# LinkedIn Posts Scraper (`calm_builder/linkedin-posts-scraper`) Actor Extract structured data from public LinkedIn post URLs. Collect post text, author, publish date, reaction and comment counts, visible comments, reaction types, and media (images, video, carousels, documents) — ideal for social listening, content research, competitor monitoring, and lead enrichment. - **URL**: https://apify.com/calm\_builder/linkedin-posts-scraper.md - **Developed by:** [Coder](https://apify.com/calm_builder) (community) - **Categories:** Social media, Lead generation, Automation - **Stats:** 5 total users, 4 monthly users, 92.3% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.50 / 1,000 post scrapeds 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 ## LinkedIn Posts Scraper Collect structured data from public [LinkedIn](https://www.linkedin.com) **post** pages using direct post URLs. Add one or more links, start a run, and receive clean JSON records in your Apify dataset — no LinkedIn login required. Use it for **social listening**, **content research**, **competitor monitoring**, **influencer analysis**, **lead enrichment**, and **marketing intelligence** — without copying posts manually. --- ### What you get Each saved row is **one LinkedIn post**, organized into clear sections: | Section | What it contains | | -------------- | --------------------------------------------------------------------------------------------- | | **Links** | The URL you provided (`inputUrl`) and the canonical post link (`postUrl`) | | **Content** | Post text, headline, and publication timestamp when available | | **Author** | Author name, profile or company link, type (`person` or `organization`), and image when shown | | **Engagement** | Reaction count, comment count, and reaction types when shown | | **`comments`** | Visible comments with author name and text when LinkedIn exposes them on the public page | | **`postType`** | Content type — for example `text`, `image`, `video`, `carousel`, or `document` | | **`media`** | Images, video sources, or other media when present | Results are saved to the dataset **as each post is processed**, so you can preview progress before the run finishes. --- ### Quick start on Apify 1. Open the Actor in the Apify Console. 2. Under **LinkedIn post URLs**, add one or more public post links (one per line). 3. Click **Start** and open the **Dataset** tab as posts are saved. **Supported input formats:** - Activity post: `https://www.linkedin.com/posts/apify_pyconsg-activity-7475096162006646784-txwr/` - UGC post: `https://www.linkedin.com/posts/jancurn_its-always-great-to-be-back-in-san-francisco-ugcPost-7477224335636680704-LH9L/` - Company post: `https://www.linkedin.com/posts/apify_two-brothers-scraped-10000-french-bakeries-activity-7477345241553936384-aWdh/` Tracking parameters in the URL (for example `utm_source`) are ignored. The Actor uses the canonical post address. **Example input:** ```json { "postUrls": [ "https://www.linkedin.com/posts/apify_pyconsg-activity-7475096162006646784-txwr/", "https://www.linkedin.com/posts/jancurn_its-always-great-to-be-back-in-san-francisco-ugcPost-7477224335636680704-LH9L/", "https://www.linkedin.com/posts/charlie-hills_claude-has-375-native-mcp-connectors-how-activity-7473675973541044225-8oQk" ] } ```` *** ### Input parameters #### LinkedIn post URLs | | | | ------------ | ----------------------------------------------------------- | | **Field** | `postUrls` | | **Type** | List of text entries (one URL per line) | | **Required** | Yes — at least one entry | | **Formats** | Standard LinkedIn post page URLs (`linkedin.com/posts/...`) | Invalid entries that cannot be recognized as a LinkedIn post URL are skipped with a warning. Duplicate URLs in the same run are still processed as separate inputs if listed more than once. *** ### What you will see during a run The run log is written for end users — messages describe collection progress only. Typical messages: - `Starting collection for N post(s).