# LinkedIn Posts Scraper (`parseforge/linkedin-posts-scraper`) Actor Scrape LinkedIn posts from any public profile or company page. Get post text, headlines, author details, engagement metrics, images, videos, and top comments with dates. Supports batch processing of multiple profiles. No login required. Export to JSON, CSV, or integrate with any app. - **URL**: https://apify.com/parseforge/linkedin-posts-scraper.md - **Developed by:** [ParseForge](https://apify.com/parseforge) (community) - **Categories:** Social media, Lead generation, Other - **Stats:** 53 total users, 22 monthly users, 99.6% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per event 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 ![ParseForge Banner](https://github.com/ParseForge/apify-assets/blob/ad35ccc13ddd068b9d6cba33f323962e39aed5b2/banner.jpg?raw=true) ## ๐Ÿ’ผ LinkedIn Posts Scraper > ๐Ÿš€ **Pull LinkedIn posts from any public profile or company page in minutes.** Post text, author info, likes, comments, dates, images, top comments. No login. > ๐Ÿ•’ **Last updated:** 2026-05-08 ยท **๐Ÿ“Š 15+ fields** per post ยท **๐Ÿ‘ค Profile + company pages** ยท **๐Ÿšซ No auth** required Pull live LinkedIn posts from public profiles, company pages, or direct post URLs. The actor walks the LinkedIn feed for each URL you supply, fetches each post's metadata and engagement signals, and returns one structured record per post ready for social-listening, competitive intelligence, content research, or B2B sales workflows. Every run fetches data live so you get the current state of LinkedIn at run time, not a stale dump. Records include the post URL, post text, author name and headline, post date, like count, comment count, repost count, image URLs, and top comments where exposed. | ๐Ÿ‘ฅ Built for | ๐ŸŽฏ Primary use cases | |---|---| | Marketing and content teams | Track competitor posting cadence and engagement | | Social listening | Monitor brand mentions and executive activity | | Sales and BD teams | Source warm leads from engagement on target posts | | Recruiters | Track talent discussions and thought leadership | | Researchers | Study B2B social trends and discussion topics | | PR and comms | Map media presence and message resonance | --- ### ๐Ÿ“‹ What the LinkedIn Posts Scraper does - ๐Ÿ“ **Post text.** Full post body as displayed on LinkedIn. - ๐Ÿ‘ค **Author info.** Name, headline, profile URL, and avatar. - ๐Ÿ“Š **Engagement.** Like count, comment count, repost count. - ๐Ÿ“… **Timestamps.** Post date and a precise timestamp where exposed. - ๐Ÿ–ผ๏ธ **Images and media.** URLs of any embedded images. - ๐Ÿ’ฌ **Top comments.** Sample of top comments where LinkedIn exposes them. The scraper accepts profile URLs, company URLs, or direct post URLs. It walks the feed for each URL you supply, paginates through posts, and pushes structured records to the dataset. Residential proxies are recommended for reliable LinkedIn access. > ๐Ÿ’ก **Why it matters:** LinkedIn is the canonical B2B content surface but its UI is paginated, JS-rendered, and aggressively rate-limited. A live, structured pull beats manual scraping for social listening, competitive intelligence, and B2B lead generation. --- ### ๐ŸŽฌ Full Demo ๐Ÿšง Coming soon: a 3-minute walkthrough showing setup, a live run, and how to pipe results into Salesforce or HubSpot via Apify integrations. --- ### โš™๏ธ Input | Field | Type | Name | Description | |---|---|---|---| | startUrls | array | LinkedIn URLs | Required. Profile URLs (`https://www.linkedin.com/in/...`), company URLs (`https://www.linkedin.com/company/...`), or direct post URLs. | | maxItems | integer | Max Items | Free users: limited to 10 items (preview). Paid users: optional, max 1,000,000. | | proxyConfiguration | object | Proxy Configuration | Proxy settings. Defaults to Apify residential pool which is required for reliable LinkedIn access. | Example 1. Posts from a CEO profile. ```json { "startUrls": [ { "url": "https://www.linkedin.com/in/satyanadella/" } ], "maxItems": 50 } ```` Example 2. Posts from multiple company pages. ```json { "startUrls": [ { "url": "https://www.linkedin.com/company/microsoft/" }, { "url": "https://www.linkedin.com/company/google/" }, { "url": "https://www.linkedin.com/company/apple/" } ], "maxItems": 100 } ``` > โš ๏ธ **Good to Know:** LinkedIn aggressively rate-limits scraping. Residential proxies are required for reliable pulls. The default proxyConfiguration uses the Apify residential pool which works out of the box. *** ### ๐Ÿ“Š Output The dataset returns one structured record per LinkedIn post. Each record carries identifiers, post text, author info, timestamps, engagement metrics, image URLs, and a back-reference URL. Consume the dataset as JSON, CSV, Excel, XML, or RSS via the Apify console or API. #### ๐Ÿงพ Schema | Field | Type | Example | |---|---|---| | ๐Ÿ†” postId | string | `urn:li:activity:7234567890` | | ๐Ÿ”— postUrl | string (url) | `https://www.linkedin.com/feed/update/urn:li:activity:7234567890/` | | ๐Ÿ“ text | string | `Excited to share our Q2 results...