LinkedIn Scraper (Python)

Scrape public LinkedIn jobs, companies, profiles and posts with Python. No login, no API key, one file.

Need this at scale? The script is for learning and small jobs. The ToolzerHub LinkedIn API returns the same data and more (Ad Library search, a company's recent updates and its affiliated pages) as JSON from any server, with no blocks to handle. 100 free credits a month, no card needed.

What it scrapes

Command	What you get
jobs <keywords>	Public job search: title, company, location, post date and salary when shown. Filter by place and age (LinkedIn often ignores the workplace filter)
job <id or url>...	One job posting with its full description, seniority, employment type, industries and applicant hint
company <name>...	A company page: about text, website, size, headquarters, specialties, follower and employee counts, similar companies
profile <name>...	A public profile: name, headline, location, about, follower count, work history, education and a few recent posts
post <url>...	One public post: text, date, author, like and comment counts, and optionally the first page of comments

Quick start

git clone https://github.com/toolzerhub/linkedin-scraper.git
cd linkedin-scraper
pip install -r requirements.txt
python linkedin_scraper.py company microsoft

More examples:

python linkedin_scraper.py jobs "data analyst" --location London --limit 20 -o jobs.json
python linkedin_scraper.py jobs "teacher" --location Sydney --posted week --workplace hybrid
python linkedin_scraper.py job 4476983365
python linkedin_scraper.py company nasa -o nasa.json
python linkedin_scraper.py profile williamhgates
python linkedin_scraper.py post https://www.linkedin.com/posts/williamhgates_for-an-affordable-climate-win-look-to-the-activity-7515504308268810240-k1KI --comments

Every command takes -o file.json to save the result and --proxy URL to route through a proxy. The script also reads HTTPS_PROXY. You can pass several companies, profiles or posts to one command, but see Limits. A company or profile can be the name from its URL (microsoft, williamhgates) or the full page URL. A job can be its numeric id or its URL. --posted takes day, week or month, and --workplace takes onsite, remote or hybrid.

Example output

python linkedin_scraper.py jobs "data analyst" --location London --limit 10 (two jobs shown)

[
  {
    "job_id": "4476590411",
    "url": "https://www.linkedin.com/jobs/view/4476590411",
    "title": "Data Analyst",
    "company": "Searchability NS&D",
    "company_url": "https://www.linkedin.com/company/searchability-ns-d",
    "location": "London Area, United Kingdom",
    "posted_date": "2026-10-07",
    "salary": null,
    "actively_hiring": true
  },
  {
    "job_id": "4472176709",
    "url": "https://www.linkedin.com/jobs/view/4472176709",
    "title": "Data Analyst - Up to £80k + Benefits + Bonus",
    "company": "Oliver Bernard",
    "company_url": "https://www.linkedin.com/company/oliverbernard",
    "location": "London Area, United Kingdom",
    "posted_date": "2026-09-30",
    "salary": null,
    "actively_hiring": true
  }
]

python linkedin_scraper.py job 4476983365

{
  "job_id": "4476983365",
  "url": "https://www.linkedin.com/jobs/view/4476983365",
  "title": "Software Engineer II (Java/AWS)",
  "company": "JPMorganChase",
  "company_url": "https://www.linkedin.com/company/jpmorganchase",
  "location": "New York, NY",
  "posted_ago": "5 days ago",
  "applicants": "162 applicants",
  "salary": "$123,500.00/yr - $150,000.00/yr",
  "is_open": true,
  "seniority_level": "Not Applicable",
  "employment_type": "Full-time",
  "industries": "Financial Services",
  "description": "Job Description\n\nYou're ready to gain the skills and experience needed to grow within your role and advance yo..."
}

python linkedin_scraper.py company microsoft (lists shortened)

{
  "slug": "microsoft",
  "url": "https://www.linkedin.com/company/microsoft",
  "company_id": "1035",
  "name": "Microsoft",
  "industry": "Software Development",
  "description": "Every company has a mission. What's ours? To empower every person and every organization to achieve more. We b...",
  "website": "https://news.microsoft.com/",
  "company_size": "10,001+ employees",
  "employee_count": 231136,
  "followers_count": 29287243,
  "type": "Public Company",
  "founded": null,
  "specialties": [
    "Business Software",
    "Developer Tools",
    "Home & Educational Software",
    "Tablets"
  ],
  "headquarters": "Redmond, Washington",
  "address": {
    "street": "1 Microsoft Way",
    "city": "Redmond",
    "region": "Washington",
    "postal_code": "98052",
    "country": "US"
  },
  "logo_url": "https://media.licdn.com/dms/image/v2/D560BAQH32RJQCl3dDQ/company-logo_200_200/B56ZYQ0mrGGoAM-/0/1744038948046/...",
  "similar_companies": [
    "google",
    "amazon",
    "apple",
    "meta"
  ]
}

python linkedin_scraper.py profile williamhgates (one recent post shown)

