type | Default | Purpose | |---|---|---:|---| | `exchange` | string | `all` | Scan all exchanges, Nasdaq, NYSE, or AMEX | | `symbol` | string | β€” | Match one exact ticker | | `search` | string | β€” | Match ticker or company name text | | `sector` | string | β€” | Partial case-insensitive sector match | | `industry` | string | β€” | Partial case-insensitive industry match | | `country` | string | β€” | Partial case-insensitive country match | | `minMarketCap` | number | β€” | Inclusive minimum USD market cap | | `maxMarketCap` | number | β€” | Inclusive maximum USD market cap | | `maxRecords` | integer | `100` | Output cap from 1 to 10,000 | If both market-cap boundaries are present, the minimum must not exceed the maximum. ### Example input: Nasdaq technology stocks ```json { "exchange": "nasdaq", "sector": "Technology", "country": "United States", "minMarketCap": 1000000000, "maxRecords": 100 } ```` This screen returns up to 100 Nasdaq-listed US technology companies with a reported market cap of at least $1 billion. ### Example input: exact ticker lookup ```json { "exchange": "all", "symbol": "AAPL", "maxRecords": 1 } ``` Ticker matching is case-insensitive and exact. Use `search` instead when you want a partial company-name or ticker match. ### Example output ```json { "symbol": "A", "companyName": "Agilent Technologies Inc. Common Stock", "exchange": "nyse", "lastSale": 131.46, "netChange": -0.54, "percentChange": -0.41, "volume": 1337000, "marketCap": 37128503358, "country": "United States", "ipoYear": 1999, "sector": "Industrials", "industry": "Biotechnology: Laboratory Analytical Instruments", "url": "https://www.nasdaq.com/market-activity/stocks/a", "rawLastSale": "$131.46", "rawPercentChange": "-0.41%", "collectedAt": "2026-07-18T02:30:00.000Z" } ``` Values change with the source. The snippet demonstrates the output shape, not a price guarantee. ### How much does it cost to scrape Nasdaq stocks? This Actor uses pay-per-event pricing: a **$0.005 run start** plus one charge for every stock saved. | Apify tier | Price per stock | 1,000 stocks plus start | |---|---:|---:| | Free | $0.000036179 | about $0.0412 | | Starter / Bronze | $0.00003146 | about $0.0365 | | Scale / Silver | $0.000024539 | about $0.0295 | | Business / Gold | $0.000018876 | about $0.0239 | | Platinum | $0.000012584 | about $0.0176 | | Diamond | $0.00001 | about $0.0150 | A small 20-stock test costs about **$0.0057 on the Free tier**. `maxRecords` gives you direct control over the variable portion of the run cost. Because filtering happens before output, you pay the per-stock event only for records saved to your dataset. The formula-derived price was validated against an 83-record, three-exchange cloud run with an 89.7% net margin. ### Filtering behavior Text filters use case-insensitive partial matching except `symbol`, which is exact. For example: - `sector: "tech"` can match `Technology`; - `industry: "semi"` can match a semiconductor industry label; - `country: "united"` can match `United States`; - `search: "micro"` checks both ticker and company name. Market-cap filters are inclusive. If a source row has no parseable market cap while a market-cap filter is active, that row is excluded rather than guessed. ### Data freshness and coverage The Actor captures the public screener response available when the run executes. `collectedAt` records the collection time for every row. Coverage includes securities returned by Nasdaq's public screener for: - Nasdaq; - New York Stock Exchange (NYSE); - American Stock Exchange (AMEX). The response may include security names such as common stock, preferred stock, warrants, units, or depositary shares. Use ticker/company text and downstream rules if your workflow needs only one security type. ### Tips for reliable stock screens - 🎯 Use an exact `symbol` for deterministic ticker lookup. - πŸ§ͺ Start with `maxRecords: 25` before scheduling a larger universe refresh. - πŸ’° Enter market caps as plain USD numbers, not `$10B` strings. - 🧭 Keep `exchange: "all"` when you do not know where a ticker is listed. - πŸ” Use short industry phrases because source labels can be detailed. - πŸ• Store `collectedAt` when comparing snapshots across scheduled runs. - 🧱 Deduplicate downstream snapshots by `symbol` plus `collectedAt` or run ID. ### Integrations and workflow patterns #### Google Sheets or Excel watchlists Schedule a daily run, export CSV or XLSX, and refresh a shared equity watchlist. #### Data warehouse instrument master Send completed-run webhooks to a loader, then upsert records by `symbol` and `exchange`. #### Quant research notebooks Call the Actor before a notebook job and read the dataset as JSON for universe selection. #### CRM and company enrichment Use company names, countries, sectors, and Nasdaq URLs as seed attributes for public-company enrichment. #### Slack or email alerts Compare today's dataset with yesterday's snapshot and notify a channel when companies enter or leave a selected market-cap or sector screen. ### API usage with Node.js ```javascript import { ApifyClient } from 'apify-client'; const client = new ApifyClient({ token: process.env.APIFY_TOKEN }); const run = await client.actor('automation-lab/nasdaq-stock-screener-scraper').call({ exchange: 'nasdaq', sector: 'Technology', minMarketCap: 1_000_000_000, maxRecords: 100, }); const { items } = await client.dataset(run.defaultDatasetId).listItems(); console.log(items); ``` ### API usage with Python ```python import os from apify_client import ApifyClient client = ApifyClient(os.environ['APIFY_TOKEN']) run = client.actor('automation-lab/nasdaq-stock-screener-scraper').call(run_input={ 'exchange': 'nyse', 'sector': 'Health Care', 'maxRecords': 100, }) items = client.dataset(run['defaultDatasetId']).list_items().items print(items) ``` ### API usage with cURL ```bash curl -X POST \ "https://api.apify.com/v2/acts/automation-lab~nasdaq-stock-screener-scraper/runs?token=$APIFY_TOKEN" \ -H "Content-Type: application/json" \ -d '{"exchange":"all","search":"apple","maxRecords":10}' ``` Use the returned `defaultDatasetId` with the dataset items endpoint after the run finishes. ### Use Nasdaq Stock Screener Scraper with MCP Connect the Actor to Claude Code: ```bash claude mcp add --transport http apify "https://mcp.apify.com?tools=automation-lab/nasdaq-stock-screener-scraper" ``` For Claude Desktop, Cursor, or VS Code, add this MCP configuration: ```json { "mcpServers": { "apify": { "url": "https://mcp.apify.com?tools=automation-lab/nasdaq-stock-screener-scraper" } } } ``` Example prompts: - "Screen Nasdaq technology companies above $5 billion market cap and return 50 records." - "Look up the current Nasdaq screener row for AAPL." - "Create a NYSE healthcare stock dataset for my research notebook." ### Scheduling and change monitoring Apify schedules can run the same input hourly, daily, weekly, or on a custom cron expression. A practical monitor workflow is: 1. schedule a filtered screen; 2. retain each run's dataset ID; 3. compare symbols with the previous successful run; 4. calculate added, removed, or changed records; 5. send a webhook to your alerting or ETL system. The Actor returns current snapshots; it does not itself calculate historical differences. ### Limitations - Nasdaq controls source availability, field coverage, classifications, and refresh timing. - This Actor does not provide historical OHLC candles, financial statements, ratios, options, dividends, or investment advice. - Some numeric fields can be absent or represented as `--`; normalized fields are then omitted. - Security names may represent share classes, warrants, units, or depositary securities. - The public screener is a market-discovery source, not an exchange-certified reference feed. - A valid filter combination can naturally return zero records. ### Is it legal to scrape Nasdaq stock screener data? The Actor accesses publicly available stock-screener data without bypassing login or access controls. Public market facts are generally not personal data, but source terms, database rights, redistribution rules, and financial-services regulations can vary by country and use case. You are responsible for ensuring that your collection, storage, publication, and downstream use comply with applicable laws and Nasdaq terms. Do not present delayed or scraped data as an official real-time exchange feed, and do not use the Actor as a substitute for licensed data where your product or regulation requires one. ### Troubleshooting #### Why did my run return no stocks? Your filters may not overlap. Remove the market-cap boundary first, then broaden sector, industry, or country text. Check that an exact `symbol` does not conflict with another filter. #### Why is a numeric field missing? Nasdaq sometimes supplies blank text or `--`. The Actor omits the normalized number instead of returning zero, because zero would be misleading. Check the raw-value dataset view for source formatting. #### Why did the run fail after retries? Nasdaq may be temporarily unavailable or throttling requests. Inspect the log for the HTTP status or response-shape error, then retry later. The Actor uses conservative bounded retries and does not hide total extraction failures. #### Why do I see fewer records than `maxRecords`? `maxRecords` is a cap, not a target. The source and filters determine the number of qualifying stocks. ### Related Automation Lab actors - [TradingView Stock Screener Scraper](https://apify.com/automation-lab/tradingview-scraper) β€” screen stocks, crypto, and forex across multiple markets. - [TradingView Earnings Calendar Scraper](https://apify.com/automation-lab/tradingview-earnings-calendar-scraper) β€” collect upcoming and historical earnings events. - [TradingView Economic Calendar Scraper](https://apify.com/automation-lab/tradingview-economic-calendar-scraper) β€” extract macroeconomic calendar releases. - [Finviz Quote Scraper](https://apify.com/automation-lab/finviz-quote-scraper) β€” enrich individual stock tickers with Finviz quote data. - [Finviz News Scraper](https://apify.com/automation-lab/finviz-news-scraper) β€” collect ticker-related market news. Choose this Actor when you need Nasdaq's public US stock universe and classification fields. Choose TradingView for cross-market screening or Finviz actors for source-specific quote and news enrichment. ### FAQ #### Does it need a Nasdaq account or API key? No. The current implementation uses Nasdaq's anonymous public screener JSON response. #### Does it use a browser or proxy? No. Version 0.1 uses lightweight direct HTTP requests with browser-like headers. This keeps runs fast and compute-efficient. #### Can I export every US stock? Yes. Set `exchange` to `all` and raise `maxRecords` up to 10,000. The current public source contains several thousand rows, and the exact count changes over time. #### Can I filter several sectors in one run? The v0.1 input accepts one partial sector phrase. Run separate inputs for unrelated sectors, or export a broad universe and filter multiple values downstream. #### Are prices real time? The Actor returns whatever the public Nasdaq