# LinkedIn Post Search Scraper (`crawlerbros/linkedin-post-search-scraper`) Actor Search LinkedIn for posts by keyword, topic, or hashtag. Filter by date posted and sort by relevance or recency. - **URL**: https://apify.com/crawlerbros/linkedin-post-search-scraper.md - **Developed by:** [Crawler Bros](https://apify.com/crawlerbros) (community) - **Categories:** Social media, Lead generation, Automation - **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $3.00 / 1,000 results This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. 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 ## LinkedIn Post Search Scraper Search LinkedIn for posts by keyword, topic, or hashtag using the LinkedIn Voyager API (HTTP-only — no browser required). Returns matching posts with full content, author details, and engagement metrics. Supports filtering by date posted and sorting by relevance or recency. --- ### What It Does - Searches LinkedIn posts using any keyword, phrase, or hashtag - Returns post content, author name, headline, profile URL, and post URL - Includes engagement metrics: reactions count and comments count - Filters by date posted: past 24 hours, past week, past month, or any time - Sorts by most relevant or most recent - Deduplicates results automatically - Requires a valid LinkedIn session cookie (`li_at`) --- ### Input | Field | Type | Required | Description | |---|---|---|---| | `searchQuery` | String | Yes | Keywords, phrase, or hashtag to search. E.g. `artificial intelligence`, `#MachineLearning`, `product launch` | | `cookie` | String | Yes | LinkedIn session cookie. Accepts plain `li_at` value or full browser cookies JSON array | | `sortBy` | Select | No | `relevance` (default) or `recency` | | `datePosted` | Select | No | `""` Any time (default), `r86400` Past 24h, `r604800` Past week, `r2592000` Past month | | `maxResults` | Integer | No | Max posts to return. Default: 25, max: 100 | | `proxyConfiguration` | Object | No | Apify proxy configuration. Defaults to residential then datacenter AUTO | --- ### Output Each item in the dataset represents one LinkedIn post: | Field | Type | Description | |---|---|---| | `postId` | String | Numeric LinkedIn activity ID | | `postUrl` | String | Direct URL to the post | | `authorName` | String | Display name of the post author | | `authorProfileUrl` | String | Author's LinkedIn profile URL | | `authorHeadline` | String | Author's headline (job title, company, location) | | `postedAt` | String | When the post was published (e.g. "1 day ago", "2 weeks ago") | | `content` | String | Post text content (may be truncated for long posts) | | `mediaType` | String | Always `text` for search results (detailed media info not available via search API) | | `reactionsCount` | Integer | Number of reactions on the post | | `commentsCount` | Integer | Number of comments on the post | | `scrapedAt` | String | ISO 8601 UTC timestamp when the record was collected | #### Example Output ```json { "postId": "7329761432933134337", "postUrl": "https://www.linkedin.com/feed/update/urn:li:activity:7329761432933134337/", "authorName": "Jane Doe", "authorProfileUrl": "https://www.linkedin.com/in/janedoe/", "authorHeadline": "Senior AI Engineer at Acme Corp | San Francisco", "postedAt": "1 day ago", "content": "Excited to share that we just launched our new AI-powered product! After 18 months of development...", "mediaType": "text", "reactionsCount": 347, "commentsCount": 42, "scrapedAt": "2026-06-08T12:34:56.789000+00:00" } ```` *** ### Cookie Setup Guide LinkedIn requires authentication to access search results. You need to provide your `li_at` session cookie. #### Option 1: Plain `li_at` value (simplest) 1. Open [linkedin.com](https://www.linkedin.com) in your browser and log in 2. Open **DevTools** (`F12` or right-click → Inspect) 3. Go to **Application** → **Cookies** → `https://www.linkedin.com` 4. Find the cookie named `li_at` 5. Copy the **Value** and paste it into the `cookie` input field #### Option 2: Full browser cookies JSON array 1. Install a browser extension like [EditThisCookie](https://www.editthiscookie.com/) or [Cookie-Editor](https://cookie-editor.com/) 2. Log into LinkedIn 3. Export all cookies as JSON from the extension 4. Paste the