jobquest 0.1.12

Stealth job scraper for LinkedIn, Indeed & Glassdoor — powered by Scrapling

JobQuest

A Python library that scrapes real job postings from LinkedIn, Indeed, and Glassdoor — and actually gets results back instead of 403 errors.

Built on top of Scrapling for Chrome-level TLS fingerprinting and Cloudflare bypass. Every request looks like it came from a real browser, because under the hood it basically did.

Why this exists

Most job scraping libraries break within weeks. Cloudflare updates its bot detection, LinkedIn starts rate-limiting harder, Glassdoor changes its GraphQL schema — and suddenly you're staring at empty DataFrames.

JobQuest handles this with stealth-first defaults:

• Chrome TLS fingerprinting via curl_cffi — your requests have the same TLS signature as Chrome 138
• Cloudflare bypass via Scrapling's StealthyFetcher when needed (full headless Chromium)
• Realistic headers generated by browserforge — not hardcoded strings from 2023
• Automatic fallback — if stealth isn't installed, it falls back to requests/tls_client

Install

pip install jobquest

Quick start

from jobquest import scrape_jobs

jobs = scrape_jobs(
    site_name=["linkedin", "indeed", "glassdoor"],
    search_term="AI Engineer",
    location="Germany",
    results_wanted=25,
    country_indeed="germany",
)

print(f"{len(jobs)} jobs found")
print(jobs[["title", "company", "location"]])

That's it. Returns a Pandas DataFrame with all the job data you'd expect.

What you get back

Each row in the DataFrame has:

Column	Description
title	Job title
company	Company name
location	City, state, country
job_url	Link to the posting
date_posted	When it was listed
description	Full job description (markdown by default)
salary_source	Where salary info came from
min_amount / max_amount	Salary range
is_remote	Remote or not
job_type	Full-time, part-time, contract, etc.
company_url	Company page link
emails	Contact emails found in the description

Plus site-specific fields like job_level, job_function, and more.

Supported sites

Site	Status	Notes
LinkedIn	Working	Guest API, no login needed
Indeed	Working	GraphQL API, mobile app headers
Glassdoor	Working	GraphQL API, auto CSRF token

All the options

from jobquest import scrape_jobs

jobs = scrape_jobs(
    site_name="linkedin",              # or ["linkedin", "indeed", "glassdoor"]
    search_term="machine learning",
    location="Berlin",
    distance=50,                       # km radius
    is_remote=True,
    job_type="fulltime",               # fulltime, parttime, contract, internship
    easy_apply=True,                   # LinkedIn/Glassdoor easy apply filter
    results_wanted=50,
    country_indeed="germany",          # for Indeed's country-specific API
    hours_old=72,                      # only jobs posted in last 72 hours
    linkedin_fetch_description=True,   # fetch full descriptions (slower)
    description_format="markdown",     # markdown, html, or plain
    enforce_annual_salary=True,        # normalize all salaries to yearly
    proxies=["http://user:pass@proxy:8080"],
    verbose=2,                         # 0=errors, 1=warnings, 2=info
)

How the stealth works

JobQuest uses a two-tier approach:

Tier 1 -- StealthSession (default for all requests) Every HTTP request goes through Scrapling's FetcherSession, which uses curl_cffi to impersonate Chrome's TLS fingerprint. Headers are generated by browserforge to match real browser patterns. This is enough for LinkedIn, Indeed, and most API calls.

Tier 2 -- StealthyFetcher (for Cloudflare-protected pages) When a site puts up a Cloudflare challenge (like Glassdoor's CSRF page), JobQuest launches a real headless Chromium browser via patchright to solve it. Cookies from that session get transferred back to the lighter HTTP session for subsequent requests.

If scrapling isn't installed, everything falls back to requests + tls_client -- the same approach most job scrapers use. You just lose the stealth advantage.

Using proxies

jobs = scrape_jobs(
    site_name="linkedin",
    search_term="data engineer",
    proxies=["http://user:pass@proxy1:8080", "socks5://proxy2:1080"],
)

Proxies rotate automatically between requests.

Export to CSV / Excel

import csv

jobs.to_csv("jobs.csv", quoting=csv.QUOTE_NONNUMERIC, escapechar="\\", index=False)
jobs.to_excel("jobs.xlsx", index=False)

Requirements

• Python 3.10+
• The stealth stack installs automatically: scrapling, curl_cffi, browserforge, patchright, playwright

License

MIT