screener provides at run time. Do not assume an exchange-certified real-time entitlement; inspect Nasdaq's data notices for your use case. #### How are duplicates handled? When all exchanges are scanned, the Actor keeps the first saved record for each symbol. It does not emit duplicate ticker symbols in one run. #### Can I use the data in an AI agent? Yes. Use the Apify API or MCP integration and keep `maxRecords` bounded so the agent receives a manageable dataset. #### Does the Actor make investment recommendations? No. It extracts public screener records and applies mechanical filters. Any analysis, trading decision, or recommendation remains your responsibility. # Actor input Schema ## `exchange` (type: `string`): Choose the US listing exchange to scan, or scan Nasdaq, NYSE, and AMEX together. ## `symbol` (type: `string`): Return one exact ticker symbol, for example AAPL. Matching is case-insensitive. ## `search` (type: `string`): Keep stocks whose ticker or company name contains this text. ## `sector` (type: `string`): Filter by Nasdaq sector text, for example Technology, Health Care, or Industrials. ## `industry` (type: `string`): Filter by an industry name or partial phrase, for example Semiconductors or Biotechnology. ## `country` (type: `string`): Filter by the issuer country shown by Nasdaq, for example United States or Canada. ## `minMarketCap` (type: `number`): Keep stocks at or above this numeric market capitalization. Records without a parseable value are excluded. ## `maxMarketCap` (type: `number`): Keep stocks at or below this numeric market capitalization. Records without a parseable value are excluded. ## `maxRecords` (type: `integer`): Stop after saving this many matching stocks. Use a small value for quick tests. ## Actor input object example ```json { "exchange": "all", "maxRecords": 20 } ``` # Actor output Schema ## `stocks` (type: `string`): No description ## `rawValues` (type: `string`): No description # 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 = { "exchange": "all", "maxRecords": 20 }; // Run the Actor and wait for it to finish const run = await client.actor("automation-lab/nasdaq-stock-screener-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`πŸ’Ύ 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); }); // πŸ“š Want to learn more πŸ“–? Go to β†’ 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 = { "exchange": "all", "maxRecords": 20, } # Run the Actor and wait for it to finish run = client.actor("automation-lab/nasdaq-stock-screener-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("πŸ’Ύ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # πŸ“š Want to learn more πŸ“–? Go to β†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "exchange": "all", "maxRecords": 20 }' | apify call automation-lab/nasdaq-stock-screener-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=automation-lab/nasdaq-stock-screener-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Nasdaq Stock Screener Scraper", "description": "πŸ“Š Screen Nasdaq's public US stock universe by exchange, sector, industry, country, ticker, company, and market cap. Export typed records to JSON, CSV, or Excel.", "version": "0.1", "x-build-id": "0H4qKg29aPkfXIa3J" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/automation-lab~nasdaq-stock-screener-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-automation-lab-nasdaq-stock-screener-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/automation-lab~nasdaq-stock-screener-scraper/runs": { "post": { "operationId": "runs-sync-automation-lab-nasdaq-stock-screener-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/automation-lab~nasdaq-stock-screener-scraper/run-sync": { "post": { "operationId": "run-sync-automation-lab-nasdaq-stock-screener-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "exchange": { "title": "πŸ›οΈ Exchange", "enum": [ "all", "nasdaq", "nyse", "amex" ], "type": "string", "description": "Choose the US listing exchange to scan, or scan Nasdaq, NYSE, and AMEX together.", "default": "all" }, "symbol": { "title": "Ticker symbol", "type": "string", "description": "Return one exact ticker symbol, for example AAPL. Matching is case-insensitive." }, "search": { "title": "Symbol or company search", "type": "string", "description": "Keep stocks whose ticker or company name contains this text." }, "sector": { "title": "Sector contains", "type": "string", "description": "Filter by Nasdaq sector text, for example Technology, Health Care, or Industrials." }, "industry": { "title": "Industry contains", "type": "string", "description": "Filter by an industry name or partial phrase, for example Semiconductors or Biotechnology." }, "country": { "title": "Country contains", "type": "string", "description": "Filter by the issuer country shown by Nasdaq, for example United States or Canada." }, "minMarketCap": { "title": "Minimum market cap (USD)", "minimum": 0, "type": "number", "description": "Keep stocks at or above this numeric market capitalization. Records without a parseable value are excluded." }, "maxMarketCap": { "title": "Maximum market cap (USD)", "minimum": 0, "type": "number", "description": "Keep stocks at or below this numeric market capitalization. Records without a parseable value are excluded." }, "maxRecords": { "title": "Maximum stock records", "minimum": 1, "maximum": 10000, "type": "integer", "description": "Stop after saving this many matching stocks. Use a small value for quick tests.", "default": 100 } } }, "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 } } } } } } } } } } ```