` - `Progress: 5 post(s) saved.` - `Could not retrieve: https://www.linkedin.com/posts/...` *(when a single post fails)* - `Run complete. Saved N post(s).` - `Run complete. Saved X of Y post(s). Z could not be retrieved.` *(when some posts fail)* If one post cannot be retrieved, other posts in the same run can still succeed. On the Apify **free plan**, you may also see a notice when free-tier limits apply (see [Free plan limits](#free-plan-limits)). *** ### Output overview #### Dataset structure - Results are saved to a **single Apify dataset** - Each row is **one post object** - Only **successfully scraped** posts appear in the dataset — posts that could not be retrieved are not included Field presence varies by post: not every post shows inline comments, reaction types, or full media on the public view. Missing sections are omitted from the output — not necessarily a scraper error. *** ### Output fields #### Links and content | Field | Description | | ------------- | -------------------------------------- | | `inputUrl` | The post URL as provided in your input | | `postUrl` | Canonical LinkedIn post link | | `text` | Post body text when available | | `headline` | Post headline or title line when shown | | `publishedAt` | ISO publish timestamp when available | #### Author | Field | Description | | ------------------- | -------------------------------------- | | `author.name` | Author display name | | `author.profileUrl` | LinkedIn profile or company page URL | | `author.type` | `person` or `organization` | | `author.imageUrl` | Author or company image URL when shown | #### Engagement | Field | Description | | --------------- | ------------------------------------------------------------------------------ | | `numLikes` | Total reaction count when shown | | `numComments` | Total comment count when shown | | `reactionTypes` | Reaction types displayed on the post (for example `LIKE`, `PRAISE`, `EMPATHY`) | #### `comments` (array) | Field | Description | | ------------- | ------------------------------------ | | `authorName` | Commenter name when shown | | `authorUrl` | Commenter profile URL when available | | `text` | Comment text | | `publishedAt` | Comment timestamp when available | #### Media | Field | Description | | -------------- | ----------------------------------------------------------------------------- | | `postType` | Content type — `text`, `image`, `video`, `carousel`, `document`, or `article` | | `media.images` | List of image URLs (and optional `alt` text when shown) | | `media.video` | Video sources and poster image when the post contains video | *** ### Example output The excerpts below come from a real run of public LinkedIn post URLs. Full output is available in the run dataset. #### Example input ```json { "postUrls": [ "https://www.linkedin.com/posts/apify_pyconsg-activity-7475096162006646784-txwr/", "https://www.linkedin.com/posts/jancurn_its-always-great-to-be-back-in-san-francisco-ugcPost-7477224335636680704-LH9L/", "https://www.linkedin.com/posts/apify_the-apify-team-is-heading-to-wearedevelopers-activity-7475503085436534784-8Fhp/" ] } ``` #### Excerpt — company carousel post with comments ```json { "inputUrl": "https://www.linkedin.com/posts/apify_pyconsg-activity-7475096162006646784-txwr/", "postUrl": "https://www.linkedin.com/posts/apify_pyconsg-activity-7475096162006646784-txwr/", "text": "At PyCon Singapore's PyLadies track, Kateřina Hroníková ran a hands-on workshop with a real output: a Women in Tech Inspiration Feed Actor...", "headline": "At PyCon Singapore's PyLadies track, Kateřina Hroníková ran a hands-on workshop with a real output: a Women in Tech Inspiration Feed Actor.", "publishedAt": "2026-06-23T08:03:25.574Z", "author": { "name": "Apify", "profileUrl": "https://cz.linkedin.com/company/apify", "type": "organization", "imageUrl": "https://media.licdn.com/dms/image/v2/D4D0BAQF7OnC-r1njIA/company-logo_100_100/..." }, "postType": "carousel", "media": { "images": [ { "url": "https://media.licdn.com/dms/image/v2/D4E10AQEomy8zWsZpUw/image-shrink_800/..." }, { "url": "https://media.licdn.com/dms/image/v2/D4E10AQH62KvFkG_w9A/image-shrink_800/..." }, { "url": "https://media.licdn.com/dms/image/v2/D4E10AQGtyi-2FsHutA/image-shrink_800/..." } ] }, "numLikes": 48, "numComments": 2, "reactionTypes": ["LIKE", "EMPATHY", "PRAISE"], "comments": [ { "authorName": "Saurav Jain", "text": "❤️❤️", "publishedAt": "2026-06-23T13:14:52.984Z" }, { "authorName": "Sandhu Singh", "text": "Hii", "publishedAt": "2026-06-23T09:08:57.768Z" } ] } ``` #### Excerpt — personal post with carousel images ```json { "inputUrl": "https://www.linkedin.com/posts/jancurn_its-always-great-to-be-back-in-san-francisco-ugcPost-7477224335636680704-LH9L/", "postUrl": "https://www.linkedin.com/posts/jancurn_its-always-great-to-be-back-in-san-francisco-activity-7477224336890912768-tZVV/", "text": "It’s always great to be back in San Francisco! With a strong crew from Apify, we’re heading to AI Engineer World's Fair next week...", "headline": "It’s always great to be back in San Francisco!", "publishedAt": "2026-06-29T05:00:02.001Z", "author": { "name": "Jan Čurn", "profileUrl": "https://www.linkedin.com/in/jancurn", "type": "person", "imageUrl": "https://media.licdn.com/dms/image/v2/D4E03AQGVYzvGHp9zhw/profile-displayphoto-shrink_400_400/..." }, "postType": "carousel", "media": { "images": [ { "url": "https://media.licdn.com/dms/image/v2/D4D22AQFnPIWsXxWMbQ/feedshare-shrink_800/..." }, { "url": "https://media.licdn.com/dms/image/v2/D4D22AQH_EAhX-Hdk0Q/feedshare-shrink_800/..." } ] }, "numLikes": 219, "numComments": 8, "reactionTypes": ["LIKE", "EMPATHY", "PRAISE"], "comments": [ { "authorName": "Saurav Jain", "text": "This sounds like a strong lineup. The “MCP doesn’t suck, your agent does” framing is especially interesting...", "publishedAt": "2026-06-29T12:45:44.581Z" }, { "authorName": "Petr Smid", "text": "Wow. Enjoy SF and with 1,000 people registered, be careful with the rooftop 😉", "publishedAt": "2026-06-29T09:08:05.825Z" } ] } ``` #### Excerpt — image post with engagement counts ```json { "inputUrl": "https://www.linkedin.com/posts/apify_the-apify-team-is-heading-to-wearedevelopers-activity-7475503085436534784-8Fhp/", "postUrl": "https://www.linkedin.com/posts/apify_the-apify-team-is-heading-to-wearedevelopers-activity-7475503085436534784-8Fhp/", "text": "The Apify team is heading to WeAreDevelopers World Congress in Berlin, July 9-10...", "headline": "The Apify team is heading to WeAreDevelopers World Congress in Berlin, July 9-10.", "publishedAt": "2026-06-24T11:00:23.683Z", "author": { "name": "Apify", "profileUrl": "https://cz.linkedin.com/company/apify", "type": "organization" }, "postType": "image", "media": { "images": [ { "url": "https://media.licdn.com/dms/image/v2/D4E10AQELPd6D6SBFBg/image-shrink_1280/..." } ] }, "numLikes": 27, "numComments": 2, "reactionTypes": ["LIKE", "PRAISE", "APPRECIATION"] } ``` #### Excerpt — high-engagement post with many visible comments ```json { "inputUrl": "https://www.linkedin.com/posts/charlie-hills_claude-has-375-native-mcp-connectors-how-activity-7473675973541044225-8oQk/", "postUrl": "https://www.linkedin.com/posts/charlie-hills_claude-has-375-native-mcp-connectors-how-activity-7473675973541044225-8oQk/", "text": "Claude has 375+ native MCP connectors. How to connect one in under 2 minutes...", "headline": "Claude has 375+ native MCP connectors.", "publishedAt": "2026-06-19T10:00:06.259Z", "author": { "name": "Charlie Hills 🦩", "profileUrl": "https://uk.linkedin.com/in/charlie-hills", "type": "person" }, "postType": "carousel", "numLikes": 1004, "numComments": 393, "reactionTypes": ["LIKE", "EMPATHY", "INTEREST"], "comments": [ { "authorName": "Sajad Hussain", "text": "100%. Feels like most people are just collecting connectors like Pokemon...", "publishedAt": "2026-06-19T12:08:18.065Z" }, { "authorName": "Brook Hinton", "text": "\"The connectors aren't the magic, chaining them is\" is