# Greenhouse (`dlandberg/greenhouse`) Actor

Scrape jobs posted from companies that use Greenhouse as their applicant tracking software. Easily get content, salary ranges, location, and much more.

- **URL**: https://apify.com/dlandberg/greenhouse.md
- **Developed by:** [Dmitry Landberg](https://apify.com/dlandberg) (community)
- **Categories:** Jobs
- **Stats:** 144 total users, 0 monthly users, 100.0% runs succeeded, 7 bookmarks
- **User rating**: No ratings yet

## Pricing

from $5.00 / 1,000 results

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

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

## 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

## What does Greenhouse Scraper do?

Greenhouse Scraper allows you to extract job data from Greenhouse's job listings:
job title, content of the job description, company name, location, salary ranges, department.

### Why scrape Greenhouse

You might want to scrape Job postings in order to:

- Monitor hiring trends for skills and technology gaps
- Create a custom database for available positions
- Automate the job search to speed up and simplify the process
- Salary benchmarking
- Competition tracking

### How to use this Greenhouse scraper?

- Create a free Apify account using your email.
- Open Greenhouse Scraper.
- (Optional) Add the list of companies that you want to scrape.
  If you don't provide the list of companies, the scraper comes with the default list of dozens of companies that use Greenhouse
- (Optional) Add yout OpenAI API Key. It will be used to extract the salary ranges from the job descriptions
- (Optional) Specify the max number of jobs you want to parse per one company. Default is 10.
- (Optional) Specify the job titles you want to scrape. The scraper will do a regex matching on the string provided.
- Click "Start" and wait for the data to be extracted.
- Download your data in JSON, XML, CSV, Excel, or HTML.

### Input schema

The input for Indeed Scraper should be a job position, location and number of results. For a fuller explanation of input in JSON, head over to the input tab.

```
{
    "companies": [
        "affirm",
        "okta"
    ],
    "position_titles": [
        "engineer"
    ],
    "max_jobs": 1,
    "openai_api_key": "<your api key>"
}
```

### Output Example

The results will be wrapped into a dataset which you can find in the Storage tab.
This is a screenshot of the view that you can expect to see
![Greenhouse parser output schema](/assets/output.png)

### Is it legal to scrape Indeed data?

Our scrapers are ethical and do not extract any private user data.
They only extract what the user has chosen to share publicly, on the website.
However, you should be aware that your results could contain personal data.
You should not scrape personal data unless you have a legitimate reason to do so.

If you're unsure whether your reason is legitimate, consult your lawyers.
You should not scrape personal data unless you have a legitimate reason to do so.
If you’re unsure whether your reason is legitimate, consult your lawyers.
You can also read our blog post on the legality of web scraping and ethical scraping.

# Actor input Schema

## `companies` (type: `array`):

Names of companies in downcase, no spaces.

## `position_titles` (type: `array`):

Keywords that you want to capture. For ex. 'engineering', 'engineering manager'

## `max_jobs` (type: `integer`):

Max number of jobs you want to parse for each company

## `openai_api_key` (type: `string`):

Parser uses it for extracting the salary range. It's optional

## Actor input object example

```json
{
  "companies": [
    "affirm",
    "okta"
  ],
  "max_jobs": 10
}
```

# 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 = {
    "companies": [
        "affirm",
        "okta"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("dlandberg/greenhouse").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 = { "companies": [
        "affirm",
        "okta",
    ] }

# Run the Actor and wait for it to finish
run = client.actor("dlandberg/greenhouse").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 '{
  "companies": [
    "affirm",
    "okta"
  ]
}' |
apify call dlandberg/greenhouse --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,dlandberg/greenhouse"
        }
    }
}
```

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/goEzxL1d28Ei1VWRz/builds/BsFzBfz2nS8WvRn0i/openapi.json