# ๐ŸŸง Hacker News Watchlist Scraper (`skootle/hackernews-watchlist`) Actor Scrape Hacker News stories and comments across top, new, best, ask, show, jobs streams. Normalized JSON, ISO dates, author karma + account age, AI-ready markdown. Watchlist mode emits only new records since the last run. Export, run via API, schedule, or integrate with other tools. - **URL**: https://apify.com/skootle/hackernews-watchlist.md - **Developed by:** [Skootle](https://apify.com/skootle) (community) - **Categories:** News, AI, Developer tools - **Stats:** 2 total users, 1 monthly users, 0.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $2.00 / 1,000 hacker news records 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 Watchlist hero](https://raw.githubusercontent.com/kesjam/skootle-actors-assets/main/heroes/hackernews.png) ### TL;DR Monitor Hacker News stories and comments across top, new, best, ask, show, and jobs streams. Returns clean structured JSON with story-type enum, ISO timestamps, author karma + account age, and a 300-500 character markdown summary per story. Watchlist mode emits only NEW records since the previous run. Built on HN's official Firebase API. Zero authentication, zero anti-bot, no rate-limit issues in practice. --- > Try it on a small dataset, then let us know what you think in a [review](https://apify.com/skootle/hackernews-watchlist/reviews). --- ### What does Hacker News Watchlist do? Hacker News Watchlist extracts stories and comments from any Hacker News stream (`top`, `new`, `best`, `ask`, `show`, `jobs`). For each story you get: title, URL, external domain, score, comment count, author, author's karma + account age, rank in the stream, story-type enum (`story`, `ask_hn`, `show_hn`, `job`, `poll`), and ISO 8601 timestamps. With `fetchComments: true`, the actor walks the comment tree per story (configurable cap, max 500 per story) and emits one record per comment with depth, parent ID, body, score, and author info. Watchlist mode (`watchlistMode: true`) makes this scraper schedulable. State persists across runs in the actor's key-value store, so a daily cron only emits stories and comments NEW since the last run. ### Why scrape Hacker News? Hacker News is the canonical curated tech-and-startup discourse feed on the internet. Y Combinator's affiliated community surfaces breaking technical stories, OSS launches, founder posts, hiring threads (`Who Is Hiring?`), and product announcements hours before they hit Twitter or mainstream media. For dev relations, recruiting, technology radar, AI training corpora, and startup intelligence, HN is high-signal data per byte. The HN Firebase API is free and public, but it's verbose: each item is a separate fetch (one for the topstories list, then one per item, then one per comment). This actor handles all of that orchestration plus author lookups (cached per run) plus the watchlist diff logic. ### Who needs this? - **DevRel teams** monitoring HN for new posts about competitor or category technologies - **Recruiters** scanning the monthly `Who Is Hiring?` thread plus the `jobs` stream - **Brand and product teams** watching for unexpected HN posts about their tools - **VC and tech-scouting analysts** filtering `Show HN` for new product launches - **AI / LLM teams** building training corpora from high-quality tech discourse - **AI agents** consuming a daily filtered HN digest as a topic-of-interest feed ### How to use Hacker News Watchlist 1. Open the **Input** tab on the actor page 2. Pick streams in the `streams` field (`top`, `new`, `best`, `ask`, `show`, `jobs`). One run handles many. 3. Set `storiesPerStream` (default 20) 4. Optionally enable `fetchAuthorProfile` (default `true`) for author karma + account age 5. Optionally enable `fetchComments` and set `commentsPerStory` (max 500 per story tree) 6. Optionally set `domainAllowlist` to filter to specific external domains 7. Optionally set `minScore` to ignore low-engagement posts 8. Optionally enable `watchlistMode` for daily diffs 9. Click **Start** ### How much will scraping Hacker News cost? This actor is priced per event: - **Actor Start**: $0.01 once per run - **Hacker News record (story or comment)**: tiered, charged per record written | Apify plan | $/1000 records | |---|---| | FREE | $20.00 | | BRONZE | $17.00 | | SILVER | $14.00 | | GOLD | $12.00 | | PLATINUM | $12.00 | | DIAMOND | $10.80 | A daily watchlist on `top` with `storiesPerStream: 30` and `fetchAuthorProfile: true` runs ~$0.45-$0.50/day on GOLD after the first day (most stories already seen, watchlist filters them out). ### Is it legal to scrape Hacker News? Yes. Hacker News's Firebase API is explicitly published as a public read-only API for developers (`hacker-news.firebaseio.com/v0/`). HN encourages programmatic access. There is no authentication, no terms-of-service block on commercial use, and the data (titles, URLs, author