{
  "slug": "williamhgates",
  "url": "https://www.linkedin.com/in/williamhgates",
  "name": "Bill Gates",
  "headline": "Chair, Gates Foundation and Founder, Breakthrough Energy",
  "location": "Seattle, Washington, United States",
  "country": "US",
  "about": "Chair of the Gates Foundation. Founder of Breakthrough Energy. Co-founder of Microsoft. Voracious reader. Avid...",
  "badges": "Creator, Top Voice",
  "followers_count": 40727634,
  "photo_url": "https://media.licdn.com/dms/image/v2/D5603AQF-RYZP55jmXA/profile-displayphoto-shrink_200_200/B56ZRi8g.aGsAY-/0...",
  "experience": [
    {
      "title": "Co-chair",
      "company": "Gates Foundation",
      "company_url": "https://www.linkedin.com/company/gates-foundation",
      "start": "2000",
      "end": null,
      "is_current": true
    },
    {
      "title": "Founder",
      "company": "Breakthrough Energy",
      "company_url": "https://www.linkedin.com/company/breakthrough-energy",
      "start": "2015",
      "end": null,
      "is_current": true
    },
    {
      "title": "Co-founder",
      "company": "Microsoft",
      "company_url": "https://www.linkedin.com/company/microsoft",
      "start": "1975",
      "end": null,
      "is_current": true
    }
  ],
  "education": [
    {
      "school": "Harvard University",
      "school_url": "https://www.linkedin.com/school/harvard-university",
      "start_year": 1973,
      "end_year": 1975
    }
  ],
  "recent_posts": [
    {
      "url": "https://www.linkedin.com/posts/williamhgates_child-malnutrition-is-one-of-africas-biggest-activity-7514893923710984192-ZuIL",
      "published_at": "2026-10-11T03:45:31+00:00",
      "text": "Tackling malnutrition requires more than a steady supply of nutritious food. Access to healthcare, clean water, and safe sanitation are just as essential to growing up healthy. ",
      "like_count": 1424
    }
  ]
}

python linkedin_scraper.py post https://www.linkedin.com/posts/williamhgates_for-an-affordable-climate-win-look-to-the-activity-7515504308268810240-k1KI

{
  "id": "7515504308268810240",
  "url": "https://www.linkedin.com/posts/williamhgates_for-an-affordable-climate-win-look-to-the-activity-75155043082688...",
  "published_at": "2026-10-12T20:10:58+00:00",
  "text": "To prevent the majority of warming contrails—the cloud-like lines we sometimes see form behind planes—we would...",
  "author_name": "Bill Gates",
  "author_url": "https://www.linkedin.com/in/williamhgates",
  "author_followers": 40727634,
  "like_count": 2850,
  "comment_count": 476,
  "shared_link": "https://www.linkedin.com/pulse/affordable-climate-win-look-sky-bill-gates-eoj7e",
  "image_url": "https://dms.licdn.com/playlist/vid/v2/D4E12AQFXSlhYCq-GVA/thumbnail-with-play-button-overlay-low/B4EaExtVeFJIC..."
}

Long text and links are shortened here. The full outputs for every command are in examples/.

Fields

jobs

Field	Description
job_id, url	LinkedIn's job id and a short link to the posting
title	Job title
company, company_url	The employer and its page
location	Place as LinkedIn shows it
posted_date	Day it was posted, YYYY-MM-DD
salary	Pay range when the card shows one, otherwise null
actively_hiring	True when the card has the "Actively Hiring" badge

job

Field	Description
job_id, url, title	Same as jobs
company, company_url, location	Same as jobs
posted_ago	How long ago it was posted, as text ("5 days ago")
applicants	The applicant hint LinkedIn shows ("162 applicants", "Over 200 applicants")
salary	Pay range when the posting shows one, otherwise null
is_open	False when LinkedIn marks the job as closed
seniority_level, employment_type, industries	The criteria LinkedIn lists. A missing one is null
description	The full description as plain text, one line per paragraph or bullet

company

Field	Description
slug, url	The name in the company URL, and the page link
company_id	LinkedIn's numeric company id
name, industry, description	Basics from the page
website	The company's own site
company_size	Size band ("10,001+ employees")
employee_count	Employee number LinkedIn reports, as an integer
followers_count	Followers as an integer
type	Public company, nonprofit and so on
founded	Year, or null when the page does not list it
specialties	List of specialties
headquarters	Headquarters as text
address	Street, city, region, postal code and country code
logo_url	Logo link (signed, it expires)
similar_companies	Names from the "similar pages" list, as URL names

profile

Field	Description
slug, url	The name in the profile URL, and the page link
name, headline	Name and headline
location, country	Place text and country code
about	The about text
badges	Badges such as "Creator, Top Voice", or null
followers_count	Followers as an integer
photo_url	Profile photo link (signed, it expires)
experience	Title, company, company_url, start year, end year and is_current
education	School, school_url, start_year and end_year
recent_posts	A few recent posts: url, published_at, text and like_count

post

Field	Description
id, url	Activity id and post link
published_at	ISO 8601 UTC
text	The full post text
author_name, author_url, author_followers	The author
like_count, comment_count	Counts as integers
shared_link	Link to a shared article, or null
image_url	Cover image link (signed, it expires)
comments	Only with --comments: text, published_at, like_count and author_name for the first page of comments