` | | ๐Ÿ‘ค authorName | string | `Satya Nadella` | | ๐Ÿ’ผ authorHeadline | string | `Chairman & CEO at Microsoft` | | ๐Ÿ”— authorUrl | string (url) | `https://www.linkedin.com/in/satyanadella/` | | ๐Ÿ–ผ๏ธ authorAvatarUrl | string (url) | `https://media.licdn.com/dms/.../avatar.jpg` | | ๐Ÿ“… publishedAt | ISO datetime | `2026-04-12T14:30:00.000Z` | | ๐Ÿ“… publishedAgo | string | `3w` | | ๐Ÿ‘ likeCount | number | `5240` | | ๐Ÿ’ฌ commentCount | number | `312` | | ๐Ÿ” repostCount | number | `847` | | ๐Ÿ–ผ๏ธ imageUrls | array | `["https://media.licdn.com/.../1.jpg", "..."]` | | ๐Ÿ’ฌ topComments | array | `[{"author":"...", "text":"..."}]` | | ๐Ÿ“… scrapedAt | ISO datetime | `2026-05-08T12:00:00.000Z` | #### ๐Ÿ“ฆ Sample records ##### 1. Typical record (CEO post with high engagement) ```json { "postId": "urn:li:activity:7234567890", "postUrl": "https://www.linkedin.com/feed/update/urn:li:activity:7234567890/", "text": "Excited to share our Q2 results: AI-driven products growing 50%+ YoY. Thanks to our customers and partners for the trust and feedback that drives the work.", "authorName": "Satya Nadella", "authorHeadline": "Chairman & CEO at Microsoft", "authorUrl": "https://www.linkedin.com/in/satyanadella/", "authorAvatarUrl": "https://media.licdn.com/dms/avatar/satya.jpg", "publishedAt": "2026-04-12T14:30:00.000Z", "publishedAgo": "3w", "likeCount": 5240, "commentCount": 312, "repostCount": 847, "imageUrls": ["https://media.licdn.com/dms/post/q2-results.jpg"], "topComments": [ {"author": "Sundar Pichai", "text": "Great results, congrats Satya."}, {"author": "Jensen Huang", "text": "Inspiring leadership."} ], "scrapedAt": "2026-05-08T12:00:00.000Z" } ``` ##### 2. Company page post (text only) ```json { "postId": "urn:li:activity:7300123456", "postUrl": "https://www.linkedin.com/feed/update/urn:li:activity:7300123456/", "text": "We are hiring senior engineers in Dublin. Apply at the link below.", "authorName": "Acme Corp", "authorHeadline": "Acme Corp", "authorUrl": "https://www.linkedin.com/company/acme-corp/", "publishedAt": "2026-05-01T09:00:00.000Z", "publishedAgo": "1w", "likeCount": 142, "commentCount": 8, "repostCount": 12, "imageUrls": [], "topComments": [], "scrapedAt": "2026-05-08T12:00:00.000Z" } ``` ##### 3. Sparse record (low-engagement post) ```json { "postId": "urn:li:activity:7400000000", "postUrl": "https://www.linkedin.com/feed/update/urn:li:activity:7400000000/", "text": "Heading to the conference next week.", "authorName": "Jane Smith", "authorHeadline": "Engineering Manager", "authorUrl": "https://www.linkedin.com/in/jane-smith/", "publishedAt": "2026-05-07T08:00:00.000Z", "publishedAgo": "1d", "likeCount": 7, "commentCount": 0, "repostCount": 0, "imageUrls": [], "topComments": [], "scrapedAt": "2026-05-08T12:00:00.000Z" } ``` *** ### โœจ Why choose this Actor | | Capability | |---|---| | ๐ŸŽฏ | **Built for the job.** Scoped specifically to LinkedIn posts so you skip the parser engineering entirely. | | ๐Ÿ”– | **Structured output.** Clean, typed fields ready for analysis, dashboards, or downstream pipelines. | | โšก | **Fast.** Optimized request patterns return results in seconds, not minutes. | | ๐Ÿ” | **Always fresh.** Every run pulls live data, so the dataset reflects LinkedIn as of run time. | | ๐ŸŒ | **No infra to manage.** Apify handles proxies, retries, scaling, scheduling, and storage. | | ๐Ÿ›ก๏ธ | **Reliable.** Battle-tested across many runs and edge cases, with graceful error handling. | | ๐Ÿšซ | **No code required.