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⇱ Bulk Linkedin Email Finder⚡ $0.8/1K Emails, Super Cheap. · Apify


👁 Bulk Linkedin Email Finder⚡ $0.8/1K Emails, Super Cheap. avatar

Bulk Linkedin Email Finder⚡ $0.8/1K Emails, Super Cheap.

Pricing

from $0.60 / 1,000 emails

Go to Apify Store

Bulk Linkedin Email Finder⚡ $0.8/1K Emails, Super Cheap.

|Input: linkedIn| |Output: Name, Email, Title, Company, etc. In Bulk| Perfect for Email campaigns, Data Enrichment, Linkedin/Linkedin sales nav Leads. ✅Forget Instantly.ai, apollo.io, and hunter.io, they are all to break the Bank.

Pricing

from $0.60 / 1,000 emails

Rating

4.6

(9)

Developer

👁 Sniper Coder

Sniper Coder

Maintained by Community

Actor stats

44

Bookmarked

1.8K

Total users

383

Monthly active users

9.7 hours

Issues response

8 days ago

Last modified

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JavaScript Crawlee & CheerioCrawler Actor Template

This template example was built with Crawlee to scrape data from a website using Cheerio wrapped into CheerioCrawler.

Quick Start

Once you've installed the dependencies, start the Actor:

$apify run

Once your Actor is ready, you can push it to the Apify Console:

apify login # first, you need to log in if you haven't already done so
apify push

Project Structure

.actor/
├── actor.json # Actor config: name, version, env vars, runtime settings
├── dataset_schena.json # Structure and representation of data produced by an Actor
├── input_schema.json # Input validation & Console form definition
└── output_schema.json # Specifies where an Actor stores its output
src/
└── main.js # Actor entry point and orchestrator
storage/ # Local storage (mirrors Cloud during development)
├── datasets/ # Output items (JSON objects)
├── key_value_stores/ # Files, config, INPUT
└── request_queues/ # Pending crawl requests
Dockerfile # Container image definition

For more information, see the Actor definition documentation.

How it works

This code is a JavaScript script that uses Cheerio to scrape data from a website. It then stores the website titles in a dataset.

  • The crawler starts with URLs provided from the input startUrls field defined by the input schema. Number of scraped pages is limited by maxPagesPerCrawl field from the input schema.
  • The crawler uses requestHandler for each URL to extract the data from the page with the Cheerio library and to save the title and URL of each page to the dataset. It also logs out each result that is being saved.

What's included

  • Apify SDK - toolkit for building Actors
  • Crawlee - web scraping and browser automation library
  • Input schema - define and easily validate a schema for your Actor's input
  • Dataset - store structured data where each object stored has the same attributes
  • Cheerio - a fast, flexible & elegant library for parsing and manipulating HTML and XML
  • Proxy configuration - rotate IP addresses to prevent blocking

Resources

Creating Actors with templates

Getting started

For complete information see this article. In short, you will:

  1. Build the Actor
  2. Run the Actor

Pull the Actor for local development

If you would like to develop locally, you can pull the existing Actor from Apify console using Apify CLI:

  1. Install apify-cli

    Using Homebrew

    $brew install apify-cli

    Using NPM

    $npm-ginstall apify-cli
  2. Pull the Actor by its unique <ActorId>, which is one of the following:

    • unique name of the Actor to pull (e.g. "apify/hello-world")
    • or ID of the Actor to pull (e.g. "E2jjCZBezvAZnX8Rb")

    You can find both by clicking on the Actor title at the top of the page, which will open a modal containing both Actor unique name and Actor ID.

    This command will copy the Actor into the current directory on your local machine.

    $apify pull <ActorId>

Documentation reference

To learn more about Apify and Actors, take a look at the following resources:

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