# Reddit Search Scraper - 3,000+ Results in 10 Seconds (`clearpath/reddit-search-scraper`) Actor Search Reddit posts and comments by keyword. 3,000+ results in seconds with smart subreddit auto-discovery. Titles, bodies, scores, authors, timestamps, permalinks. 5 sort orders, time filters. Scope to specific subreddits or let it find them for you. - **URL**: https://apify.com/clearpath/reddit-search-scraper.md - **Developed by:** [ClearPath](https://apify.com/clearpath) (community) - **Categories:** Lead generation, Social media, Automation - **Stats:** 47 total users, 22 monthly users, 99.7% runs succeeded, NaN bookmarks - **User rating**: 1.00 out of 5 stars ## Pricing from $0.99 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Reddit Search Scraper | Fast Bulk Keyword Search (2026)
3,000+ results in under 10 seconds — type a keyword, get results from 20+ auto-discovered subreddits. The fastest Reddit search scraper on Apify.
Just enter a keyword. The actor automatically finds the top 20 most relevant subreddits and searches across all of them in parallel. No need to know which subreddits to target. Posts, comments, or both. Five sort orders, time filters.
Clearpath Reddit Suite   •  Search, analyze, and monitor Reddit at scale
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Search Scraper
Keyword search across Reddit 		 Post & Comments
Full comment tree scraper 		 Subreddit Posts
Feed scraper with 108 fields 		 Profile Scraper
Bulk profile & karma lookup
#### Copy to your AI assistant Copy this block into ChatGPT, Claude, Cursor, or any LLM to start building with this data. ```` Reddit Search Scraper (clearpath/reddit-search-scraper) on Apify searches Reddit posts and comments by keyword at scale. Returns structured results with title, author, subreddit, score, comment count, upvote ratio, creation date, body text, permalink, and status flags. Content types: posts only, comments only, or both. 5 sort orders: relevance, new, top, hot, most comments. Time filters: hour, day, week, month, year. Subreddit scoping: search all of Reddit, one subreddit, or multiple subreddits in parallel. Subreddit input accepts plain names, r/prefix, or full URLs. No hard result limit (set maxResults to 0 for unlimited). Input: query (required), maxResults (default 100, 0 = unlimited), contentType (posts/comments/both), sort, timeFilter, subreddit (single), subreddits (array). Output: JSON array of post rows (20 fields) and/or comment rows (13 fields). Pricing: $0.99 per 1,000 results (pay per event). Apify token required. ```` ### Key Features - **Smart subreddit auto-discovery** — just type a keyword and the actor automatically finds the top 20 most relevant subreddits and searches across all of them. Get thousands of targeted results without knowing which subreddits to target - **Posts, comments, or both** — a single `contentType` toggle controls whether you get posts, comments, or both result types in one run. No need to run the actor twice - **5 sort orders** — relevance, new, top, hot, and most comments. Choose how results are ranked to match your use case - **Time filtering** — restrict results to the past hour, day, week, month, or year. Combine with any sort order to narrow the window - **Subreddit scoping** — search all of Reddit at once, target a single subreddit, or search across multiple subreddits in one run - **Bulk subreddit input** — paste subreddit names in any format: `python`, `r/python`, `https://reddit.com/r/python`. Mix formats freely in the same input - **Fast** — results stream in within seconds. Multiple subreddits run concurrently, so adding more subs doesn't proportionally increase run time ### How to Search Reddit #### Auto-discover subreddits (easiest) Just enter a keyword. The actor finds the top 20 relevant subreddits automatically and searches across them. ```json { "query": "notion alternative", "maxResults": 1000 } ```` Returns ~1,000+ results from across r/notion, r/obsidianmd, r/productivity, r/notetaking, and 16 other relevant communities. #### Basic keyword search Enter a search query. The actor searches all of Reddit and returns up to 100 posts sorted by relevance. ```json { "query": "python web scraping" } ``` #### Search for comments instead of posts Set `contentType` to `comments` to search comment text instead of post titles and bodies. ```json { "query": "best framework for