# Hacker News Scraper — Stories, Jobs, Comments & Users API (`bovi/hacker-news-scraper`) Actor Scrape Hacker News stories, comments, jobs, and user profiles via the official Firebase and Algolia APIs. No proxy, no auth. Supports top/new/best/ask/show/job feeds, full-text search, comment trees, and user data. Pay per result. - **URL**: https://apify.com/bovi/hacker-news-scraper.md - **Developed by:** [Vitalii Bondarev](https://apify.com/bovi) (community) - **Categories:** Developer tools, MCP servers, AI - **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.18 / 1,000 hacker news items 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.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 ## Hacker News Scraper — Stories, Jobs & Comments API | from $1/1K No Login Used by developer-tooling teams, content intelligence platforms, and AI agents monitoring tech discourse. Scrape Hacker News stories, comments, jobs, and user profiles via the **official Firebase API** and **Algolia HN Search API**. No login required. No proxy needed. Zero-auth Firebase and Algolia APIs. Pay per result. ### Features - **6 live feeds** — Top, New, Best, Ask HN, Show HN, Job stories (via Firebase) - **Full-text search** — Algolia HN Search with relevance or date sort - **Comments** — fetch top-level comment threads with `parent_id` for threading - **User profiles** — karma, created date, bio, submission count - **Direct item fetch** — supply any HN item IDs - **`parse_confidence`** — machine-readable quality score in every record - **Flat schema** — 17 fields, ready for CSV/JSON/BigQuery ### Why this beats the alternatives | Actor | Price | API | Comments | Users | parse_confidence | Proxy needed | |---|---|---|---|---|---|---| | **This actor** | **$1.00/1k** | Firebase + Algolia | ✓ | ✓ | ✓ | No | | epctex/hackernews-scraper | $10/mo rental | HTML scraping | ✓ | — | No | Required | | harvestlab/hacker-news-scraper | $1.00/1k | Firebase + Algolia | — | ✓ | No | No | | automation-lab/hackernews-scraper | $1.00/1k | HTML scraping | — | — | No | No | | andok/hackernews-scraper | ? | Firebase | — | — | No | No | **Our edge**: only actor combining Firebase feeds + Algolia search + comments + user profiles + `parse_confidence`, all via official APIs. No proxy required — HN Firebase is public, zero-auth, and extremely stable. ### Modes | Mode | API | Returns | |---|---|---| | `topStories` | Firebase | Front-page top 500 stories | | `newStories` | Firebase | Newest 500 stories | | `bestStories` | Firebase | All-time best 200 stories | | `askStories` | Firebase | Ask HN posts | | `showStories` | Firebase | Show HN posts | | `jobStories` | Firebase | Job posts | | `searchQueries` | Algolia | Full-text search results | | `itemIds` | Firebase | Fetch specific items by ID | | `users` | Firebase | User profiles | ### Output schema | Field | Type | Description | |---|---|---| | `item_id` | int | HN item ID | | `type` | string | story / comment / job / poll / user | | `title` | string | Story or job title | | `text` | string | Self-post body or comment text (HTML decoded) | | `url` | string | External link (link stories) | | `domain` | string | Bare domain extracted from url | | `author` | string | Submitter username | | `score` | int | Upvote points | | `num_comments` | int | Comment count (descendants) | | `created_at` | string | ISO 8601 UTC timestamp | | `hn_url` | string | Direct HN link | | `parent_id` | int | Parent item ID (comments only) | | `story_id` | int | Root story ID (comments only) | | `query` | string | Query or feed name | | `feed` | string | Mode used | | `scraped_at` | string | Run timestamp ISO 8601 UTC | | `parse_confidence` | float | 0.0–1.0 data quality score | | `warnings` | array | Machine-readable quality issues | ### Usage examples #### Get today's top 50 stories ```json { "mode": "topStories", "maxItems": 50 } ```` #### Search for AI stories (newest first) ```json { "mode": "searchQueries", "searchQueries": ["large language models", "AI agents"], "searchSortBy": "date", "searchTags": "story", "maxItems": 100 } ``` #### Top stories with comments ```json { "mode": "topStories", "maxItems": 10, "fetchComments": true, "maxCommentsPerStory": 10 } ``` #### Fetch specific items ```json { "mode": "itemIds", "itemIds": ["48343683", "48340411"] } ``` #### User profiles ```json { "mode": "users", "usernames": ["pg", "tptacek", "dang"] } ``` ### Pricing **Base:** $1.00 per 1,000 items (stories, jobs, user profiles). You only pay for what you get. **With comments** (`fetchComments=true`): comments are billed as an additional `hn-comment` event. This keeps comment-only runs transparent — you pay for what you actually receive. - 50 top stories (no comments): ~$0.05 - 100 search results: ~$0.10 - Daily top-50 monitoring (no comments): ~$1.50/month - Top-10 stories + 10 comments each: $0.01 + $0.10 = ~$0.11 Platform compute is negligible — pure API, no browser, no proxy. ### Pricing examples | Run | Items | Cost | |---|---|---| | Top 50 stories (no comments) | 50 | ~$0.05 | | 100 search results | 100 | ~$0.10 | | Daily top-50 monitoring, 30 days | 1,500 | ~$1.50/mo | | Top-10 stories + 10 comments each | 110 | ~$0.11 | You only pay for items successfully pushed to the dataset. ### FAQ **Do I need a proxy or API key?