** Configure in the UI, run from CLI, schedule via cron, or call from any language with the Apify SDK. | > ๐Ÿ“Š Production-grade structured social data without the engineering overhead of building and maintaining your own scraper. *** ### ๐Ÿ“ˆ How it compares to alternatives | Approach | Cost | Coverage | Refresh | Filters | Setup | |---|---|---|---|---|---| | **โญ LinkedIn Posts Scraper** *(this Actor)* | $5 free credit, then pay-per-use | Public profiles + companies | **Live per run** | Profile, company, post URL | โšก 2 min | | Build your own scraper | Engineering hours | Full once built | Whenever you maintain it | Custom code | ๐Ÿข Days to weeks | | Paid social-listening tools | $$$ monthly per seat | Vendor-defined | Periodic | Vendor-defined | โณ Hours | | Manual sourcing | Hours per check | Limited | Stale | Manual | ๐Ÿ•’ Variable | Pick this Actor when you want broad coverage, source-native filtering, and no pipeline maintenance. *** ### ๐Ÿš€ How to use 1. ๐Ÿ“ **Sign up.** [Create a free account with $5 credit](https://console.apify.com/sign-up?fpr=vmoqkp) (takes 2 minutes). 2. ๐ŸŒ **Open the Actor.** Go to the LinkedIn Posts Scraper page on the Apify Store. 3. ๐ŸŽฏ **Add LinkedIn URLs.** Paste profile, company, or post URLs into startUrls. 4. ๐Ÿš€ **Run it.** Click **Start** and let the Actor collect your data. 5. ๐Ÿ“ฅ **Download.** Grab your results in the **Dataset** tab as CSV, Excel, JSON, or XML. > โฑ๏ธ Total time from signup to downloaded dataset: **3-5 minutes.** No coding required. *** ### ๐Ÿ’ผ Business use cases
#### ๐Ÿ“Š Marketing and content - Benchmark competitor posting cadence and engagement - Identify high-performing content formats by industry - Track executive activity for thought-leadership analysis - Build content libraries from top-performing posts #### ๐Ÿข Social listening and PR - Monitor brand mentions across executive feeds - Track message resonance after launch announcements - Build crisis-response monitoring dashboards - Map share-of-voice in your industry
#### ๐ŸŽฏ Sales and BD - Source warm leads from engagement on target posts - Track buying signals from prospect activity - Build account-based marketing target lists - Power outbound personalization with recent posts #### ๐Ÿ› ๏ธ Engineering and product - Prototype social-data products without owning a crawler - Replace fragile in-house LinkedIn scrapers - Wire datasets into your apps via the Apify API or webhooks - Skip the proxy, retry, and parsing maintenance entirely
*** ### ๐ŸŒŸ Beyond business use cases Data like this powers more than commercial workflows. The same structured records support research, education, civic projects, and personal initiatives.
#### ๐ŸŽ“ Research and academia - Empirical datasets for papers, thesis work, and coursework - Longitudinal studies tracking changes across snapshots - Reproducible research with cited, versioned data pulls - Classroom exercises on data analysis and ethical scraping #### ๐ŸŽจ Personal and creative - Side projects, portfolio demos, and indie app launches - Data visualizations, dashboards, and infographics - Content research for bloggers, YouTubers, and podcasters - Hobbyist collections and personal trackers
#### ๐Ÿค Non-profit and civic - Transparency reporting and accountability projects - Advocacy campaigns backed by public-interest data - Community-run databases for local issues - Investigative journalism on public records #### ๐Ÿงช Experimentation - Prototype AI and machine-learning pipelines with real data - Validate product-market hypotheses before engineering spend - Train small domain-specific models on niche corpora - Test dashboard concepts with live input
*** ### ๐Ÿ”Œ Automating LinkedIn Posts Scraper This Actor exposes a REST endpoint, so you can drive it from any language or workflow tool. - **Node.js** - call it via the [Apify JS SDK](https://docs.apify.com/sdk/js). - **Python** - call it via the [Apify Python SDK](https://docs.apify.com/sdk/python). - **REST** - hit it directly through the [Apify v2 API](https://docs.apify.com/api/v2). **Schedules.** Use Apify Scheduler to capture daily or weekly snapshots of target profiles. Combine with the Apify dataset diff tools to track new posts and engagement velocity between runs. *** ### โ“ Frequently Asked Questions
๐Ÿ’ณ Do I need a paid Apify plan to run this actor? No. You can start right now on the free Apify plan, which includes **$5 in monthly credit**. That is enough to run the scraper several times and explore the output. Paid plans unlock higher item caps, more concurrent runs, and larger datasets. [Create a free Apify account here](https://console.apify.com/sign-up?fpr=vmoqkp).
