LinkedIn Comments Export Script

@Jennycreation

Hello sir, i already have linkedin post comment scraper in python language. can give you demo for this. I am a full-time freelancer with **17+ years of experience** in web development, software development, automation, and API integrations. My expertise includes: * ASP.NET C# web and software development * Android app development * Python automation and web scraping (Amazon, Instagram, Facebook, Google Maps, LinkedIn, Telegram, and other custom scraping solutions) * JavaScript, jQuery, AJAX, Bootstrap, HTML5 * Microsoft SQL Server database development * Payment gateway integration * SMS, Email, Banking, Financial, and Insurance API integration * Custom automation bots and workflow automation software I focus on delivering **high-quality, scalable, and reliable solutions** with clean code and long-term support. Please contact me in private chat so we can discuss your requirements in detail. I can also show you a **demo of similar projects** I have completed. Looking forward to working with you. Thanks & Regards

@FizzaNadeemK

Hello, I can build a clean Python automation script that accepts a LinkedIn post URL, authenticates securely, collects the available comments and commenter details, and exports everything into a consistent, readable JSON structure. I’ll use browser automation with careful handling of pagination, dynamic content, session management, and error recovery, while keeping credentials outside the source code. I’ll also provide a simple README covering setup, configuration, and execution. I can start immediately and keep the implementation lightweight, documented, and easy to run across Windows, macOS, and Linux. Best Regards, Fizza

@NehalSK

As an IT masters graduate from the University of Melbourne and with professional experience as a software developer intern, I believe I possess the precise combination of skills to complete this LinkedIn comments export script project. My expertise in Python and extensive knowledge of software architecture make me an ideal candidate for your task. With a strong background in JSON and Linux, I will deliver stellar results while adhering thoroughly to your required formatting specifications. Regarding your specific requirements for this project, my time at Queue Solutions allowed me to gain hands-on experience in developing web applications with React and Node JS. I dealt with data organization, scraping from multiple sources, establishing efficient data structures, and delivering comprehensive outputs. All these experiences align impeccably with the task you have entrusted. Additionally, my grasp of "headless" browsing techniques through Selenium and undetected-chromedriver and my inherent understanding of the LinkedIn platform will provide you with a streamlined solution that ensures we work harmoniously within LinkedIn's framework. My familiarity and experience working within automation sciences match your requirements, giving us a higher chance of delivering success quickly. Thank you for considering me for the job; I am excited about the opportunity!

@victoryokafor

The main challenge here is not simply collecting comments,it’s producing a reliable, structured dataset that preserves the post metrics and useful commenter information without creating a complicated workflow. I’d structure the script to accept one LinkedIn post URL, authenticate securely with supplied credentials, collect the available comments and associated public profile details, and export everything into a consistent, human-readable JSON schema. The deliverable would include: • Post URL and total reactions/likes • Comment text and commenter name • Public headline and profile URL where available • Consistent JSON structure • Python 3.x compatibility • Cross-platform setup for Windows, macOS and Linux • Secure credential handling via environment variables/config • README with setup instructions and a one-line run command I’d build the browser automation with a maintainable framework such as Playwright or Selenium, using realistic waits, session handling and error recovery rather than fragile selectors or hard-coded timing. I’ll also account for pagination/lazy-loaded comments and validate the exported JSON before saving it. I can provide relevant Python automation/scraping examples from my portfolio and discuss any LinkedIn-specific constraints before implementation. I’m available to start immediately and can keep the code clean, modular and easy to maintain.

@syedalihasnat929

Hi, This is exactly the kind of focused Python automation project I’m interested in. I can build a clean script that takes a LinkedIn post URL, handles the required authentication, extracts the post’s comments and engagement data, and produces a consistent, readable JSON output containing the commenter name, headline, profile URL, and comment details. I also understand that the important part here is reliability across different posts and a simple setup rather than just making it work once. I can deliver the Python script together with a clear README covering setup, credential handling, dependencies, and execution. I’m available to start immediately and can deliver within 2 days. If you share a sample post URL and your expected JSON structure, I can get started right away.

@satyamsubham1

I can help you with this LinkedIn commenting project and deliver clear, relevant, and natural-sounding comments that match your brand and target audience. I understand that LinkedIn comments need to be more than generic responses—they should add value, encourage engagement, and sound genuinely human. I will carefully follow your requirements, maintain the appropriate tone, and ensure the work is accurate and consistent. I am reliable, responsive, and can start immediately. I can also provide revisions if needed to make sure the final output matches your expectations. I’d be happy to discuss the exact requirements and get started.

@amenaTheQueen

Hi, I can build this in Python using Playwright/Selenium with headless browsing, session handling, dynamic comment loading, and clean JSON export. The script will extract all comments, commenter name/headline/profile URL, and post reaction count, with `.env` credential handling, README, and one-line execution. I’ll keep the code clean, cross-platform, and easy to maintain. Available to start immediately.

@hemantmadhukumar

I’m a Python/DevOps engineer with 5+ years of experience building automation, data-processing, API and production deployment workflows. I can deliver a clean, modular LinkedIn comment exporter using Playwright or Selenium with authenticated session handling, headless browser execution, realistic waits, pagination/“load more” handling, and structured JSON output. The script will capture every available comment along with commenter name, headline, profile URL, and the post’s reaction count. Credentials will be handled securely through environment variables rather than hard-coded values. I’ll also include robust error handling, logging, cross-platform Python 3.x support, requirements/setup files, and a concise README with a one-line execution command. I’ll keep the code easy to maintain so selectors, output schema, and browser settings can be updated independently if LinkedIn changes its UI.