REST APIs", "contentType": "comments", "maxResults": 200 } ``` #### Get both posts and comments Set `contentType` to `both` to retrieve matching posts and comments in a single run. Results are labeled with `_type` so you can filter them downstream. ```json { "query": "remote work productivity", "contentType": "both", "maxResults": 500 } ``` #### Search within a specific subreddit Use `subreddit` to scope results to a single community. Any format works. ```json { "query": "machine learning projects", "subreddit": "r/learnpython", "sort": "top", "timeFilter": "month" } ``` #### Search across multiple subreddits Use the `subreddits` array to search several communities in parallel. Mix name formats freely. ```json { "query": "best budget laptop 2026", "subreddits": [ "SuggestALaptop", "r/laptops", "https://www.reddit.com/r/thinkpad" ], "sort": "new", "maxResults": 300 } ``` #### Newest results with time filter Combine `sort: "new"` with a time filter to find the most recent discussions within a specific window. ```json { "query": "iPhone 17 review", "sort": "new", "timeFilter": "week", "maxResults": 1000 } ``` ### Input Parameters | Parameter | Type | Default | Description | |-----------|------|---------|-------------| | `query` | string | *required* | Keywords to search for. Supports boolean operators and quoted phrases (max 700 characters) | | `maxResults` | integer | `100` | Maximum number of results to return. Set to 0 for unlimited | | `contentType` | enum | `posts` | What to search: `posts`, `comments`, or `both` | | `sort` | enum | `relevance` | Sort order: `relevance`, `new`, `top`, `hot`, `comments` | | `timeFilter` | enum | all time | Time range: `hour`, `day`, `week`, `month`, `year`. Leave empty for all time | | `subreddit` | string | — | Scope search to a single subreddit. Leave empty to search all of Reddit | | `subreddits` | string\[] | `[]` | Search across multiple subreddits. Results are merged and deduplicated | | `autoDiscoverSubreddits` | boolean | `true` | Auto-find relevant subreddits when none specified | | `maxSubreddits` | integer | `20` | Max subreddits to auto-discover (1-50) | #### Sort order reference | Value | Behavior | |-------|----------| | `relevance` | Reddit's default. Balances keyword match quality with engagement signals | | `new` | Most recent results first, regardless of score | | `top` | Highest score (upvotes minus downvotes) | | `hot` | Currently trending content. Balances recency and engagement. Posts only | | `comments` | Most commented results first. Posts only | #### Time filter reference | Value | Window | |-------|--------| | `hour` | Past 60 minutes | | `day` | Past 24 hours | | `week` | Past 7 days | | `month` | Past 30 days | | `year` | Past 365 days | | *(empty)* | All time (default) | #### Subreddit input formats All of these are equivalent and can be mixed in the same `subreddits` array: - `python` - `r/python` - `/r/python` - `https://reddit.com/r/python` - `https://www.reddit.com/r/python` - `https://old.reddit.com/r/python` #### Search query syntax The `query` field supports Reddit's full search syntax, including boolean operators and exact phrase matching. Maximum query length is 700 characters. | Syntax | Example | Behavior | |--------|---------|----------| | Keywords | `python web scraping` | Matches any of the keywords | | Exact phrase | `"web scraping"` | Matches the exact phrase | | OR | `"flask" OR "django"` | Matches either term | | AND | `"python" AND "scraping"` | Both terms must appear | | Grouped | `("flask" OR "django") AND "REST API"` | Combine operators with parentheses | You can build complex queries by combining these operators: ``` ("best tool" OR "recommend" OR "alternative to") AND ("project management" OR "task tracking") ``` ### What Data Can You Extract? ![Output Example](https://iili.io/BIPPgyv.gif) The output contains two row types depending on your `contentType` setting: **post** rows and **comment** rows. Each row includes a `_type` field so you can distinguish them when using `both` mode. #### Post row (20 fields) ```json { "_type": "post", "_status": "found", "id": "t3_1abc", "title": "Python web scraping in 2026", "author": "dev123", "subreddit": "python", "score": 542, "commentCount": 89, "upvoteRatio": 0.95, "createdAt": "2026-04-04T12:00:00Z", "editedAt": null, "permalink": "/r/python/comments/1abc/python_web_scraping_in_2026/", "url": "https://www.reddit.com/r/python/comments/1abc/python_web_scraping_in_2026/", "body": "I've