๐Ÿšจ What happens if my run fails or returns no results? Failed runs are not charged. If LinkedIn changes its DOM, proxies get rate-limited, or your URLs match nothing, re-run the actor or open our [contact form](https://tally.so/r/BzdKgA) and we will look into it.
๐Ÿ“ How many items can I scrape per run? Free users are limited to **10 items per run** so you can preview the output. Paid users can raise maxItems up to **1,000,000** per run.
๐Ÿ•’ How fresh is the data? Every run fetches live data at the moment of execution. There is no cache or delay: records reflect what LinkedIn returned at run time. Schedule the actor to maintain a rolling snapshot.
๐Ÿง‘โ€๐Ÿ’ป Can I call this actor from my own code? Yes. Apify exposes every actor as a REST endpoint and ships first-class SDKs for [Node.js](https://docs.apify.com/sdk/js) and [Python](https://docs.apify.com/sdk/python). You can start a run, read the dataset, and handle webhooks from your own app in a few lines.
๐Ÿ“ค How do I export the data? Every Apify dataset can be downloaded in one click as CSV, JSON, JSONL, Excel, HTML, XML, or RSS. You can also pull results programmatically via the [Apify API](https://docs.apify.com/api/v2) or stream into BigQuery, S3, and other destinations through built-in integrations.
๐Ÿ“… Can I schedule the actor to run automatically? Yes. Use the Apify scheduler to run the actor on any cadence, from hourly to monthly. Results are saved to your dataset and can be delivered to webhooks, email, Slack, cloud storage, or automation tools such as Zapier and Make.
๐Ÿช Can I use the data commercially? Yes. The scraped data is yours to use in your own internal pipelines, products, and reports, subject to the terms of service of the source site and applicable privacy laws.
๐Ÿ’ผ Which plan should I pick for production use? Apify's Starter and Scale plans are designed for production workloads. They give you faster instances, more concurrent runs, and higher proxy quotas. Pick the plan that matches your dataset size and refresh cadence; the in-app pricing calculator will help you size it.
๐Ÿ› ๏ธ The data I need is not in the output. Can you add it? Most likely yes. Open the [contact form](https://tally.so/r/BzdKgA) and tell us which field you need. We add fields all the time when there is a clear use case and the source page exposes the data.
