Nimbryxo Studio

Use B2B Lead Discovery by Job Title & Location with Python

Find public LinkedIn profiles by job title, location, or company using cookieless web search. Returns names, best-effort titles and companies, locations when shown, canonical profile URLs, and quality flags. No verified emails or phone numbers.

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.

{
  "jobTitles": [
    "CEO"
  ],
  "maxLeads": 1
}

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

FieldTypeRequiredDescription
jobTitlesarrayrequiredJob titles to search for (e.g. 'Software Engineer', 'CEO', 'Marketing Manager'). Each title generates a separate search query.
locationsarrayoptionalLocations to target (e.g. 'New York', 'California', 'United States'). Leave empty to search globally.
companyNamesarrayoptionalSpecific companies to target (max 5). Leave empty to search all companies.
maxLeadsintegeroptionalMaximum number of leads to return (1-100).
includeEmailGuessbooleanoptionalAdd a best-effort email guess derived from name + company domain. Guesses are NOT verified and may be wrong. Off by default.
proxyConfigurationobjectoptionalOptional Apify proxy configuration. Yahoo may block datacenter IPs.

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/br0MlYQ8QWIsOvZaX/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.

B2B leads with name, job title, company, LinkedIn profile, location, and data-quality flags.

Questions before you run

Which inputs are required?

The published required fields are jobTitles

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.

Generated from source build 7RJl92cbfyYuYVKbK and its README and schemas. Source changes regenerate this guide; no third-party editorial claims are inferred.