StaffSpy is a staff scraper library for LinkedIn.

Features

• Scrapes staff from a company on LinkedIn
• Obtains skills, experiences, certifications & more
• Aggregates the employees in a Pandas DataFrame

Video Guide for StaffSpy - updated for release v0.1.4

Installation

pip install -U staffspy

Python version >= 3.10 required

Usage

from pathlib import Path
from staffspy import LinkedInAccount, SolverType

session_file = Path(__file__).resolve().parent / "session.pkl"
account = LinkedInAccount(
    # credentials - remove these to sign in with browser
    username="myemail@gmail.com",
    password="mypassword",
    solver_api_key="CAP-6D6A8CE981803A309A0D531F8B4790BC", # optional but needed if hit with captcha
    solver_service=SolverType.CAPSOLVER,

    session_file=str(session_file), # save login cookies to only log in once (lasts a week or so)
    log_level=1, # 0 for no logs
)

# search by company
staff = account.scrape_staff(
    company_name="openai",
    search_term="software engineer",
    location="london",
    extra_profile_data=True, # fetch all past experiences, schools, & skills
    max_results=50, # can go up to 1000
)
# or fetch by user ids
users = account.scrape_users(
    user_ids=['williamhgates', 'rbranson', 'jeffweiner08']
)
staff.to_csv("staff.csv", index=False)
users.to_csv("users.csv", index=False)

Browser login

If you rather use a browser to log in, install the browser add-on to StaffSpy .

pip install staffspy[browser]

Do not pass the username & password params, then a browser will open to sign in to LinkedIn on the first sign-in. Press enter after signing in to begin scraping.

Output

profile_id	name	first_name	last_name	location	age	position	followers	connections	premium	company	past_company1	past_company2	school	extra_school	skill1	skill2	skill3	is_connection	premium	creator	potential_email	profile_link	profile_photo
javiersierra2102	Javier Sierra	Javier	Sierra	London, England, United Kingdom	39	Software Engineer	735	725	FALSE	OpenAI	Meta	Oculus VR	Hult International Business School	Universidad Simón Bolívar	Java	JavaScript	C++	FALSE	FALSE	FALSE	javier.sierra@openai.com, jsierra@openai.com	https://www.linkedin.com/in/javiersierra2102	https://media.licdn.com/dms/image/C4D03AQHEyUg1kGT08Q/profile-displayphoto-shrink_800_800/0/1516504680512?e=1727913600&v=beta&t=3enCmNDBtJ7LxfbW6j1hDD8qNtHjO2jb2XTONECxUXw
dougli	Douglas Li	Douglas	Li	London, England, United Kingdom	37	@ OpenAI UK, previously at Meta	583	401	FALSE	OpenAI	Shift Lab	Facebook	Washington University in St. Louis		Java	Python	JavaScript	FALSE	TRUE	FALSE	douglas.li@openai.com, dli@openai.com	https://www.linkedin.com/in/dougli	https://media.licdn.com/dms/image/D4E03AQETmRyb3_GB8A/profile-displayphoto-shrink_800_800/0/1687996628597?e=1727913600&v=beta&t=HRYGJ4RxsTMcPF1YcSikXlbz99hx353csho3PWT6fOQ
nkartashov	Nick Kartashov	Nick	Kartashov	London, England, United Kingdom	33	Software Engineer	2186	2182	TRUE	OpenAI	Google	DeepMind	St. Petersburg Academic University	Bioinformatics Institute	Teamwork	Java	Haskell	FALSE	FALSE	FALSE	nick.kartashov@openai.com, nkartashov@openai.com	https://www.linkedin.com/in/nkartashov	https://media.licdn.com/dms/image/D4E03AQEjOKxC5UgwWw/profile-displayphoto-shrink_800_800/0/1680706122689?e=1727913600&v=beta&t=m-JnG9nm0zxp1Z7njnInwbCoXyqa3AN-vJZntLfbzQ4

Parameters for LinkedInAccount()

Optional
├── session_file (str):
|    file path to save session cookies, so only one manual login is needed.
|    can use mult profiles this way
|
| For automated login
├── username (str):
|    linkedin account email
│
├── password (str):
|    linkedin account password
|
├── solver_service (SolverType):
|    solves the captcha using the desired service - either CapSolver, or 2Captcha (worse of the two)
|
├── solver_api_key (str):
|    api key for the solver provider
│
├── log_level (int):
|    Controls the verbosity of the runtime printouts
|    (0 prints only errors, 1 is info, 2 is all logs. Default is 0.)

Parameters for scrape_staff()

Optional
├── company_name (str):
|    company identifier on linkedin, will search for that company if that company id does not exist
|    e.g. openai from https://www.linkedin.com/company/openai
|
├── user_id (str):
|    alternative to company_name, provide user identifier on linkedin, will scrape this user's company
|    e.g. dougmcmillon from https://www.linkedin.com/in/dougmcmillon
|
├── search_term (str):
|    staff title to search for
|    e.g. software engineer
|
├── location (str):
|    location the staff resides
|    e.g. london
│
├── extra_profile_data (bool)
|    fetches educations, experiences, skills, certifications (Default false)
│
├── max_results (int):
|    number of staff to fetch, default/max is 1000 for a search imposed by LinkedIn

Parameters for scrape_users()

├── user_ids (list):
|    user ids to scrape from
|     e.g. dougmcmillon from https://www.linkedin.com/in/dougmcmillon

LinkedIn notes

- only 1000 max results per search
- extra_profile_data increases runtime by O(n)
- if rate limited, the program will stop scraping
- if using non-browser sign in, turn off 2fa

Staff Schema

Staff
├── Personal Information
│   ├── search_term
│   ├── id
│   ├── name
│   ├── first_name
│   ├── last_name
│   ├── location
│   └── bio
│
├── Professional Details
│   ├── position
│   ├── profile_id
│   ├── profile_link
│   ├── potential_emails
│   └── estimated_age
│
├── Social Connectivity
│   ├── followers
│   ├── connections
│   └── mutuals_count
│
├── Status
│   ├── influencer
│   ├── creator
│   ├── premium
│   └── is_connection
│
├── Visuals
│   └── profile_photo
│
├── Skills
│   ├── name
│   └── endorsements
│
├── Experiences
│   ├── from_date
│   ├── to_date
│   ├── duration
│   ├── title
│   ├── company
│   ├── location
│   └── emp_type
│
├── Certifications
│   ├── title
│   ├── issuer
│   ├── date_issued
│   ├── cert_id
│   └── cert_link
│
└── Educational Background
    ├── years
    ├── school
    └── degree

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Frequently Asked Questions

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Q: Can I get my account banned?
A: It is a possibility, although there are no recorded incidents. Let me know if you are the first.

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Q: Scraped 999 staff members, with 869 hidden LinkedIn Members?
A: It means your LinkedIn account is bad. Not sure how they classify it but unverified email, new account, low connections and a bunch of factors go into it.

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Q: Encountering issues with your queries?
A: If problems persist, submit an issue.