been experimenting with different scraping libraries...", "domain": "self.python", "isSelfPost": true, "isNsfw": false, "isSpoiler": false, "isLocked": false, "isStickied": false, "isArchived": false, "flair": "Discussion", "thumbnail": null } ``` **Post fields (20+):** `id`, `title`, `author`, `subreddit`, `score`, `commentCount`, `upvoteRatio`, `createdAt`, `editedAt`, `permalink`, `url`, `body`, `domain`, `isSelfPost`, `isNsfw`, `isSpoiler`, `isLocked`, `isStickied`, `isArchived`, `flair`, `thumbnail` #### Comment row (13 fields) ```json { "_type": "comment", "_status": "found", "id": "t1_xyz789", "author": "commenter42", "subreddit": "python", "score": 42, "createdAt": "2026-04-04T13:00:00Z", "editedAt": null, "permalink": "/r/python/comments/1abc/comment/xyz789/", "body": "Great tutorial, I've been looking for something like this.", "isScoreHidden": false, "isOP": false, "postId": "t3_1abc", "postTitle": "Python web scraping in 2026", "postUrl": "https://www.reddit.com/r/python/comments/1abc/python_web_scraping_in_2026/" } ``` **Comment fields (13):** `id`, `author`, `subreddit`, `score`, `createdAt`, `editedAt`, `permalink`, `body`, `isScoreHidden`, `isOP`, `postId`, `postTitle`, `postUrl` ### Pricing - Pay Per Event (PPE)
$0.99 per 1,000 results
You pay only for what you scrape. Each result (post or comment) counts as one `result-scraped` event. **Budget controls:** Set a spending limit on any run from the Apify Console. The actor stops automatically when the budget is reached, and you keep all data scraped up to that point. ### Use Cases **Brand monitoring.** Search for your company or product name across all of Reddit. Use `sort: "new"` to catch mentions as they appear. Schedule daily or hourly runs to build a continuous feed of brand mentions with scores, timestamps, and subreddit context. **Market research.** Search keywords related to your industry to understand what real users discuss, recommend, and complain about. The `score` and `commentCount` fields reveal which topics generate the most engagement. Scope to relevant subreddits for focused insights. **Content research.** Find top-performing discussions on any topic. Use `sort: "top"` with `timeFilter: "month"` to surface the highest-scoring content from the past 30 days. The `body` field gives you the full text, and `upvoteRatio` tells you how universally the community agrees. **Competitor analysis.** Search competitor names and products to see what customers say on Reddit. Compare engagement metrics across different brands. The `subreddit` field reveals which communities discuss each competitor most. **Sentiment analysis.** Pull thousands of comments mentioning a topic and feed them into your NLP pipeline. Each row includes the full text, score, and metadata needed for downstream analysis. Use time filters to segment sentiment by period. **Lead generation.** Monitor subreddits where your target audience asks for recommendations. Search for phrases like "looking for", "best tool for", or "alternative to" to find high-intent posts. Export to your CRM or outreach tool via Apify integrations. **Academic research.** Build datasets of public Reddit discussions on any topic. The structured output with timestamps, scores, and subreddit metadata supports quantitative analysis of online discourse, community dynamics, and information spread. **SEO and content strategy.** Analyze which questions and topics generate engagement in your niche. Use comment search to find the specific advice and recommendations that get upvoted. Map these insights back to your content calendar. ### FAQ **How many results can I get per run?** No hard limit. Set `maxResults` to 0 for unlimited. With auto-discovery across 20+ subreddits, a single keyword can return thousands of results. The actual count depends on how many matching posts/comments exist in the discovered subreddits. **What's the difference between searching posts and comments?** Post search matches against post titles and body text. Comment search matches against comment text. Use `contentType: "both"` to search both simultaneously. Each type is returned as separate rows with a `_type` field. **How does multi-subreddit search work?