handles, scores, public comments) is freely visible to anyone in a browser. Use the data for research, AI training, brand monitoring, recruiting, internal analytics. Standard practice is to attribute HN as a source if you republish content, but the API itself is unrestricted. ### Examples #### Example 1: Daily top-30 digest ```json { "streams": ["top"], "storiesPerStream": 30, "fetchAuthorProfile": true, "watchlistMode": true, "maxItems": 30 } ```` #### Example 2: New posts above 100 score, last 24h ```json { "streams": ["new"], "storiesPerStream": 100, "minScore": 100, "fetchAuthorProfile": true, "maxItems": 30 } ``` #### Example 3: Show HN product-launch tracker ```json { "streams": ["show"], "storiesPerStream": 50, "watchlistMode": true, "fetchAuthorProfile": true, "maxItems": 50 } ``` #### Example 4: Ask HN community question feed ```json { "streams": ["ask"], "storiesPerStream": 30, "fetchComments": true, "commentsPerStory": 30, "watchlistMode": true, "maxItems": 1000 } ``` #### Example 5: Job-listing watchlist ```json { "streams": ["jobs"], "storiesPerStream": 100, "watchlistMode": true, "maxItems": 100 } ``` #### Example 6: Brand monitoring (filter by domain) ```json { "streams": ["top", "new"], "storiesPerStream": 100, "domainAllowlist": ["yourcompany.com", "competitor1.com", "competitor2.com"], "watchlistMode": true, "maxItems": 50 } ``` #### Example 7: AI / LLM corpus build ```json { "streams": ["top"], "storiesPerStream": 500, "fetchComments": true, "commentsPerStory": 100, "fetchAuthorProfile": true, "maxItems": 50000 } ``` Run weekly to accumulate a labeled tech-discourse dataset for fine-tuning. #### Example 8: Author-trust filter ```json { "streams": ["new"], "storiesPerStream": 200, "fetchAuthorProfile": true, "minScore": 5, "maxItems": 100 } ``` Filter the output downstream for `authorAccountAge != 'today'` and `authorKarma > 100` to skip brand-new spam accounts. ### Input parameters | Field | Type | Default | Description | |---|---|---|---| | `streams` | enum\[] | `["top"]` | `top`, `new`, `best`, `ask`, `show`, `jobs`. One run handles many. | | `storiesPerStream` | int | `20` | 1-500 | | `fetchAuthorProfile` | bool | `true` | Adds author karma + account age. One extra API call per unique author, cached. | | `fetchComments` | bool | `false` | Walks the comment tree per story | | `commentsPerStory` | int | `0` | Max 500 | | `domainAllowlist` | string\[] | `[]` | Only emit stories whose external URL matches | | `minScore` | int | `0` | Score threshold | | `watchlistMode` | bool | `false` | Idempotent diff against KV-stored seen IDs | | `maxItems` | int | `50` | Hard cap on records (stories + comments) | ### Story-type enum | Value | Meaning | |---|---| | `story` | Standard linked story | | `ask_hn` | Ask HN: question to the community | | `show_hn` | Show HN: project/product launch | | `job` | YC company job posting | | `poll` | HN poll | ### Hacker News output format The dataset has two record types. Filter by `recordType`. #### `hn_story` | Field | Type | Description | |---|---|---| | `outputSchemaVersion`, `recordType`, `recordId` | string | Discriminated identity | | `itemId`, `url`, `hnUrl` | int/string | HN ID + external URL + HN comment-page URL | | `storyType` | enum | See enum table | | `title`, `text`, `textPlain` | string | Title + body (HTML + stripped) | | `externalUrl`, `domain` | string | External link + parsed domain | | `author`, `authorKarma`, `authorAccountAge` | string/int/string | Author profile (when `fetchAuthorProfile: true`); accountAge as `'12y'`, `'5mo'`, etc. | | `score`, `descendants`, `rank` | int | Score, comment count, position in stream | | `stream` | enum | Source stream | | `createdAt`, `scrapedAt` | ISO 8601 | | | `fieldCompletenessScore`, `agentMarkdown` | int / string | Quality + LLM-ready summary | #### `hn_comment` | Field | Type | Description | |---|---|---| | `outputSchemaVersion`, `recordType`, `recordId` | string | Discriminated identity | | `itemId`, `url` | int/string | Comment ID + URL | | `storyId`, `parentId`, `depth` | int | Tree linkage | | `text`, `textPlain` | string | Body (HTML + stripped) | | `author`, `createdAt`, `scrapedAt` | string / ISO 8601 | | | `fieldCompletenessScore`, `agentMarkdown` | int / string | Quality + LLM-ready summary | #### Hacker News scraper output example (story) ```json { "outputSchemaVersion": "2026-05-08", "recordType": "hn_story", "recordId": "hn:story:48067119", "itemId": 48067119, "stream": "top", "rank": 1, "storyType": "story", "title": "Google broke reCAPTCHA for de-googled Android users", "url": "https://reclaimthenet.org/google-broke-recaptcha-for-de-googled-android-users", "domain": "reclaimthenet.org", "score": 656, "descendants": 234, "author": "anonymousiam", "authorKarma": 5099, "authorAccountAge": "9y", "createdAt": "2026-05-08T14:22:53.000Z", "fieldCompletenessScore": 