# Reddit Search Scraper - Keyword & Brand Monitoring ($1.5/1k) (`harshmaur/reddit-search-scraper`) Actor Search Reddit by keyword and scrape every matching post, comment, and subreddit. Monitor brand mentions, track topics, and find leads with sort and time-range filters — all of Reddit or one community. No API key, no login. Export CSV/Excel/JSON. From $1.50 per 1,000 results. - **URL**: https://apify.com/harshmaur/reddit-search-scraper.md - **Developed by:** [Harsh Maur](https://apify.com/harshmaur) (community) - **Categories:** AI, Social media, Agents - **Stats:** 3 total users, 2 monthly users, 83.3% runs succeeded, 2 bookmarks - **User rating**: 5.00 out of 5 stars ## Pricing from $1.50 / 1,000 result saveds 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 ## Reddit Search Scraper — Search Reddit by Keyword & Scrape the Results (No API Key)

The Reddit keyword search scraper: turn any search term into structured posts, comments, and subreddits. No login, no API key, no rate limits — from $1.50 per 1,000 results.

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What it does • How to use • Input • Output • Use cases • Pricing • FAQ

--- ### What does Reddit Search Scraper do? {#what-does-reddit-search-scraper-do} **Reddit Search Scraper** is built around one job: you give it keywords, it runs each one as a [Reddit](https://www.reddit.com/) search and saves everything that matches as clean, structured data. Each term can return **posts** (the default), **comments**, and **communities (subreddits)** — pick any combination per run. You stay in control of how Reddit ranks the matches: sort by **relevance, hot, top, new, or comment count**, and narrow the window from the **last hour** all the way out to **all time**. Want laser focus instead of site-wide coverage? Point `withinCommunity` at a single subreddit (`gaming` and `r/gaming` both work) and the search never leaves it. You can even flip on `crawlCommentsPerPost` to pull the discussion under every post the search finds. There is **no Reddit account, no OAuth app, and no API key** involved — the scraper reads public Reddit directly and sidesteps the official API's 600-requests-per-10-minutes ceiling. Results land in your Apify dataset ready to export as **JSON, CSV, Excel, XML, or HTML**, or to flow into **n8n, Zapier, Make, the REST API, or MCP-connected AI agents**. --- ### How to search Reddit by keyword (step by step) {#how-to-search-reddit-by-keyword} Going from a keyword to a downloadable dataset takes about a minute: 1. [Sign up for Apify](https://apify.com/) for free, or log in to your existing account 2. Open [Reddit Search Scraper](https://apify.com/harshmaur/reddit-search-scraper) 3. Add one or more **Search keywords** — each one runs as its own independent Reddit search 4. Tick what you want back: **posts** (on by default), **comments**, and/or **communities** 5. Pick a **sort order** (relevance / hot / top / new / comments) and a **time range** (last hour → all time) 6. Optionally fill **Limit search to a community** to stay inside one subreddit 7. Hit **Start**, then grab your results as JSON, CSV, or Excel from the dataset tab > 💡 Every saved item carries the `searchTerm` that produced it, so multi-keyword runs are trivial to split apart afterwards. **Fine-tuning knobs:** `maxPostsCount`, `maxCommentsCount`, and `maxCommunitiesCount` cap how much each search term saves; `crawlCommentsPerPost` + `maxCommentsPerPost` add the comment thread under each matched post; `includeNSFW` opts into 18+ content (off by default). --- ### Input example: Reddit keyword monitoring {#input-example} A classic reddit brand monitoring setup — watch a brand name across all of Reddit, freshest mentions first, restricted to the past week: ```json { "searchTerms": ["Notion", "Notion AI"], "searchPosts": true, "searchComments": true, "searchCommunities": false, "searchSort": "new", "searchTime": "week", "maxPostsCount": 100, "maxCommentsCount": 200, "includeNSFW": false, "proxy": { "useApifyProxy": true, "apifyProxyGroups": ["RESIDENTIAL"] } } ```` To keep the same watchlist inside one community, add `"withinCommunity": "r/productivity"` — the search then runs only against that subreddit. To also capture the conversation under each matching post, set `"crawlCommentsPerPost": true` with a `"maxCommentsPerPost"` cap. *** ### Output example {#output-example} Every match is saved as a flat JSON object with a `dataType` discriminator (`post`, `comment`, or `community`). Here's a post item found by a keyword search: ```json { "dataType": "post", "id": "t3_1kx94qe", "parsedId": "1kx94qe", "title": "Switched our whole team to Notion AI — honest review after 3 