full JSON array into the `cookie` input field > **Note**: Your cookie is used only for authentication with LinkedIn's API. Never share it publicly. Cookies typically expire after 1 year or when you log out of LinkedIn. *** ### Keyword Search vs Hashtag Search | Search Type | Example Input | What It Finds | |---|---|---| | Keyword phrase | `artificial intelligence` | Posts mentioning the exact phrase or related terms | | Single keyword | `startup` | Posts containing the word startup | | Hashtag | `#MachineLearning` | Posts tagged with that hashtag | | Multi-word | `product launch announcement` | Posts about product launches | | Person mention | `Elon Musk Tesla` | Posts mentioning Elon Musk in context of Tesla | *** ### Sort and Filter Combinations | `sortBy` | `datePosted` | What You Get | |---|---|---| | `relevance` | (empty) | Most relevant posts of all time | | `relevance` | `r86400` | Most relevant posts from last 24 hours | | `recency` | (empty) | Newest posts first, no date filter | | `recency` | `r86400` | Most recent posts from last 24 hours | | `recency` | `r604800` | Most recent posts from last week | | `recency` | `r2592000` | Most recent posts from last month | *** ### FAQs **How many posts can I scrape per run?** Up to 100 posts per run (set via `maxResults`). LinkedIn's search API returns results in pages of 10. **Why are some engagement counts zero?** LinkedIn's search API does not always return engagement data in search result previews. When the `socialProofText` field is absent from the result, counts default to 0. Use the [LinkedIn Post Scraper](https://apify.com/crawlerbros/linkedin-post-scraper) actor to get full engagement data for specific posts. **Why is post content sometimes truncated?** Search results return a content snippet, not the full post text. Long posts are cut off by LinkedIn's search API. To retrieve the full text, visit the post URL directly. **What causes rate limiting?** LinkedIn throttles search requests. The actor automatically adds delays between requests (2–5 seconds) and retries on 429 responses. If you need to scrape large volumes, increase the delay by reducing `maxResults` and running multiple actors. **Do I need a proxy?** A proxy is recommended but not required. The actor first tries a residential proxy (best for LinkedIn), then falls back to datacenter proxy, then direct connection. You can also supply a custom `proxyConfiguration`. **Why does the actor fail with "cookie is invalid or expired"?** Your `li_at` cookie has expired or LinkedIn invalidated the session. Log out and back into LinkedIn, then copy the fresh `li_at` value. **Can I search posts in other languages?** Yes. Enter your search query in any language. LinkedIn returns results in the language of the posts matching your query. **Is logging in or a paid LinkedIn account required?** No paid subscription is required. Any standard LinkedIn account works. The `li_at` session cookie from a free account is sufficient. ### Explore the rest of the LinkedIn suite Need a different LinkedIn surface? Pair this actor with any of the others in the LinkedIn Suite — all published under the same publisher and built to share the same cookie format and output conventions. | Actor | What it scrapes | |---|---| | [LinkedIn Comments Scraper](https://apify.com/crawlerbros/linkedin-comments-scraper) | All comments + reply threads on a post | | [LinkedIn Company Employees Scraper](https://apify.com/crawlerbros/linkedin-company-employees-scraper) | Employee list for any company (by URN) | | [LinkedIn Company Info Scraper](https://apify.com/crawlerbros/linkedin-company-info-scraper) | Company About page (size, HQ, industry, specialties) | | [LinkedIn Company Posts Scraper](https://apify.com/crawlerbros/linkedin-company-posts-scraper) | Posts published from a company page | | [LinkedIn Events Scraper](https://apify.com/crawlerbros/linkedin-events-scraper) | Events by keyword/URL with full event detail | | [LinkedIn Hashtag Posts Scraper](https://apify.com/crawlerbros/linkedin-hashtag-posts-scraper) | Posts ranked under a `#hashtag` | | [LinkedIn Jobs Scraper](https://apify.com/crawlerbros/linkedin-jobs-scraper) | Job listings via the public jobs-guest API | | [LinkedIn Jobs Scraper