** When you provide multiple subreddits, the actor searches each one in parallel. Results are merged into a single dataset. Each row includes a `subreddit` field so you can filter or group by community. **What subreddit formats are accepted?** Plain name (`python`), prefixed (`r/python`), full URL (`https://reddit.com/r/python`), old/new/mobile URLs, and any combination in the same input. The actor normalizes everything before searching. **Can I search all of Reddit at once?** Yes. Leave both `subreddit` and `subreddits` empty, and the actor searches across all public subreddits. **How do time filters work?** Time filters restrict results to a specific window: past hour, day, week, month, or year. Leave empty to search all time. Time filters work with all sort orders. **What happens if I search a subreddit that doesn't exist?** The actor skips it and continues with the remaining subreddits. You are not charged for failed searches. **What does the `_status` field mean?** `"found"` means the result was successfully scraped. This field is consistent across all actors in the Clearpath Reddit Suite, so you can build pipelines that handle status uniformly. **How does "both" mode split the results?** When `contentType` is `"both"`, the actor runs post search and comment search in parallel. Each type gets up to `maxResults` results independently. The total output can be up to twice `maxResults`. **Can I use boolean operators in the search query?** Yes. The query supports AND, OR, quoted phrases for exact matching, and parentheses for grouping. For example: `("flask" OR "django") AND "REST API"`. Maximum query length is 700 characters. **What sort orders work for comments?** `relevance`, `new`, and `top` work for both posts and comments. `hot` and `comments` (most comments) apply only to post search. **Can I schedule recurring searches?** Yes. Set up a schedule in the Apify Console to run the actor at any interval. Combine with `sort: "new"` and a time filter to build a continuous monitoring pipeline without duplicate results. **What output formats are available?** The Apify Console lets you download results as JSON, CSV, Excel, XML, or RSS. You can also access the dataset via the Apify API in any of these formats. **How does this compare to the Subreddit Posts Scraper?** This actor searches by keyword across Reddit. The [Subreddit Posts Scraper](https://apify.com/clearpath/reddit-subreddit-posts-scraper) scrapes a subreddit's feed (hot, new, top, rising, controversial) without a keyword filter. Use this actor when you need to find specific content. Use the Subreddit Posts Scraper when you want everything from a subreddit's feed. **How does this compare to the Post & Comments Scraper?** This actor finds posts and comments by keyword. The [Post & Comments Scraper](https://apify.com/clearpath/reddit-post-comments-bulk-scraper) starts from specific post URLs and extracts full comment trees with nested replies. Use this actor for discovery, and the other for deep extraction of known threads. ### Support - **Bugs**: Issues tab - **Features**: Email or issues - **Email**: max@mapa.slmail.me ### Legal Compliance Extracts publicly available data. Users must comply with Reddit terms and data protection regulations (GDPR, CCPA). *** # Actor input Schema ## `query` (type: `string`): Keywords to search for (max 700 characters). Supports quoted phrases like "machine learning" and boolean operators like ("python" OR "javascript") AND "web scraping". ## `maxResults` (type: `integer`): Maximum number of results to return. Set to 0 for unlimited. With auto-discovery across 20+ subreddits, a single keyword can return thousands of results. ## `contentType` (type: `string`): Search for posts, comments, or both. Posts include title, body, score, and subreddit. Comments include the reply text and parent post context. ## `sort` (type: `string`): Most relevant = best keyword match. Top = highest scored. Newest = most recent first. Hot and Most comments apply to posts only. ## `timeFilter` (type: `string`): Only include results posted within the selected time range. ## `subreddit` (type: `string`): Scope to a single subreddit. Leave empty to auto-discover relevant subreddits for your query. Accepts python, r/python, or full URLs. ## `subreddits` (type: `array`): Search across specific subreddits in parallel. When provided, auto-discovery is skipped. ## `autoDiscoverSubreddits` (type: `boolean`): When no subreddit