months", "body": "We migrated from a mix of Confluence and Google Docs back in March...", "postType": "text", "flair": "Review", "authorName": "ops_lead_42", "authorId": "t2_9k3mfa", "parsedAuthorId": "9k3mfa", "communityName": "r/productivity", "parsedCommunityName": "productivity", "subredditName": "productivity", "subredditId": "t5_2qkq6", "subredditSubscribers": 2890000, "postUrl": "https://www.reddit.com/r/productivity/comments/1kx94qe/", "url": "https://www.reddit.com/r/productivity/comments/1kx94qe/", "score": 847, "upVotes": 847, "upvoteRatio": 0.94, "commentsCount": 213, "totalAwardsReceived": 1, "nsfw": false, "over18": false, "isSelf": true, "locked": false, "stickied": false, "edited": false, "domain": "self.productivity", "mediaType": "text", "hasMedia": false, "isVideo": false, "isGallery": false, "ageHours": 52.4, "scorePerHour": 16.16, "commentsPerHour": 4.06, "engagementTotal": 1060, "commentToScoreRatio": 0.25, "isHighEngagement": true, "titleLength": 62, "bodyLength": 1845, "wordCount": 322, "createdAt": "2026-06-07T09:14:00.000Z", "crawledAt": "2026-06-09T13:38:00.000Z", "searchTerm": "Notion AI" } ``` Posts arrive with 70+ fields in total — including media details (`galleryImages`, `mediaAssets`, `videoUrl`), moderation flags, and derived engagement analytics. Comment items add thread context (`postTitle`, `parentId`, `depth`, `controversiality`, `isSubmitter`), and community items report `membersCount`, `onlineUsersCount`, descriptions, and icons. *** ### What can you do with scraped Reddit search results? {#use-cases} - 🔔 **Reddit brand monitoring** — track keywords on Reddit like your brand, product names, and common misspellings; sort by `new`, schedule the run, and catch every mention while it's still answerable. - 🎯 **Lead generation** — search phrases your buyers actually type ("looking for a CRM", "alternative to X") and surface threads where a helpful reply can win a customer. - 📊 **Market research** — pull unfiltered opinions on a product category from across Reddit or inside one niche subreddit, then mine the `body` text for pain points and feature requests. - 📈 **Trend tracking** — re-run the same keywords on a schedule with `searchTime: "day"` and watch `score`, `commentsCount`, and `scorePerHour` to spot topics gaining momentum before they peak. - ✍️ **Content discovery** — find the top-voted questions and discussions around your topic (`searchSort: "top"`) to fuel blog posts, videos, and FAQ pages people already want. *** ### How much does Reddit Search Scraper cost? {#pricing} Billing is **pay per result** — there is no subscription and no platform markup. You're charged a small fee to start the run plus a per-item fee for every result stored: - **Run start:** $0.02 - **Per stored result:** $0.0015 That works out to **$1.52 for 1,000 results**, $15.02 for 10,000, and so on — roughly **from $1.50 per 1,000 results**, with zero cost between runs. A daily keyword-monitoring schedule that saves 50 mentions per day costs about $0.10/day. Keep runs cheap by tuning `maxPostsCount` / `maxCommentsCount` per search term: you only pay for what gets stored. *** ### FAQ {#faq} #### Do I need a Reddit API key or account? No. Reddit Search Scraper reads publicly visible search results directly, so there's nothing to register: no API key, no OAuth app, no Reddit login. It also isn't bound by the official API's 600 requests per 10 minutes limit. #### Can I monitor a keyword on Reddit over time? Yes — this is the actor's sweet spot. Configure your keywords with `searchSort: "new"` and a short window like `searchTime: "day"`, then create a **Schedule** in the Apify Console to re-run it hourly or daily. Pair it with a webhook or an n8n/Zapier/Make flow and new mentions land in Slack, a spreadsheet, or your CRM automatically. #### Can I search within a single subreddit? Yes. Set `withinCommunity` to the subreddit — plain name (`gaming`) or prefixed (`r/gaming`) both work — and every search term runs only inside that community. Leave it empty to search all of Reddit. #### What's the difference between searching for posts, comments, and communities? They're three independent toggles. `searchPosts` (default on) returns submissions that match your keywords, `searchComments` returns individual matching comments with their thread context, and `searchCommunities` returns subreddits whose name or description matches. Enable any mix in one run; the `dataType` field tells each item apart. #### Can I also get the comments under each post the search finds? Yes. Turn on `crawlCommentsPerPost` and the scraper visits every matched post and collects its comment thread, capped by `maxCommentsPerPost`. Expect