Ultra](https://apify.com/crawlerbros/linkedin-jobs-scraper-ultra) | Same as jobs-scraper + full detail enrichment | | [LinkedIn Learning Courses Scraper](https://apify.com/crawlerbros/linkedin-learning-courses-scraper) | LinkedIn Learning course catalog by keyword | | [LinkedIn People Search Scraper](https://apify.com/crawlerbros/linkedin-people-search-scraper) | People search with every LinkedIn facet (role, company, school, location, etc.) | | [LinkedIn Post Reactions Scraper](https://apify.com/crawlerbros/linkedin-post-reactions-scraper) | Reactors on a post (name, headline, reaction type) | | [LinkedIn Post Scraper](https://apify.com/crawlerbros/linkedin-post-scraper) | Full post (text, media, engagement counts, author) | | [LinkedIn Profile Posts Scraper](https://apify.com/crawlerbros/linkedin-profile-posts-scraper) | All posts/reposts/articles for one profile | | [LinkedIn Profile Scraper](https://apify.com/crawlerbros/linkedin-profile-scraper) | Public profile fields (name, headline, positions, education, skills) | | [LinkedIn Profile Scraper Pro](https://apify.com/crawlerbros/linkedin-profile-scraper-pro) | Profile fields + extras (recommendations, organizations, languages) | | [LinkedIn Profile Scraper Pro Ultra](https://apify.com/crawlerbros/linkedin-profile-scraper-pro-ultra) | Pro + premium fields (contact info, followers list when allowed) | | [LinkedIn Profile Scraper Ultra](https://apify.com/crawlerbros/linkedin-profile-scraper-ultra) | Profile + the full upstream dash-120 surface | | [LinkedIn Profile Search by Name](https://apify.com/crawlerbros/linkedin-profile-search-by-name) | Search profiles by person name (great for matching CSVs of names) | | [LinkedIn Schools Alumni Scraper](https://apify.com/crawlerbros/linkedin-schools-alumni-scraper) | Alumni list for any LinkedIn school page | | [LinkedIn Top Content Scraper](https://apify.com/crawlerbros/linkedin-top-content-scraper) | Trending / top-engagement posts by topic | | [LinkedIn User Activity Scraper](https://apify.com/crawlerbros/linkedin-user-activity-scraper) | Reactions + comments + posts feed for one profile | All actors share the same `cookie` input format (plain `li_at` OR full cookies JSON array) and the same omit-empty output convention. # Actor input Schema ## `searchQuery` (type: `string`): Keywords or hashtag to search for. Examples: 'artificial intelligence', '#MachineLearning', 'product launch announcement' ## `cookie` (type: `string`): Your LinkedIn session cookie. Accepts either: (1) the li\_at value from browser DevTools → Application → Cookies, or (2) full cookies JSON array exported from an extension like EditThisCookie. ## `sortBy` (type: `string`): How to sort search results. 'recency' and 'date\_posted' are aliases — both sort by most recent posts first. ## `datePosted` (type: `string`): Filter posts by how recently they were posted. ## `authorType` (type: `string`): Restrict results to posts authored by a person or by a company. Leave blank for both. ## `contentType` (type: `array`): Select which post media types to include. Valid values: articles, posts, documents, videos, images. ## `language` (type: `string`): Preferred result language. Non-English values also disable LinkedIn's spell-correction rewriting. ## `maxResults` (type: `integer`): Maximum number of posts to return. ## `fromNetwork` (type: `string`): Filter posts by your LinkedIn connection degree. Leave blank for any. 'F' = 1st-degree, 'S' = 2nd-degree, 'O' = 3rd-degree and beyond. ## `industries` (type: `array`): Filter posts by industry. Select one or more industries. ## `mentions` (type: `array`): Filter posts mentioning specific companies or people. Provide LinkedIn handles or display names (e.g. 'OpenAI', 'Satya Nadella'). These are appended to the search query. ## `mentionsCompany` (type: `string`): Restrict results to posts that @-mention a specific company. Accepts a numeric LinkedIn company ID (e.g. '1441') or a company slug (e.g. 'google'). Slugs are resolved server-side; numeric IDs are passed through to the LinkedIn filter chain. ## `mentionsPerson` (type: `string`): Restrict results to posts that @-mention a specific person. Accepts a numeric LinkedIn member ID or a profile slug (e.g. 