@shivp488

Hi, I have strong experience with Python automation, browser-based workflows, and data extraction, and can build a clean, maintainable scraper with structured JSON output and documentation. I can also provide relevant examples of automation/scraping work and ensure robust handling of pagination, dynamic content, and session management.

@CliveMSoftware

I'll build a production-ready Python script using undetected-chromedriver with Playwright fallback to bypass LinkedIn's bot detection while keeping the code maintainable and efficient. The script will parse the target post URL, authenticate with your credentials, iterate through all comments with smart scrolling and loading detection, and extract commenter names, headlines, profile URLs, and post reaction counts into a clean, consistent JSON schema. I'll include proper error handling for network timeouts, CAPTCHA scenarios, and edge cases like deleted profiles. The README will cover pip dependency installation, secure credential passing via environment variables, and a simple one-line execution example that works across Windows, macOS, and Linux. Delivery in 3 days with full source code and a test run against a public post.

@Harshad007168

Currently, the work I’m doing also involves Selenium and similar browser automation technologies, so I’m already familiar with this type of implementation. Would it be okay to use the same approach for this project ?

@harish42035

hey! i build exactly these kinds of python automation scripts (scraping with human-like browsing, session handling, anti-flag logic). can deliver a clean script that takes a post URL and outputs structured JSON with all comments + reactions + commenter details. i'll use playwright with stealth settings so it behaves like a real user. delivery in 2-3 days with a test run on your post. quick question - do you need it to run once or as a recurring tool for multiple posts?

@pooja10verma

With my extensive background in Full Stack Development, I understand the importance of clean, well-structured code that is easy to understand and maintain. I have a strong command over Python and expert knowledge in Selenium, which combined with my experience in Web Scraping will allow me to deliver high-quality results for this project. I have worked on similar projects in the past where web automation was required to extract data from LinkedIn and other websites, which should assure you of my competence in this domain. In addition to consistently using "human-like" browsing techniques while scraping as per the project requirements, I am also adept at leveraging undetected-chromedriver - a crucial tool ensuring efficient data-extraction without raising any flags or limiting the application's scope of action. I take great pride in strictly adhering to best practices and complying with rate-limits while extracting data through browser automation. Lastly, I prioritize creating comprehensive documentation that ensures efficient project usage by any team member. My README files are always clear and concise, containing detailed instructions for environment setup coupled with a simple one-line command prompt to execute. My proficiency spans various operating systems (Windows, macOS, Linux), so compatibility would not be an issue.

@bhargav922002

Hello, I am bharghav, with 10 years of experience specializing in Python, Linux, Web Scraping, and Software Architecture. I believe my expertise aligns perfectly with your project needs. I understand you require a Python script that securely logs into LinkedIn to extract comments from a specific post URL, along with additional details like total likes and commenter profiles, all formatted neatly in JSON. I’ll ensure the script utilizes headless browsing techniques to maintain a human-like interaction while avoiding rate limits and CAPTCHA challenges. Let’s chat further so we can fine-tune the requirements and make this project a success.

@virals29

Yes sir i can help you work and experience Advance excel, data entry, microsoft Office,microsoft words, typing etc

@ranaatif1299

Hi Sir, I am availablle immediately.I will get this done within next 14 hours.I have 5 years of experience in Python scripting ,ML , AI Engineering. Let's connect

@aasthaj46

Hi, I’m an experienced Python automation developer with strong expertise in browser automation, data extraction, and structured JSON pipelines. I can build a clean, maintainable tool that accepts a LinkedIn post URL and exports the available comment data with a consistent JSON schema, including commenter name, headline, profile URL, and post reaction count. Approach: Python + Playwright/Selenium, with robust waits, session handling, pagination, error handling, and configurable browser settings. I’ll also include secure credential handling, cross-platform setup, and a concise README with a one-line execution command. I’ll design it for reliability and responsible request pacing, while avoiding techniques intended to bypass LinkedIn’s CAPTCHA, rate limits, or other access controls. I can share relevant browser-automation/scraping examples and start immediately. Estimated delivery: 10-15 days.

@raushank237

As an experienced full-stack developer with a specialty in Python, I have been handling similar web scraping projects throughout my career. To comply with your project requirements, I'm acquainted with tools like Selenium and undetected-chromedriver which are known for their seamless automation capabilities while mimicking human-like browsing. My strong understanding of Python along with third-party libraries will ensure the script works effectively on any recent Python 3.x version and across common operating systems like Windows, macOS, and Linux. Moreover, I have a sound comprehension of environment setup, credential handling, and README development which will guarantee that my delivered script comes with a complete and easy-to-understand guide. I understand the significance of consistency and readability in JSON structure, therefore I'll design it meticulously to store each comment along with relevant details like user name, headline, profile URL as well as the total likes/reactions count for the post. Over the years, I have proven myself in solving complex automation challenges and adopting necessary means to meet dynamic rate-limit protocols<strong>[emdash]</strong>exactly what you demand from this project. With my skills and expertise, let's create a robust and efficient LinkedIn Comments Export Script together!

@abhayautomation

Hello, I can build this script for you with super simple workflow: you run one command, paste the LinkedIn post URL, and the script handles the login, collects the comments and required profile/post details, and exports everything into a JSON file. I’ll use Python + Playwright for automation and make it behave as naturally as possible, with realistic navigation, waits, scrolling. If needed we can also integrate a CAPTCHA-solving API to reduce interruptions during browsing. What You’ll Receive • Clean, well-structured Python script. • Simple README with setup and usage instructions. • Easy command-based JSON export. If you’d like, I can also provide a small demo/sample of my approach. Thank you!