โš–๏ธ Is scraping LinkedIn legal? This Actor only collects data from publicly accessible LinkedIn pages, the same content any visitor can read. Public web scraping is generally legal in most jurisdictions for non-personal data, but laws vary by country and use case. You are responsible for compliance with LinkedIn's Terms of Service, applicable privacy laws (such as GDPR or CCPA), and any data-protection rules that apply. ***
### ๐Ÿ”Œ Integrate with any app LinkedIn Posts Scraper connects to any cloud service via [Apify integrations](https://apify.com/integrations): - [**Make**](https://docs.apify.com/platform/integrations/make) - Automate multi-step workflows - [**Zapier**](https://docs.apify.com/platform/integrations/zapier) - Connect with 5,000+ apps - [**Slack**](https://docs.apify.com/platform/integrations/slack) - Get run notifications in your channels - [**Airbyte**](https://docs.apify.com/platform/integrations/airbyte) - Pipe results into your warehouse - [**GitHub**](https://docs.apify.com/platform/integrations/github) - Trigger runs from commits and releases - [**Google Drive**](https://docs.apify.com/platform/integrations/drive) - Export datasets straight to Sheets You can also use webhooks to trigger downstream actions when a run finishes. Push fresh data into your product backend or alert your team in Slack. *** ### ๐Ÿ”— Recommended Actors - [**๐Ÿ’ผ LinkedIn Profile Scraper**](https://apify.com/parseforge/linkedin-profile-scraper) - LinkedIn profiles with contact and experience data - [**๐Ÿ“ธ Instagram Posts Scraper**](https://apify.com/parseforge/instagram-posts-scraper) - Instagram posts and reels with metadata - [**๐Ÿฆ X (Twitter) Scraper**](https://apify.com/parseforge/x-com-scraper) - Tweets with engagement and author info - [**๐Ÿ“ฑ Reddit Posts Scraper**](https://apify.com/parseforge/reddit-posts-scraper) - Subreddit posts with comments and engagement - [**๐Ÿ“ฑ TikTok Video Scraper**](https://apify.com/parseforge/tiktok-video-scraper) - TikTok videos with metadata and engagement > ๐Ÿ’ก **Pro Tip:** browse the complete [ParseForge collection](https://apify.com/parseforge) for more reference-data scrapers. *** **๐Ÿ†˜ Need Help?** [**Open our contact form**](https://tally.so/r/BzdKgA) to request a new scraper, propose a custom project, or report an issue. *** > โš ๏ธ **Disclaimer.** This Actor is an independent tool and is not affiliated with, endorsed by, or sponsored by LinkedIn or Microsoft. All trademarks mentioned are the property of their respective owners. The scraper accesses only publicly available pages and is intended for legitimate research, analytics, and lead-generation use. Users are responsible for compliance with LinkedIn's Terms of Service, applicable privacy laws, and any data-protection rules that apply. # Actor input Schema ## `startUrls` (type: `array`): LinkedIn profile URLs (e.g. https://www.linkedin.com/in/satyanadella/), company URLs (e.g. https://www.linkedin.com/company/microsoft/), or direct post URLs. ## `maxItems` (type: `integer`): Free users: Limited to 10 items (preview). Paid users: Optional, max 1,000,000 ## `proxyConfiguration` (type: `object`): Residential proxies recommended for reliable extraction from LinkedIn. ## Actor input object example ```json { "startUrls": [ { "url": "https://www.linkedin.com/in/satyanadella/" } ], "maxItems": 10, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } } ``` # Actor output Schema ## `overview` (type: `string`): Overview of posts with key fields ## `fullData` (type: `string`): Complete dataset with all post fields # 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 = { "startUrls": [ { "url": "https://www.linkedin.com/in/satyanadella/" } ], "maxItems": 10, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }; // Run the Actor and wait for it to finish const run = await client.actor("parseforge/linkedin-posts-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`๐Ÿ’พ Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "startUrls": [{ "url": "https://www.linkedin.com/in/satyanadella/" }], "maxItems": 10, "proxyConfiguration": { "useApifyProxy": True, "apifyProxyGroups": ["RESIDENTIAL"], }, } # Run the Actor and wait for it to finish run = client.actor("parseforge/linkedin-posts-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("๐Ÿ’พ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "startUrls": [ { "url": "https://www.linkedin.com/in/satyanadella/" } ], "maxItems": 10, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }' | apify call parseforge/linkedin-posts-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=parseforge/linkedin-posts-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "LinkedIn Posts Scraper", "description": "Scrape LinkedIn posts from any public profile or company page. Get post text, headlines, author details, engagement metrics, images, videos, and top comments with dates. Supports batch processing of multiple profiles. No login required. Export to JSON, CSV, or integrate with any app.", "version": "1.0", "x-build-id": "bvE9zF0RgW1gtyHmJ" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/parseforge~linkedin-posts-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-parseforge-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/parseforge~linkedin-posts-scraper/runs": { "post": { "operationId": "runs-sync-parseforge-linkedin-posts-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/parseforge~linkedin-posts-scraper/run-sync": { "post": { "operationId": "run-sync-parseforge-linkedin-posts-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "properties": { "startUrls": { "title": "LinkedIn URLs", "type": "array", "description": "LinkedIn profile URLs (e.g. https://www.linkedin.com/in/satyanadella/), company URLs (e.g. https://www.linkedin.com/company/microsoft/), or direct post URLs.", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } }, "maxItems": { "title": "Max Items", "minimum": 1, "maximum": 1000000, "type": "integer", "description": "Free users: Limited to 10 items (preview). Paid users: Optional, max 1,000,000" }, "proxyConfiguration": { "title": "Proxy Configuration", "type": "object", "description": "Residential proxies recommended for reliable extraction from LinkedIn." } } }, "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 } } } } } } } } } } ```