'satyanadella'). ## `minReactions` (type: `integer`): Only emit posts with at least this many reactions. Set to 0 to include all. ## `excludeReposts` (type: `boolean`): When enabled, skip posts that are reshares of someone else's content. ## `emitNoResultsMarker` (type: `boolean`): When enabled and the search yields zero results (with no errors), push a single structured marker record ({searchQuery, noResults: true, scrapedAt}) so callers can distinguish 'no matches' from 'scrape failed'. ## `talksAbout` (type: `array`): Filter posts that discuss specific topics or hashtags. Values are appended with '#' to the search query (e.g. 'AI' becomes '#AI'). You may also enter them with a leading '#'. ## `proxyConfiguration` (type: `object`): Optional Apify proxy configuration. ## Actor input object example ```json { "searchQuery": "artificial intelligence", "sortBy": "relevance", "datePosted": "", "authorType": "", "contentType": [ "articles", "posts", "documents", "videos", "images" ], "language": "en", "maxResults": 25, "fromNetwork": "", "industries": [], "mentions": [], "mentionsCompany": "", "mentionsPerson": "", "minReactions": 0, "excludeReposts": false, "emitNoResultsMarker": true, "talksAbout": [] } ``` # 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 = { "searchQuery": "artificial intelligence", "sortBy": "relevance", "datePosted": "", "authorType": "", "contentType": [ "articles", "posts", "documents", "videos", "images" ], "language": "en", "maxResults": 25, "fromNetwork": "", "industries": [], "mentions": [], "mentionsCompany": "", "mentionsPerson": "", "minReactions": 0, "excludeReposts": false, "emitNoResultsMarker": true, "talksAbout": [] }; // Run the Actor and wait for it to finish const run = await client.actor("crawlerbros/linkedin-post-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 = { "searchQuery": "artificial intelligence", "sortBy": "relevance", "datePosted": "", "authorType": "", "contentType": [ "articles", "posts", "documents", "videos", "images", ], "language": "en", "maxResults": 25, "fromNetwork": "", "industries": [], "mentions": [], "mentionsCompany": "", "mentionsPerson": "", "minReactions": 0, "excludeReposts": False, "emitNoResultsMarker": True, "talksAbout": [], } # Run the Actor and wait for it to finish run = client.actor("crawlerbros/linkedin-post-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 '{ "searchQuery": "artificial intelligence", "sortBy": "relevance", "datePosted": "", "authorType": "", "contentType": [ "articles", "posts", "documents", "videos", "images" ], "language": "en", "maxResults": 25, "fromNetwork": "", "industries": [], "mentions": [], "mentionsCompany": "", "mentionsPerson": "", "minReactions": 0, "excludeReposts": false, "emitNoResultsMarker": true, "talksAbout": [] }' | apify call crawlerbros/linkedin-post-search-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=crawlerbros/linkedin-post-search-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "LinkedIn Post Search Scraper", "description": "Search LinkedIn for posts by keyword, topic, or hashtag. Filter by date posted and sort by relevance or recency.", "version": "1.35", "x-build-id": "diQ02ewtFzXw4hv5J" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/crawlerbros~linkedin-post-search-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-crawlerbros-linkedin-post-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/crawlerbros~linkedin-post-search-scraper/runs": { "post": { "operationId": "runs-sync-crawlerbros-linkedin-post-search-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/crawlerbros~linkedin-post-search-scraper/run-sync": { "post": { "operationId": "run-sync-crawlerbros-linkedin-post-search-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "searchQuery", "cookie" ], "properties": { "searchQuery": { "title": "Search Query", "type": "string", "description": "Keywords or hashtag to search for. Examples: 'artificial intelligence', '#MachineLearning', 'product launch announcement'" }, "cookie": { "title": "LinkedIn Cookie", "type": "string", "description": "Your LinkedIn session cookie. Accepts either: (1) the li_at value from browser DevTools → Application → Cookies, or (2) full cookies JSON array exported from an extension like EditThisCookie." }, "sortBy": { "title": "Sort By", "enum": [ "relevance", "recency", "date_posted" ], "type": "string", "description": "How to sort search results. 