100, "agentMarkdown": "**๐Ÿ“ฐ HN ยท Google broke reCAPTCHA for de-googled Android users**\n- โฌ† 656 ยท ๐Ÿ’ฌ 234 ยท #1\n- ๐Ÿ‘ค u/anonymousiam ยท 5099 karma ยท 9y\n- ๐ŸŒ reclaimthenet.org\n- ๐Ÿ”— https://reclaimthenet.org/..." } ``` ### During the Actor run The actor first fetches the stream's ID list (one call per stream). Then for each ID it fetches the item details (`hacker-news.firebaseio.com/v0/item/.json`). When `fetchAuthorProfile: true`, the author's profile is fetched once and cached for the rest of the run (so a story with 50 comments by the same person costs one extra API call, not 50). When `fetchComments: true`, the comment tree is walked depth-first per story. Each record is validated against a Zod schema before push. The actor writes: 1. **`OUTPUT`** โ€” compact run summary 2. **`AGENT_BRIEFING`** โ€” markdown digest with top stories by score 3. **`WATCHLIST_STATE`** โ€” (when `watchlistMode: true`) seen story + comment IDs ### FAQ #### How does Hacker News Watchlist work? The actor calls HN's official Firebase API at `hacker-news.firebaseio.com/v0/`. Every list (top, new, best, ask, show, jobs) is one HTTP call returning an array of IDs. Every item is one HTTP call returning the full item JSON. #### Is there a rate limit? HN's Firebase API doesn't publish a hard rate limit and is generous in practice. The actor adds a 60ms delay between requests as a courtesy to avoid spiking concurrent connections. #### Can I monitor for new stories only? Yes. Set `watchlistMode: true`. The first run captures everything; subsequent runs only emit records new since the previous run. #### Can I get author karma and account age? Yes โ€” that's the default (`fetchAuthorProfile: true`). Adds one HN API call per unique author, cached within the run. #### Can I get comments along with stories? Yes. Set `fetchComments: true` and `commentsPerStory` to your cap. #### Can I filter by domain? Yes. Set `domainAllowlist` to a list of allowed domains (e.g., `["yourcompany.com"]`). Only stories whose external URL matches will be emitted. #### Can I filter by score? Yes. Set `minScore` to your threshold. Stories below it are skipped. #### Can I use this with the Apify API? Yes. POST to `https://api.apify.com/v2/acts/skootle~hackernews-watchlist/runs`. #### Can I integrate with Make / Zapier / n8n / Slack? Yes. Click **Integrations** on the actor page. #### Why use this when HN's API is free? The free API requires per-item fetches and gives you no schema. This actor handles all the orchestration (stream โ†’ IDs โ†’ items โ†’ authors โ†’ comments โ†’ watchlist diff), normalizes into a versioned typed schema, joins author profile data per story, computes ranks, and ships agent-ready markdown summaries. If you're feeding this into a daily Slack digest or an AI agent, it pays back the per-record cost in saved engineering time. #### Your feedback Hit a bug or want a feature? Open an issue on the [Issues tab](https://apify.com/skootle/hackernews-watchlist/issues/open) rather than the reviews page, and we'll fix it fast (typically within 48 hours). ### Why choose Hacker News Watchlist - **All 6 streams covered** โ€” `top`, `new`, `best`, `ask`, `show`, `jobs`. One actor handles all in one run. - **Author profile join** โ€” `authorKarma`, `authorAccountAge` ready to filter spam vs trusted contributors - **Story-type enum** โ€” `story`, `ask_hn`, `show_hn`, `job`, `poll`. No need to grep titles. - **Watchlist diff mode** โ€” only emits NEW records since the last run - **Versioned schema** โ€” `outputSchemaVersion: '2026-05-08'` literal - **Idempotent record IDs** โ€” `hn:story:`, `hn:comment:` stable across runs - **Discriminated union** โ€” stories + comments share one dataset, filterable by `recordType` - **Agent-grade output** โ€” `agentMarkdown` ready to paste into an LLM context - **Zero anti-bot, zero auth** โ€” built on HN's official public Firebase API ### Other Skootle actors you might want to check - **[Reddit Subreddit Scraper](https://apify.com/skootle/reddit-subreddit-monitor)** โ€” same pattern for subreddit monitoring - **[GitHub Trending Repos](https://apify.com/skootle/github-trending)** โ€” daily trending dev repos with API enrichment - **[SEC EDGAR Filings Monitor](https://apify.com/skootle/sec-edgar-filings)** โ€” public-company filings stream - **[Apple App Store Reviews Monitor](https://apify.com/skootle/app-store-reviews)** โ€” App Store reviews + metadata - **[Shopify App Store Scraper](https://apify.com/skootle/shopify-app-store-scraper)** โ€” Shopify app listings + pricing tiers ### Support and contact File issues on this actor's page โ€” replies within 48 hours. Feature requests welcome โ€” tag with `enhancement`. # Actor input Schema ## `streams` (type: `array`): Which HN streams to pull. One run handles many. ## `storiesPerStream` (type: `integer`): How many stories to fetch from each stream (1 to 