longer runs and more stored items when this is enabled. #### How do the sort and time filters work? `searchSort` mirrors Reddit's own search ranking: `relevance`, `hot`, `top`, `new`, or `comments`. `searchTime` constrains results to the `hour`, `day`, `week`, `month`, `year`, or `all` time. For monitoring, `new` + a tight window works best; for research, `top` + `year` or `all` surfaces the canonical threads. #### How many results can I get per keyword? Each search term gets its own budget: up to `maxPostsCount` posts (default 25, up to 50,000), `maxCommentsCount` comments, and `maxCommunitiesCount` subreddits. Set a limit to `0` to switch that result type off entirely. #### Which export formats and integrations are supported? Datasets download as **JSON, CSV, Excel, XML, or HTML** straight from Apify. For automation, trigger and consume runs via **n8n, Zapier, Make, or the REST API** — and MCP-compatible AI agents (Claude, ChatGPT, Cursor) can call the actor as a tool through the [Apify MCP server](https://mcp.apify.com/). *** ### More Reddit scrapers Searching by keyword is just one way in. If your starting point is a URL, a user, or a whole community, one of these siblings will fit better: | Actor | When to use it instead | | --- | --- | | [Reddit Scraper](https://apify.com/harshmaur/reddit-scraper) | The all-in-one: combine keyword search, direct post/profile/subreddit URLs, and full-subreddit crawls in a single run. | | [Reddit Comments Scraper](https://apify.com/harshmaur/reddit-comments-scraper) | You already have post URLs and want every comment in the thread, nested replies included. | | [Reddit User Scraper](https://apify.com/harshmaur/reddit-user-scraper) | You're profiling specific Redditors — karma, account age, and their post/comment history. | | [Subreddit Scraper](https://apify.com/harshmaur/reddit-subreddit-scraper) | You want a community's full post archive rather than keyword matches. | ***

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# Actor input Schema ## `searchTerms` (type: `array`): Enter one or more keywords to search Reddit (e.g. "best laptops 2026", "AI news"). Each keyword runs as a separate search. ## `searchPosts` (type: `boolean`): Include posts in search results. ## `searchComments` (type: `boolean`): Include comments in search results. ## `searchCommunities` (type: `boolean`): Include communities (subreddits) in search results. ## `withinCommunity` (type: `string`): Restrict the search to a single subreddit, e.g. gaming or r/gaming. Leave empty to search all of Reddit. ## `searchSort` (type: `string`): Controls how search results are ranked. ## `searchTime` (type: `string`): Limit results to posts from a specific time window. ## `maxPostsCount` (type: `integer`): Maximum number of posts to save per search (when 'Search for posts' is enabled). ## `maxCommentsCount` (type: `integer`): Maximum number of comments to save per search (when 'Search for comments' is enabled). ## `maxCommunitiesCount` (type: `integer`): Maximum number of communities to save per search (when 'Search for communities' is enabled). ## `crawlCommentsPerPost` (type: `boolean`): When enabled, comments are also collected for every post found. This significantly increases run time and data output. ## `maxCommentsPerPost` (type: `integer`): Maximum comments to scrape per individual post (when 'Scrape comments for each post' is enabled). ## `includeNSFW` (type: `boolean`): Include posts marked as Not Safe For Work in results. ## `proxy` (type: `object`): Either use Apify proxy, or provide your own proxy servers. ## Actor input object example ```json { "searchTerms": [ "artificial intelligence" ], "searchPosts": true, "searchComments": false, "searchCommunities": false, "withinCommunity": "", "searchSort": "new", "searchTime": "all", "maxPostsCount": 25, "maxCommentsCount": 25, "maxCommunitiesCount": 5, "crawlCommentsPerPost": false, "maxCommentsPerPost": 10, "includeNSFW": false, "proxy": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } } ``` # Actor output Schema ## `results` (type: `string`): All scraped Reddit data including posts, comments, communities, and user profiles. Use 'dataType' field to filter by type. # 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 = { "searchTerms": [ "artificial intelligence" ], "searchSort": "new", "searchTime": "all", "maxPostsCount": 25, "maxCommentsCount": 25, "maxCommunitiesCount": 5, "maxCommentsPerPost": 10, "proxy": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }; // Run the Actor and wait for it to finish const run = await client.actor("harshmaur/reddit-search-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 = { "searchTerms": ["artificial