'recency' and 'date_posted' are aliases — both sort by most recent posts first.", "default": "relevance" }, "datePosted": { "title": "Date Posted", "enum": [ "", "r86400", "r604800", "r2592000" ], "type": "string", "description": "Filter posts by how recently they were posted.", "default": "" }, "authorType": { "title": "Author Type", "enum": [ "", "PERSON", "COMPANY" ], "type": "string", "description": "Restrict results to posts authored by a person or by a company. Leave blank for both.", "default": "" }, "contentType": { "title": "Content Types", "type": "array", "description": "Select which post media types to include. Valid values: articles, posts, documents, videos, images.", "default": [ "articles", "posts", "documents", "videos", "images" ], "items": { "type": "string" } }, "language": { "title": "Language", "enum": [ "en", "es", "fr", "de", "pt", "it" ], "type": "string", "description": "Preferred result language. Non-English values also disable LinkedIn's spell-correction rewriting.", "default": "en" }, "maxResults": { "title": "Max Results", "minimum": 1, "maximum": 100, "type": "integer", "description": "Maximum number of posts to return.", "default": 25 }, "fromNetwork": { "title": "From Network", "enum": [ "", "F", "S", "O" ], "type": "string", "description": "Filter posts by your LinkedIn connection degree. Leave blank for any. 'F' = 1st-degree, 'S' = 2nd-degree, 'O' = 3rd-degree and beyond.", "default": "" }, "industries": { "title": "Industries", "type": "array", "description": "Filter posts by industry. Select one or more industries.", "items": { "type": "string", "enum": [ "Software Development", "Financial Services", "Healthcare", "Education", "Marketing & Advertising", "Consulting", "Retail", "Manufacturing", "Legal Services", "Real Estate" ], "enumTitles": [ "Software Development", "Financial Services", "Healthcare", "Education", "Marketing & Advertising", "Consulting", "Retail", "Manufacturing", "Legal Services", "Real Estate" ] }, "default": [] }, "mentions": { "title": "Mentions", "type": "array", "description": "Filter posts mentioning specific companies or people. Provide LinkedIn handles or display names (e.g. 'OpenAI', 'Satya Nadella'). These are appended to the search query.", "default": [], "items": { "type": "string" } }, "mentionsCompany": { "title": "Mentions Company", "type": "string", "description": "Restrict results to posts that @-mention a specific company. Accepts a numeric LinkedIn company ID (e.g. '1441') or a company slug (e.g. 'google'). Slugs are resolved server-side; numeric IDs are passed through to the LinkedIn filter chain.", "default": "" }, "mentionsPerson": { "title": "Mentions Person", "type": "string", "description": "Restrict results to posts that @-mention a specific person. Accepts a numeric LinkedIn member ID or a profile slug (e.g. 'satyanadella').", "default": "" }, "minReactions": { "title": "Minimum Reactions", "minimum": 0, "maximum": 1000000, "type": "integer", "description": "Only emit posts with at least this many reactions. Set to 0 to include all.", "default": 0 }, "excludeReposts": { "title": "Exclude Reposts", "type": "boolean", "description": "When enabled, skip posts that are reshares of someone else's content.", "default": false }, "emitNoResultsMarker": { "title": "Emit No-Results Marker", "type": "boolean", "description": "When enabled and the search yields zero results (with no errors), push a single structured marker record ({searchQuery, noResults: true, scrapedAt}) so callers can distinguish 'no matches' from 'scrape failed'.", "default": true }, "talksAbout": { "title": "Talks About (Topics / Hashtags)", "type": "array", "description": "Filter posts that discuss specific topics or hashtags. Values are appended with '#' to the search query (e.g. 'AI' becomes '#AI'). You may also enter them with a leading '#'.", "default": [], "items": { "type": "string" } }, "proxyConfiguration": { "title": "Proxy Configuration", "type": "object", "description": "Optional Apify proxy configuration." } } }, "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 } } } } } } } } } } ```