Use LinkedIn Guest-View Profile Data Extractor with Python

Extract names, headlines, work history, education, certifications, honors, volunteer work, projects, and follower counts from public LinkedIn profiles, with optional current-employer enrichment. No login or cookies required.

1. Choose the data you need

Review the published README for supported collection modes, examples, and limits. The recipe below uses the current published input definition.

2. Prepare a source-based input

This JSON contains published prefills and required-field defaults. Review every value for your task before running it; it is not a promise of successful collection.

{
  "enrichCompany": true,
  "includeStatusRows": true,
  "maxSearchResults": 25,
  "profileUrls": [
    "https://www.linkedin.com/in/williamhgates"
  ]
}

Download input.example.json and save your reviewed copy as input.json.

Field	Type	Required	Description
`profileUrls`	array	optional	LinkedIn profile URLs (https://linkedin.com/in/username) or bare usernames. Full URLs, usernames, 'in/username' shorthand and regional subdomains are all accepted. Optional when searchNames is provided.
`searchNames`	array	optional	Optional search-by-name mode: full names (e.g. "Satya Nadella") to find on LinkedIn's public people directory. Every discovered profile is then scraped through the same pipeline and appears with its own searchQuery field. Combine with profileUrls or use alone.
`searchCompany`	string	optional	Optional. When searching by name, keep only candidates whose directory card lists this company (case-insensitive substring).
`searchLocation`	string	optional	Optional. When searching by name, keep only candidates whose directory card lists this location (case-insensitive substring).
`maxSearchResults`	integer	optional	Upper bound on profiles discovered and scraped in search-by-name mode.
`enrichCompany`	boolean	optional	Fetch the current employer's own public LinkedIn company page for extra detail (employee count, size, industry, website, headquarters, logo, specialties, founded year, followers, description). Uses a free public mirror, so it adds no proxy cost. Cached per company within a run.
`includeStatusRows`	boolean	optional	Add one structured status row when a run returns no profiles or only some of the requested profiles. Turn off if you want the dataset to contain profile records only.
`cookies`	string	optional	Optional and entirely unnecessary for the cookieless data. Supply your own LinkedIn session cookies (browser-export JSON, a JSON array of {name,value}, or a raw Cookie header) to additionally fill fields LinkedIn withholds from logged-out visitors — the real headline, exact connection count, and the full Experience list with titles and dates. Use ``cookie`` as an alias accepted for compatibility. Never required; leave empty for the standard cookieless run.

3. Start an Actor run

Set APIFY_TOKEN in your environment. Python 3.10 or newer is sufficient; this recipe uses no third-party packages.

Execution may incur charges. Review current pricing on Apify. The request asks for a 120-second timeout and a charge limit; these settings are subject to Apify’s pricing and do not guarantee an all-inclusive spending cap.

import json
import os
import urllib.request

# Save the schema-derived example as input.json; review and edit it first.
with open("input.json", encoding="utf-8") as stream:
    actor_input = json.load(stream)

token = os.environ["APIFY_TOKEN"]
request = urllib.request.Request(
    "https://api.apify.com/v2/acts/lHu4lm8g5nkseYsIY/runs?timeout=120&maxTotalChargeUsd=0.50",
    data=json.dumps(actor_input).encode("utf-8"),
    headers={"Authorization": "Bearer " + token, "Content-Type": "application/json"},
    method="POST",
)
# This starts a potentially billable run. Do not automatically retry this POST.
with urllib.request.urlopen(request, timeout=40) as response:
    run = json.load(response)["data"]
print("Run ID:", run["id"])
print("Status:", run["status"])
# Inspect and download results in Apify Console once the run succeeds.

4. Inspect the actual results

Open the run in Apify Console and wait for a successful completion. Use the published output schema to locate results and the dataset schema to understand declared views. Missing or optional record fields must not be treated as guaranteed values.

One record per requested profile, with identity, About, followers, connections, work/education links, self-authored sections (certifications, recommendations, languages, services, publications, patents, courses, honors, projects, volunteering, skills), and optional current-employer enrichment.

Questions before you run

Which inputs are required?

No top-level fields are marked required in the published schema. Conditional requirements can still apply; check the README.

What does this guide verify?

The fields, prefills, and schema links are rendered from the published build. This is a usage recipe, not a paid live extraction test. Source availability and collection results can vary.

What if the run request times out?

Check Apify Console before retrying. The first request may already have created a run. Do not automatically repeat a run-creation POST.

Open on Apify Full Actor reference

Generated from source build 0PUenpBM33btMM7BP and its README and schemas. Source changes regenerate this guide; no third-party editorial claims are inferred.