** No. The HN Firebase and Algolia APIs are public and require zero auth. No proxy needed — HN data is served globally with no geo-blocks. **What formats can I export the results in?** JSON, CSV, JSONL, Excel, and XML — all via Apify's dataset export. Connect to Google Sheets, Airtable, or any BI tool with no code. **Can I run this on a schedule?** Yes. Use Apify Schedules to run daily/hourly on `topStories` or a `searchQueries` query and monitor tech discourse automatically. **What if the actor returns empty results?** For feed modes (`topStories` etc.) the Firebase API returns IDs before story bodies — if a story was deleted mid-run, it is skipped silently. For `searchQueries` mode, verify your `searchTags` filter matches the content type you expect (e.g. `story` vs `comment`). The `OUTPUT` key-value store always explains the failure reason. ### Monitoring mode Run daily on `topStories` or `searchQueries` to track trending topics. Pair with Apify Schedules for automated tech-signal monitoring — no code required. ### Use with AI agents (MCP) This actor is callable as a **tool by AI agents** (Claude Desktop, Cursor, VS Code, n8n, LangGraph, CrewAI, or any MCP-compatible client) via Apify's hosted Model Context Protocol server. An agent uses it to **look up live Hacker News stories, search for content by keyword, or fetch a user's profile mid-conversation** — e.g. "what's trending on HN right now?", "find recent HN discussions about AI agents", or "what's pg's karma on HN?". Point your MCP client at this tool: ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=bovi/hacker-news-scraper", "--header", "Authorization: Bearer " ] } } } ``` Minimal calls an agent can make: ```json { "mode": "topStories", "maxItems": 10 } ``` ```json { "mode": "searchQueries", "searchQueries": ["AI agents"], "maxItems": 20 } ``` ```json { "mode": "users", "usernames": ["pg"] } ``` Flat output rows the agent can reason over directly: ```json { "item_id": 48343683, "type": "story", "title": "Show HN: We built an MCP server for live data", "url": "https://example.com/mcp", "domain": "example.com", "author": "hnuser", "score": 312, "num_comments": 87, "created_at": "2026-06-03T10:22:00Z", "hn_url": "https://news.ycombinator.com/item?id=48343683", "query": "topStories", "feed": "topStories", "parse_confidence": 1.0 } ``` Reliability for agents: both APIs (Firebase + Algolia) are **officially maintained by Y Combinator** for third-party use, so results don't silently break on redesigns. Every row carries a `parse_confidence` score (0.0–1.0) and a `warnings` array — a machine-readable quality signal your agent can filter on. No proxy needed. No API key inside the tool — auth is your Apify token in the client config above. ### Integrations Built for developer-tooling teams and content-intelligence platforms monitoring tech discourse, trending stories, and HN job posts — the JSON/dataset output drops into the tools you already run, no glue code: - **n8n / Make / Zapier** — trigger a run or pipe every new dataset item into 500+ apps (Google Sheets, Airtable, Slack, HubSpot, your database) with no code: [n8n](https://docs.apify.com/platform/integrations/n8n), [Make](https://docs.apify.com/platform/integrations/make), [Zapier](https://docs.apify.com/platform/integrations/zapier). - **Webhooks** — fire your own endpoint the moment a run finishes, to push results straight into your pipeline ([docs](https://docs.apify.com/platform/integrations/webhooks)). - **MCP server** — expose this actor as a tool to Claude, Cursor, or any [MCP client](https://mcp.apify.com) so an AI agent can pull this data mid-conversation ([guide](https://blog.apify.com/how-to-use-mcp/)). - **API & SDKs** — fetch the dataset as JSON, CSV, or Excel through the Apify REST API or the Python / JS SDKs. See all [Apify integrations](https://apify.com/integrations). ### Legal The [HN Firebase API](https://github.com/HackerNews/API) is publicly documented and maintained by Y Combinator for third-party use. The [Algolia HN Search