the line that matters.", "publishedAt": "2026-06-19T10:07:14.648Z" } ] } ``` Posts that could not be retrieved do not appear in the dataset. Check the run log for a short message per failed URL. *** ### Pricing This Actor uses **pay-per-result** pricing. You are charged only for posts **successfully saved** to the dataset. | What you pay for | When it is charged | | ------------------- | ---------------------------------------- | | **Each saved post** | Once per post row written to the dataset | **Examples** (see the **Pricing** tab on the Store listing for current rates): | Run | What you pay for | | -------------------------- | ---------------- | | 50 post URLs, 48 succeed | 48 results | | 100 post URLs, all succeed | 100 results | | 20 post URLs, 5 fail | 15 results | Failed or skipped URLs are not saved and are not billed as results. *** ### Free plan limits On the Apify **free plan**, the Actor may automatically apply: | Limit | Value | | --------------------------- | ------------------------------------------- | | Post URLs processed per run | **5** (only the first entries in your list) | Additional URLs in the same run are not processed. Paid Apify plans can use the full input list without this cap. If limits apply, the run log will include a short notice. *** ### Public pages and data coverage **No LinkedIn login required**\ The Actor reads publicly visible post pages. It does not sign in to LinkedIn and does not use your account or cookies. **Guest view vs signed-in view**\ Results reflect what LinkedIn shows to visitors who are not logged in. Compared with what you see when signed in, output may include: - Fewer inline comments or partial comment threads - Reaction counts without a full list of who reacted - Missing media on some post types - Shorter or simplified post text on certain pages Coverage varies by post, author type, and LinkedIn's own visibility settings. **Post URL formats**\ Standard `linkedin.com/posts/...` links are supported, including activity, UGC, and share-style slugs. **High-traffic or restricted posts**\ Some posts may not be retrieved in a given run. Retrying later or processing URLs in a smaller batch can help in some cases. **Compliance**\ You are responsible for using collected data in line with applicable laws and [LinkedIn's terms of service](https://www.linkedin.com/legal/user-agreement). *** ### Tips for best results 1. **Use the post link from the browser** — Open the post on LinkedIn, copy the address bar URL, and paste it into `postUrls`. 2. **Start with a small batch** — Test with 5–10 posts before large exports. 3. **Expect partial comments** — `numComments` is the total count; the `comments` array contains only comments visible on the public page (often a subset). 4. **Deduplicate on `postUrl`** — Use the canonical post link as a stable key across runs. 5. **Schedule recurring runs** — Use Apify schedules to monitor the same posts or refresh a list over time. 6. **Export flexibly** — Download the dataset as JSON, CSV, Excel, or connect via API to your warehouse or automation tools. *** ### Frequently asked questions **Can I scrape a profile or company feed?**\ This Actor is built for **individual post URLs**. For company post feeds, use a LinkedIn company scraper with post collection enabled. **Why is a post missing from my dataset?**\ The post may be unavailable, temporarily busy, restricted, or the URL may be invalid. Check the run log for `Could not retrieve: ...` messages. Other posts in the same run can still succeed. **Why does `numComments` not match the `comments` array length?**\ `numComments` is the total count shown on the post. The `comments` array includes only comments LinkedIn exposes on the public page — often fewer than the full thread. **Why is the author a person on a company post?**\ Some posts are published by executives or employees on behalf of an organization. The `author.type` field indicates `person` or `organization` as shown on the page. **Will failed posts be charged?