intelligence"], "searchSort": "new", "searchTime": "all", "maxPostsCount": 25, "maxCommentsCount": 25, "maxCommunitiesCount": 5, "maxCommentsPerPost": 10, "proxy": { "useApifyProxy": True, "apifyProxyGroups": ["RESIDENTIAL"], }, } # Run the Actor and wait for it to finish run = client.actor("harshmaur/reddit-search-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 '{ "searchTerms": [ "artificial intelligence" ], "searchSort": "new", "searchTime": "all", "maxPostsCount": 25, "maxCommentsCount": 25, "maxCommunitiesCount": 5, "maxCommentsPerPost": 10, "proxy": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }' | apify call harshmaur/reddit-search-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=harshmaur/reddit-search-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Reddit Search Scraper - Keyword & Brand Monitoring ($1.5/1k)", "description": "Search Reddit by keyword and scrape every matching post, comment, and subreddit. Monitor brand mentions, track topics, and find leads with sort and time-range filters — all of Reddit or one community. No API key, no login. Export CSV/Excel/JSON. From $1.50 per 1,000 results.", "version": "0.0", "x-build-id": "PEUqhaShx69zdl8BH" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/harshmaur~reddit-search-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-harshmaur-reddit-search-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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/harshmaur~reddit-search-scraper/runs": { "post": { "operationId": "runs-sync-harshmaur-reddit-search-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/harshmaur~reddit-search-scraper/run-sync": { "post": { "operationId": "run-sync-harshmaur-reddit-search-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "searchTerms" ], "properties": { "searchTerms": { "title": "Search keywords", "type": "array", "description": "Enter one or more keywords to search Reddit (e.g. \"best laptops 2026\", \"AI news\"). Each keyword runs as a separate search.", "default": [], "items": { "type": "string" } }, "searchPosts": { "title": "Search for posts", "type": "boolean", "description": "Include posts in search results.", "default": true }, "searchComments": { "title": "Search for comments", "type": "boolean", "description": "Include comments in search results.", "default": false }, "searchCommunities": { "title": "Search for communities", "type": "boolean", "description": "Include communities (subreddits) in search results.", "default": false }, "withinCommunity": { "title": "Limit search to a community", "type": "string", "description": "Restrict the search to a single subreddit, e.g. gaming or r/gaming. Leave empty to search all of Reddit.", "default": "" }, "searchSort": { "title": "Sort results by", "enum": [ "", "relevance", "hot", "top", "new", "comments" ], "type": "string", "description": "Controls how search results are ranked.", "default": "new" }, "searchTime": { "title": "Time range", "enum": [ "all", "hour", "day", "week", "month", "year" ], "type": "string", "description": "Limit results to posts from a specific time window.", "default": "all" }, "maxPostsCount": { "title": "Max posts", "minimum": 0, "maximum": 50000, "type": "integer", "description": "Maximum number of posts to save per search (when 'Search for posts' is enabled).", "default": 25 }, "maxCommentsCount": { "title": "Max comments", "minimum": 0, "type": "integer", "description": "Maximum number of comments to save per search (when 'Search for comments' is enabled).", "default": 25 }, "maxCommunitiesCount": { "title": "Max communities", "minimum": 0, "type": "integer", "description": "Maximum number of communities to save per search (when 'Search for communities' is enabled).", "default": 5 }, "crawlCommentsPerPost": { "title": "Scrape comments for each post", "type": "boolean", "description": "When enabled, comments are also collected for every post found. This significantly increases run time and data output.", "default": false }, "maxCommentsPerPost": { "title": "Max comments per post", "minimum": 0, "type": "integer", "description": "Maximum comments to scrape per individual post (when 'Scrape comments for each post' is enabled).", "default": 10 }, "includeNSFW": { "title": "Include NSFW (18+) content", "type": "boolean", "description": "Include posts marked as Not Safe For Work in results.", "default": false }, "proxy": { "title": "Proxy configuration", "type": "object", "description": "Either use Apify proxy, or provide your own proxy servers.", "default": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } } } }, "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 } } } } } } } } } } ```