API](https://hn.algolia.com/api) is officially provided under agreement with YC. Both require no authentication and have no scraping restrictions. Built by the Apify actor factory. Not affiliated with Y Combinator or Hacker News. ### More scrapers from our toolkit Building a data pipeline? These actors pair well with this one — each runs on your own Apify account with the same pay-per-result pricing, no subscription: - [Coingecko Scraper](https://apify.com/bovi/coingecko-scraper) - [Credential Breach Checker](https://apify.com/bovi/credential-breach-checker) - [Dexscreener Scraper](https://apify.com/bovi/dexscreener-scraper) - [Github Scraper](https://apify.com/bovi/github-scraper) Chain any of them together from the **Integrations** tab (the *Run succeeded* trigger) to build a multi-step workflow — one actor's output feeds the next. ### Use it from your existing tools #### Use with Claude Desktop / Cursor / Cline (MCP) Load this actor as a tool in your AI assistant. Call it directly from your AI assistant via the Apify MCP server — no Store browsing needed. Paste this into your MCP client config (e.g. `claude_desktop_config.json`) and restart the client: ```json { "mcpServers": { "apify-hacker-news-scraper": { "command": "npx", "args": [ "-y", "@apify/actors-mcp-server", "--tools", "bovi/hacker-news-scraper" ], "env": { "APIFY_TOKEN": "YOUR_APIFY_TOKEN" } } } } ``` Replace `YOUR_APIFY_TOKEN` with your own Apify API token (free at apify.com → Settings → Integrations). Curated to a handful of tools so the agent selects reliably. #### Works with Clay Run this actor as an HTTP enrichment step inside a Clay table: - **Method:** `POST` - **URL:** `https://api.apify.com/v2/acts/bovi~hacker-news-scraper/run-sync-get-dataset-items?token={{apify_token}}` - **Body (JSON):** map your Clay columns to the actor input (see the Input section above), e.g. `{"mode": "{{clay_column}}"}` The run finishes synchronously and returns the dataset rows straight into your Clay table. It runs on Apify's cloud under your own token and usage. Synchronous runs must complete within 300 seconds. # Actor input Schema ## `mode` (type: `string`): Which data to fetch. Use 'topStories' for front-page headlines, 'searchQueries' to find stories by keyword (set searchQueries too), 'itemIds' to fetch specific HN items by ID, 'users' to look up profiles by username. Other options: newStories, bestStories, askStories, showStories, jobStories. ## `maxItems` (type: `integer`): Maximum total items to return across all queries/feeds. Keep low (10–50) for agent use to minimize token cost. 0 = no limit (up to API maximum). Default 100. ## `searchQueries` (type: `array`): Required when mode='searchQueries'. List of search terms to send to the Algolia HN Search API. Each query runs separately. Example: \["AI agents", "large language models"]. Supports quoted phrases. ## `itemIds` (type: `array`): Required when mode='itemIds'. List of HN item IDs to fetch. Accepts story, comment, job, or poll IDs. Example: \["48343683", "48340411"]. ## `usernames` (type: `array`): Required when mode='users'. List of HN usernames to look up. Returns karma, account age, bio, and submission count. Example: \["pg", "tptacek"]. ## `fetchComments` (type: `boolean`): When true, also fetch top-level comments for each story (one level deep). Each comment is a separate row with parent\_id linking to the story. Set false (default) to keep results lean for agent use. ## `maxCommentsPerStory` (type: `integer`): Maximum top-level comments to fetch per story when fetchComments=true. 0 = all available. Default 20. ## `searchSortBy` (type: `string`): Sort order when mode='searchQueries'. 'relevance' returns best-match first; 'date' returns newest first. Default relevance. ## `searchTags` (type: `string`): Algolia type filter for search mode. Use 'story' (default) to return only stories; 'comment' for comments; 'ask\_hn', 'show\_hn', or 'job' for those subtypes. Leave blank for all types. ## Actor input object example ```json { "mode": "topStories", "maxItems": 100, "searchQueries": [ "AI agents", "large language models" ], "itemIds": [ "48343683" ], "usernames": [ "pg" ], "fetchComments": false, "maxCommentsPerStory": 20, "searchSortBy": "relevance", "searchTags": "story" } ``` # Actor output Schema ## `results` (type: `string`): Dataset containing Hacker News Scraper records (item\_id, type, title, url, author, score, num\_comments, created\_at, domain, query, parent\_id, parse\_confidence). # 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 = { "mode": "topStories", "maxItems": 100, "searchQueries": [ "AI agents", "large language models" ], "itemIds": [ "48343683" ], "usernames": [ "pg" ], "fetchComments": false, "maxCommentsPerStory": 20, "searchSortBy": "relevance", "searchTags": "story" }; // Run the Actor and wait for it to finish const run = await client.actor("bovi/hacker-news-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 = { "mode": "topStories", "maxItems": 100, "searchQueries": [ "AI agents", "large language models", ], "itemIds": ["48343683"], "usernames": ["pg"], "fetchComments": False, "maxCommentsPerStory": 20, "searchSortBy": "relevance", "searchTags": "story", } # Run the Actor and wait for it to finish run = client.actor("bovi/hacker-news-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 '{ "mode": "topStories", "maxItems": 100, "searchQueries": [ "AI agents", "large language models" ], "itemIds": [ "48343683" ], "usernames": [ "pg" ], "fetchComments": false, "maxCommentsPerStory": 20, "searchSortBy": "relevance", "searchTags": "story" }' | apify call bovi/hacker-news-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=bovi/hacker-news-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Hacker News Scraper — Stories, Jobs, Comments & Users API", "description": "Scrape Hacker News stories, comments, jobs, and user profiles via the official Firebase and Algolia APIs. No proxy, no auth. Supports top/new/best/ask/show/job feeds, full-text search, comment trees, and user data. Pay per result.", "version": "0.1", "x-build-id": "x9rWallO5mPFfRv51" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/bovi~hacker-news-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-bovi-hacker-news-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/bovi~hacker-news-scraper/runs": { "post": { "operationId": "runs-sync-bovi-hacker-news-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/bovi~hacker-news-scraper/run-sync": { "post": { "operationId": "run-sync-bovi-hacker-news-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": { "mode": { "title": "Mode", "enum": [ "topStories", "newStories", "bestStories", "askStories", "showStories", "jobStories", "searchQueries", "itemIds", "users" ], "type": "string", "description": "Which data to fetch. Use 'topStories' for front-page headlines, 'searchQueries' to find stories by keyword (set searchQueries too), 'itemIds' to fetch specific HN items by ID, 'users' to look up profiles by username. Other options: newStories, bestStories, askStories, showStories, jobStories." }, "maxItems": { "title": "Max items total", "minimum": 0, "type": "integer", "description": "Maximum total items to return across all queries/feeds. Keep low (10–50) for agent use to minimize token cost. 0 = no limit (up to API maximum). Default 100.", "default": 100 }, "searchQueries": { "title": "Search queries", "type": "array", "description": "Required when mode='searchQueries'. List of search terms to send to the Algolia HN Search API. Each query runs separately. Example: [\"AI agents\", \"large language models\"]. Supports quoted phrases.", "items": { "type": "string" } }, "itemIds": { "title": "Item IDs", "type": "array", "description": "Required when mode='itemIds'. List of HN item IDs to fetch. Accepts story, comment, job, or poll IDs. Example: [\"48343683\", \"48340411\"].", "items": { "type": "string" } }, "usernames": { "title": "Usernames", "type": "array", "description": "Required when mode='users'. List of HN usernames to look up. Returns karma, account age, bio, and submission count. Example: [\"pg\", \"tptacek\"].", "items": { "type": "string" } }, "fetchComments": { "title": "Fetch comments", "type": "boolean", "description": "When true, also fetch top-level comments for each story (one level deep). Each comment is a separate row with parent_id linking to the story. Set false (default) to keep results lean for agent use.", "default": false }, "maxCommentsPerStory": { "title": "Max comments per story", "minimum": 0, "type": "integer", "description": "Maximum top-level comments to fetch per story when fetchComments=true. 0 = all available. Default 20.", "default": 20 }, "searchSortBy": { "title": "Search sort order", "enum": [ "relevance", "date" ], "type": "string", "description": "Sort order when mode='searchQueries'. 'relevance' returns best-match first; 'date' returns newest first. Default relevance.", "default": "relevance" }, "searchTags": { "title": "Search tags filter", "type": "string", "description": "Algolia type filter for search mode. Use 'story' (default) to return only stories; 'comment' for comments; 'ask_hn', 'show_hn', or 'job' for those subtypes. Leave blank for all types.", "default": "story" } } }, "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 } } } } } } } } } } ```