**\ No. Only posts successfully saved to the dataset are billed as results. See the **Pricing** tab for current rates. **Can I run hundreds of post URLs at once?**\ Yes on paid plans. Posts are processed in parallel; results appear in the dataset as each one completes. *** ### Support For Actor-specific issues, use the **Issues** tab on the Apify Store listing or contact the publisher through Apify. For platform questions (runs, billing, API, schedules), see [Apify documentation](https://docs.apify.com) and Apify support. # Actor input Schema ## `postUrls` (type: `array`): Enter LinkedIn post URLs, one per line. Supported links include standard post pages (for example, https://www.linkedin.com/posts/username\_activity-1234567890-abcd/ or https://www.linkedin.com/posts/company-name\_keywords-activity-1234567890-abcd/). Tracking parameters in the URL are ignored. ## Actor input object example ```json { "postUrls": [ "https://www.linkedin.com/posts/apify_two-brothers-scraped-10000-french-bakeries-activity-7477345241553936384-aWdh", "https://www.linkedin.com/posts/charlie-hills_claude-has-375-native-mcp-connectors-how-activity-7473675973541044225-8oQk" ] } ``` # 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 = { "postUrls": [ "https://www.linkedin.com/posts/apify_two-brothers-scraped-10000-french-bakeries-activity-7477345241553936384-aWdh", "https://www.linkedin.com/posts/charlie-hills_claude-has-375-native-mcp-connectors-how-activity-7473675973541044225-8oQk" ] }; // Run the Actor and wait for it to finish const run = await client.actor("calm_builder/linkedin-posts-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 = { "postUrls": [ "https://www.linkedin.com/posts/apify_two-brothers-scraped-10000-french-bakeries-activity-7477345241553936384-aWdh", "https://www.linkedin.com/posts/charlie-hills_claude-has-375-native-mcp-connectors-how-activity-7473675973541044225-8oQk", ] } # Run the Actor and wait for it to finish run = client.actor("calm_builder/linkedin-posts-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 '{ "postUrls": [ "https://www.linkedin.com/posts/apify_two-brothers-scraped-10000-french-bakeries-activity-7477345241553936384-aWdh", "https://www.linkedin.com/posts/charlie-hills_claude-has-375-native-mcp-connectors-how-activity-7473675973541044225-8oQk" ] }' | apify call calm_builder/linkedin-posts-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=calm_builder/linkedin-posts-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "LinkedIn Posts Scraper", "description": "Extract structured data from public LinkedIn post URLs. Collect post text, author, publish date, reaction and comment counts, visible comments, reaction types, and media (images, video, carousels, documents) — ideal for social listening, content research, competitor monitoring, and lead enrichment.", "version": "0.0", "x-build-id": "URzpAgLZkixml0Mrd" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/calm_builder~linkedin-posts-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-calm_builder-linkedin-posts-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/calm_builder~linkedin-posts-scraper/runs": { "post": { "operationId": "runs-sync-calm_builder-linkedin-posts-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/calm_builder~linkedin-posts-scraper/run-sync": { "post": { "operationId": "run-sync-calm_builder-linkedin-posts-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "postUrls" ], "properties": { "postUrls": { "title": "LinkedIn post URLs", "minItems": 1, "type": "array", "description": "Enter LinkedIn post URLs, one per line. Supported links include standard post pages (for example, https://www.linkedin.com/posts/username_activity-1234567890-abcd/ or https://www.linkedin.com/posts/company-name_keywords-activity-1234567890-abcd/). Tracking parameters in the URL are ignored.", "items": { "type": "string", "minLength": 1 } } } }, "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 } } } } } } } } } } ```