# Behance Projects Scraper (`headlessagent/behance-projects-scraper`) Actor

This Apify Actor extracts project data from Behance profiles based on a given username. It's designed for efficient data collection, handling pagination and offering flexible proxy options

- **URL**: https://apify.com/headlessagent/behance-projects-scraper.md
- **Developed by:** [Headless Agent](https://apify.com/headlessagent) (community)
- **Categories:** Automation, Social media, Other
- **Stats:** 10 total users, 1 monthly users, 3.7% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $2.60 / 1,000 results

This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.

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

## Behance Projects Scraper

This Apify Actor extracts project data from Behance profiles based on a given username. It's designed for efficient data collection, handling pagination and offering flexible proxy options.

### Features

- Extracts all projects from a specified Behance username.
- Retrieves comprehensive project details including covers, features, fields, owners, and statistics.
- Supports resuming scrapes from a specific cursor position.
- Offers optional proxy usage for enhanced anonymity and bypass of rate limits.
- Outputs structured JSON for easy integration and analysis.

### Input

The Actor expects a JSON input with the following fields:

```json
{
  "username": "designerpreis",
  "cursor": "",
  "proxyUrl": ""
}
```

- **`username`** (string, required):
  The Behance username to scrape projects from.
  Example: `"designerpreis"`

- **`cursor`** (string, optional):
  The cursor to start scraping from. Useful for resuming interrupted scrapes.
  If not provided, the scraper starts from the beginning.
  Example: `"MTI="`

- **`proxyUrl`** (string, optional):
  A single custom proxy URL to use (e.g., `http://user:pass@host:port`).
  If provided, the Actor will use this proxy for all requests.
  **Important:** Only use a single host, not a rotating proxy, as it may cause errors with multi-page scraping.

### Output

For every project found on the Behance profile, the output dataset (`behance_projects_<username>`) will contain an object with detailed fields.

**Example Project Output (simplified):**

```json
{
	"__typename": "Project",
	"covers": {
		"size_202": {
			"url": "https://mir-s3-cdn-cf.behance.net/projects/202/92665c210524379.Y3JvcCwxMzgwLDEwODAsMjcwLDA.png"
		},
		"size_404": {
			"url": "https://mir-s3-cdn-cf.behance.net/projects/404/92665c210524379.Y3JvcCwxMzgwLDEwODAsMjcwLDA.png"
		},
		"size_808": {
			"url": "https://mir-s3-cdn-cf.behance.net/projects/808/92665c210524379.Y3JvcCwxMzgwLDEwODAsMjcwLDA.png"
		}
	},
	"features": [],
	"fields": [
		{
			"id": 3,
			"label": "Animation",
			"slug": "Animation",
			"url": "/search/projects?field=3"
		},
		{
			"id": 145,
			"label": "3D Art",
			"slug": "3D Art",
			"url": "/search/projects?field=145"
		},
		{
			"id": 241,
			"label": "CGI",
			"slug": "CGI",
			"url": "/search/projects?field=241"
		}
	],
	"hasMatureContent": false,
	"id": 210524379,
	"sourceFiles": [],
	"matureAccess": "allowed",
	"modifiedOn": 1744365623,
	"name": "Reel 2024",
	"owners": [
		{
			"displayName": "Everton Rios Marques",
			"hasPremiumAccess": false,
			"id": 3367079,
			"isFollowing": false,
			"isProfileOwner": false,
			"location": "São Paulo, Brazil",
			"locationUrl": "https://www.behance.net/search/users?country=BR&city=S%C3%A3o+Paulo",
			"url": "https://www.behance.net/evertonrios",
			"username": "evertonrios",
			"isMessageButtonVisible": true,
			"availabilityInfo": {
				"availabilityTimeline": "within_next_few_weeks",
				"isAvailableFullTime": false,
				"isAvailableFreelance": true,
				"hiringTimeline": {
					"key": "now",
					"label": "Now"
				}
			},
			"creatorPro": {
				"isActive": false,
				"initialSubscriptionDate": null
			},
			"images": {
				"size_50": {
					"url": "https://mir-s3-cdn-cf.behance.net/user/50/a0827a3367079.6149e6d5dd8f7.jpg"
				}
			}
		}
	],
	"publishedOn": 1729268209,
	"privacyLevel": "PUBLIC",
	"stats": {
		"appreciations": {
			"all": 458
		},
		"views": {
			"all": 5279
		},
		"comments": {
			"all": 21
		}
	},
	"slug": "Reel-2024",
	"tools": [
		{
			"id": 5704,
			"title": "Maxon Cinema 4D",
			"category": "9",
			"categoryLabel": "Software",
			"categoryId": 9,
			"approved": 1,
			"url": "/search/projects?tools=5704",
			"backgroundColor": null
		},
		{
			"id": 403683929,
			"title": "Redshift Render",
			"category": "9",
			"categoryLabel": "Software",
			"categoryId": 9,
			"approved": 1,
			"url": "/search/projects?tools=403683929",
			"backgroundColor": null
		},
		{
			"id": 185681947,
			"title": "Adobe After Effects",
			"category": "9",
			"categoryLabel": "Software",
			"categoryId": 9,
			"approved": 1,
			"url": "/search/projects?tools=185681947",
			"backgroundColor": "#00005B"
		}
	],
	"url": "https://www.behance.net/gallery/210524379/Reel-2024"
}
```

# Actor input Schema

## `username` (type: `string`):

The Behance username to scrape projects from.

## `cursor` (type: `string`):

The cursor to start scraping from (optional).

## `proxyUrl` (type: `string`):

A single custom proxy URL to use (e.g., 'http://user:pass@proxy.com:8080'). Only use a single host, not a rotating proxy, as it may cause errors with multi-page scraping.

## Actor input object example

```json
{
  "username": "maciejpaluszny"
}
```

# 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 = {
    "username": "maciejpaluszny"
};

// Run the Actor and wait for it to finish
const run = await client.actor("headlessagent/behance-projects-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 = { "username": "maciejpaluszny" }

# Run the Actor and wait for it to finish
run = client.actor("headlessagent/behance-projects-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 '{
  "username": "maciejpaluszny"
}' |
apify call headlessagent/behance-projects-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,headlessagent/behance-projects-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/9S1B1WWh9cO2RmAc4/builds/Uep0iEWhfjnfgvEut/openapi.json