# ⚡️ Linkedin Jobs Scraper 🔥 (`oza-dev/linkedin-jobs-scraper`) Actor

LinkedIn Job Scraper is a powerful and reliable automation tool Designed to extract job listings directly from LinkedIn Jobs using advanced search logic and filters. It helps recruiters, job boards, analysts, and HR professionals gather high-quality job data at scale — with over 98% success rate

- **URL**: https://apify.com/oza-dev/linkedin-jobs-scraper.md
- **Developed by:** [Oza Dev](https://apify.com/oza-dev) (community)
- **Categories:** Jobs
- **Stats:** 39 total users, 0 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per usage

This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-usage

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## LinkedIn Jobs Scraper (Apify Actor)

Ce scraper permet d'extraire des offres d'emploi de LinkedIn sans avoir besoin de se connecter. Il est conçu pour être déployé en tant qu'Actor sur la plateforme Apify.

### Fonctionnalités

- **Recherche par mots-clés** : Trouvez des postes spécifiques (ex: "Data Scientist").
- **Localisation flexible** : Filtrez par ville, pays ou région.
- **Filtres avancés** :
  - Date de publication (24h, semaine, mois).
  - Type de travail (Sur site, Remote, Hybride).
  - Niveau d'expérience (Stagiaire, Junior, Senior, etc.).
- **Pagination automatique** : Extrayez autant d'offres que nécessaire (jusqu'à 1000).
- **Exportation facile** : Résultats disponibles en JSON, CSV, Excel, etc. via Apify.

### Paramètres d'entrée

| Champ | Type | Description | Par défaut |
|-------|------|-------------|------------|
| `title` | String | Titre du poste recherché | "Python Developer" |
| `location` | String | Lieu de la recherche | "United States" |
| `rows` | Integer | Nombre d'offres à extraire | 50 |
| `publishedAt` | Enum | Période de publication | "Any time" |
| `workType` | Enum | Type de travail (Remote, etc.) | "Any" |
| `experienceLevel` | Enum | Niveau d'expérience requis | "Any" |

### Données extraites

Pour chaque offre, le scraper récupère :

- Le titre du poste
- Le nom de l'entreprise
- La localisation
- Le lien direct vers l'offre
- La date de publication
- La source (LinkedIn)

### Comment l'utiliser sur Apify

1. Créez un nouvel Actor sur [Apify](https://apify.com).
2. Copiez le contenu de `main.py`, `INPUT_SCHEMA.json`, `requirements.txt` et `Dockerfile`.
3. Déployez et lancez l'Actor avec vos paramètres.

### Notes techniques

Ce scraper utilise l'API publique de LinkedIn (`jobs-guest`), ce qui évite les problèmes de blocage liés aux comptes personnels. Pour des volumes importants, l'utilisation de **proxies résidentiels** Apify est fortement recommandée.

# Actor input Schema

## `title` (type: `string`):

The name of the job (e.g. Web developer).

## `location` (type: `string`):

The location of the job (e.g. Paris, New York).

## `rows` (type: `integer`):

How many rows do you want to display?

## `publishedAt` (type: `string`):

Select time range for job postings.

## `workType` (type: `string`):

Select work type to display.

## `experienceLevel` (type: `string`):

Select the experience levels to be displayed.

## Actor input object example

```json
{
  "title": "Python Developer",
  "location": "United States",
  "rows": 50,
  "publishedAt": "",
  "workType": "",
  "experienceLevel": ""
}
```

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {};

// Run the Actor and wait for it to finish
const run = await client.actor("oza-dev/linkedin-jobs-scraper").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {}

# Run the Actor and wait for it to finish
run = client.actor("oza-dev/linkedin-jobs-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{}' |
apify call oza-dev/linkedin-jobs-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,oza-dev/linkedin-jobs-scraper"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/IbqgHIwXa52OVtMNs/builds/z8c7axaybpAqcTnNT/openapi.json