is specified, automatically find the most relevant communities for your query and search across them. Disable for a single global search (capped at ~300 results). ## `maxSubreddits` (type: `integer`): How many subreddits to auto-discover. More = more results, slower run. ## Actor input object example ```json { "query": "best CRM for startups", "maxResults": 100, "contentType": "posts", "sort": "relevance", "timeFilter": "", "subreddits": [], "autoDiscoverSubreddits": true, "maxSubreddits": 20 } ``` # Actor output Schema ## `results` (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 = { "query": "best CRM for startups" }; // Run the Actor and wait for it to finish const run = await client.actor("clearpath/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 = { "query": "best CRM for startups" } # Run the Actor and wait for it to finish run = client.actor("clearpath/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 '{ "query": "best CRM for startups" }' | apify call clearpath/reddit-search-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=clearpath/reddit-search-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Reddit Search Scraper - 3,000+ Results in 10 Seconds", "description": "Search Reddit posts and comments by keyword. 3,000+ results in seconds with smart subreddit auto-discovery. Titles, bodies, scores, authors, timestamps, permalinks. 5 sort orders, time filters. Scope to specific subreddits or let it find them for you.", "version": "0.0", "x-build-id": "DSL5uk01COzYwKV1K" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/clearpath~reddit-search-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-clearpath-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/clearpath~reddit-search-scraper/runs": { "post": { "operationId": "runs-sync-clearpath-reddit-search-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/clearpath~reddit-search-scraper/run-sync": { "post": { "operationId": "run-sync-clearpath-reddit-search-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "query" ], "properties": { "query": { "title": "Search query", "maxLength": 700, "type": "string", "description": "Keywords to search for (max 700 characters). Supports quoted phrases like \"machine learning\" and boolean operators like (\"python\" OR \"javascript\") AND \"web scraping\"." }, "maxResults": { "title": "Max results", "minimum": 0, "type": "integer", "description": "Maximum number of results to return. Set to 0 for unlimited. With auto-discovery across 20+ subreddits, a single keyword can return thousands of results.", "default": 100 }, "contentType": { "title": "Content type", "enum": [ "posts", "comments", "both" ], "type": "string", "description": "Search for posts, comments, or both. Posts include title, body, score, and subreddit. Comments include the reply text and parent post context.", "default": "posts" }, "sort": { "title": "Sort order", "enum": [ "relevance", "new", "top", "hot", "comments" ], "type": "string", "description": "Most relevant = best keyword match. Top = highest scored. Newest = most recent first. Hot and Most comments apply to posts only.", "default": "relevance" }, "timeFilter": { "title": "Time filter", "enum": [ "", "hour", "day", "week", "month", "year" ], "type": "string", "description": "Only include results posted within the selected time range.", "default": "" }, "subreddit": { "title": "Subreddit", "type": "string", "description": "Scope to a single subreddit. Leave empty to auto-discover relevant subreddits for your query. Accepts python, r/python, or full URLs." }, "subreddits": { "title": "Multiple subreddits", "type": "array", "description": "Search across specific subreddits in parallel. When provided, auto-discovery is skipped.", "items": { "type": "string" }, "default": [] }, "autoDiscoverSubreddits": { "title": "Auto-discover subreddits", "type": "boolean", "description": "When no subreddit is specified, automatically find the most relevant communities for your query and search across them. Disable for a single global search (capped at ~300 results).", "default": true }, "maxSubreddits": { "title": "Max subreddits to discover", "minimum": 1, "maximum": 50, "type": "integer", "description": "How many subreddits to auto-discover. More = more results, slower run.", "default": 20 } } }, "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 } } } } } } } } } } ```