500). ## `fetchAuthorProfile` (type: `boolean`): Adds one HN API call per unique author. Cached within a single run. ## `fetchComments` (type: `boolean`): Walks the comment tree per story. Adds latency and records. ## `commentsPerStory` (type: `integer`): Hard cap on comments per story (0 to 500). ## `domainAllowlist` (type: `array`): Only emit stories whose external URL domain is in this list. Empty = all. ## `minScore` (type: `integer`): Only emit stories with score >= N. ## `watchlistMode` (type: `boolean`): When true, only emit records NEW since the previous run. State persists in the key-value store. ## `maxItems` (type: `integer`): Hard cap on total records (stories + comments). Conservative default for the 5-minute auto-test. ## Actor input object example ```json { "streams": [ "top" ], "storiesPerStream": 20, "fetchAuthorProfile": true, "fetchComments": false, "commentsPerStory": 0, "domainAllowlist": [], "minScore": 0, "watchlistMode": false, "maxItems": 50 } ``` # Actor output Schema ## `datasetItems` (type: `string`): Stories and comments. Discriminate by recordType. ## `agentBriefing` (type: `string`): Markdown digest with top 10 stories by score. ## `runSummary` (type: `string`): Compact OUTPUT object with row counts and per-stage error counts. # 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 = { "streams": [ "top" ], "domainAllowlist": [] }; // Run the Actor and wait for it to finish const run = await client.actor("skootle/hackernews-watchlist").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`๐Ÿ’พ 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); }); // ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ 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 = { "streams": ["top"], "domainAllowlist": [], } # Run the Actor and wait for it to finish run = client.actor("skootle/hackernews-watchlist").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("๐Ÿ’พ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "streams": [ "top" ], "domainAllowlist": [] }' | apify call skootle/hackernews-watchlist --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=skootle/hackernews-watchlist", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "๐ŸŸง Hacker News Watchlist Scraper", "description": "Scrape Hacker News stories and comments across top, new, best, ask, show, jobs streams. Normalized JSON, ISO dates, author karma + account age, AI-ready markdown. Watchlist mode emits only new records since the last run. Export, run via API, schedule, or integrate with other tools.", "version": "0.1", "x-build-id": "embZxCbDWumehh3pD" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/skootle~hackernews-watchlist/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-skootle-hackernews-watchlist", "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/skootle~hackernews-watchlist/runs": { "post": { "operationId": "runs-sync-skootle-hackernews-watchlist", "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/skootle~hackernews-watchlist/run-sync": { "post": { "operationId": "run-sync-skootle-hackernews-watchlist", "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": { "streams": { "title": "Streams to monitor", "type": "array", "description": "Which HN streams to pull. One run handles many.", "items": { "type": "string" } }, "storiesPerStream": { "title": "Stories per stream", "minimum": 1, "maximum": 500, "type": "integer", "description": "How many stories to fetch from each stream (1 to 500).", "default": 20 }, "fetchAuthorProfile": { "title": "Include author karma + account age", "type": "boolean", "description": "Adds one HN API call per unique author. Cached within a single run.", "default": true }, "fetchComments": { "title": "Fetch comments per story", "type": "boolean", "description": "Walks the comment tree per story. Adds latency and records.", "default": false }, "commentsPerStory": { "title": "Comments per story (max)", "minimum": 0, "maximum": 500, "type": "integer", "description": "Hard cap on comments per story (0 to 500).", "default": 0 }, "domainAllowlist": { "title": "Domain allowlist", "type": "array", "description": "Only emit stories whose external URL domain is in this list. Empty = all.", "items": { "type": "string" } }, "minScore": { "title": "Minimum score", "minimum": 0, "type": "integer", "description": "Only emit stories with score >= N.", "default": 0 }, "watchlistMode": { "title": "Watchlist mode (idempotent diff)", "type": "boolean", "description": "When true, only emit records NEW since the previous run. State persists in the key-value store.", "default": false }, "maxItems": { "title": "Max total records", "minimum": 1, "maximum": 20000, "type": "integer", "description": "Hard cap on total records (stories + comments). Conservative default for the 5-minute auto-test.", "default": 50 } } }, "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 } } } } } } } } } } ```