How it works

1. jobs and job call the same small public endpoints LinkedIn's own job pages use (/jobs-guest/jobs/api/seeMoreJobPostings/search and /jobs-guest/jobs/api/jobPosting/<id>). They answer with HTML fragments, and jobs pages through them 10 at a time. The requests look like Chrome (curl_cffi copies its network fingerprint).
2. company, profile and post ask for the public page (/company/<name>, /in/<name>, /posts/<slug>). Each page holds a <script type="application/ld+json"> block with the main facts, and the page itself holds the rest (company details, work history). Only the job requests send a Referer header. On the pages it makes LinkedIn answer HTTP 999.
3. Each reply is cleaned with BeautifulSoup into the fields above. Counts become integers, times become ISO 8601 UTC, tracking parameters are cut from links, and the raw HTML is dropped.

Limits

• Public data only.
• Only what a signed-out visitor sees. That means no full employee lists, no connections, no skills, no contact details, and only a few recent posts on a profile. comments returns the first page (8 in our 2026-10-17 runs) of a post's comments, not all of them.
• jobs pages through results and can stop early when LinkedIn limits the next page. The script then prints a warning and returns the jobs it already has.
• LinkedIn is strict with repeat requests. The job commands cope better, but they also slow down on long runs. Several names in one page command (company, profile, post) often end with HTTP 429 or 999 and a "rate-limited or blocked" error, and the command saves nothing. Run one page per command and pause between commands. HTTP 999 is also what an unknown profile name gets, so check the spelling first. Run it from a home connection, or pass --proxy (a sticky residential proxy works best).
• No concurrency. The script waits 2 seconds between requests and retries a 429 once. That is all, so it stays short enough to read in one sitting.
• It breaks when LinkedIn changes its pages. See "How we keep it working".

Scaling up

The script is for learning and small jobs. At scale you run into blocks, changing page formats and proxy costs. The ToolzerHub LinkedIn API handles all of that:

	This script	ToolzerHub API
Data	Jobs, company pages, public profiles and posts	20 LinkedIn endpoints: those, plus location search, Ad Library search, company updates and affiliated pages
Blocks and proxies	Your problem	Handled
When LinkedIn changes	Wait for a fix here	Fixed on our side
Cost	Free, plus your proxy	100 free credits a month, then from $0.99 per 1,000 calls

How we keep it working

Every command is run against live LinkedIn pages before each update, and the "last verified" badge shows the last day they all passed. If something breaks, open an issue.

FAQ

Is scraping LinkedIn legal? Scraping publicly available data is generally allowed in many places, but it depends on your country, what you collect and how you use it. Read the Legal section below.

Why am I getting blocked? LinkedIn refuses clients that ask for many pages in a row. On 2026-10-17 one page per command worked from a datacenter IP, while several companies in one command got HTTP 999. Run one page per command and slow down.

Can it get a company's employee list or a profile's skills? No. A signed-out visitor does not see them.

Related scrapers

• instagram-scraper: public Instagram profiles, posts, comments and search
• tiktok-scraper: public TikTok profiles, videos, comments and hashtags
• threads-scraper: public Threads profiles, posts, replies and search
• reddit-scraper: public subreddits, posts, comments, search and user posts
• google-maps-scraper: public Google Maps places, details and reviews
• facebook-ad-library-scraper: public Meta Ad Library ads by keyword or advertiser, with their videos and images
• zillow-scraper: public Zillow listings, property details, Zestimates and price history

Legal and responsible use

This project is for education and for collecting publicly available data. You are responsible for how you use it.

• Public data only. The script reads pages anyone can see without an account. Do not use it to get around logins, paywalls, CAPTCHAs or other access controls.
• Terms and robots rules. LinkedIn's terms of service may restrict automated access. Read them and decide for yourself; following them is your responsibility.
• Personal data. Profiles and comments can contain personal data. Laws such as the GDPR (EU and UK) and the CCPA (California) may apply. Collect only what you need, have a lawful basis, keep it secure, delete it when you no longer need it, and respect people's requests to access or erase their data.
• Copyright. Posts, images and videos belong to their creators. Do not republish them without permission.
• Be gentle. Keep request rates low and do not disrupt the service.
• No warranty. The software is provided "as is" under the MIT License, without warranty of any kind. The authors are not liable for any claim or damage arising from its use.
• Not affiliated. This project is not affiliated with, endorsed by or sponsored by LinkedIn Corporation. LinkedIn is a trademark of LinkedIn Corporation.
• Takedown requests. If you own rights in something here and want it changed or removed, email contact@toolzerhub.com.

This section is not legal advice. If you are unsure, talk to a lawyer.

License

MIT © ToolzerHub