Is it legal to scrape Behance?

Scraping public data on Behance is generally legal for non-commercial or research purposes as long as you respect copyright laws. However, you should always check Adobe's Terms of Service and ensure you are not redistributing artists' work as your own.

Does Behance have an official public API?

Adobe officially retired the public Behance API for new users several years ago. While some legacy integrations still exist, web scraping is currently the most effective method for large-scale data extraction.

How do I avoid getting blocked by Behance?

To avoid blocks, use a scraper with built-in stealth features that can bypass DataDome. Additionally, employing residential proxies and simulating human-like scrolling will help you stay under the radar.

What format will the extracted data be in?

Using tools like Automatio, you can export your Behance data into CSV, JSON, or Excel formats. JSON is highly recommended for Behance as it effectively handles nested data like project tags and multiple images.

Can I scrape high-resolution images from Behance?

Yes, but you must navigate to the specific project page and extract the direct image source from the CDN. Since Behance uses lazy-loading, your scraper must trigger the image to load before capturing the URL.

What proxies work best for Behance?

Residential proxies are the most reliable choice because they appear as genuine home users. Data center proxies are often flagged instantly by Adobe's security layers and should generally be avoided for this platform.

How often should I scrape Behance for trend analysis?

A weekly or bi-weekly scraping schedule is usually sufficient to capture significant shifts in creative trends. If you are monitoring specific high-volume agencies, a daily scrape may be more appropriate to catch new uploads.

Do I need to be logged in to scrape Behance?

No, most project data and creative profiles are publicly visible. It is safer to scrape without logging in to prevent your personal Adobe account from being flagged or restricted.

How to Scrape Behance: A Step-by-Step Guide for Creative Data Extraction

Learn how to scrape Behance projects, creative portfolios, and talent data. This guide covers anti-bot bypass, JavaScript rendering, and automated extraction.

Start Scraping Free

behance.netHard

Coverage:GlobalNorth AmericaEuropeAsia

Available Data10 fields

TitlePriceLocationDescriptionImagesSeller InfoContact InfoPosting DateCategoriesAttributes

All Extractable Fields

Project TitleCreative Owner NameProfile URLProject DescriptionAppreciation CountView CountComment CountProject TagsCreative FieldsTools UsedImage Source URLsOwner LocationFollower CountPublished Date

Technical Requirements

JavaScript Required

No Login

Has Pagination

No Official API

Anti-Bot Protection Detected

CloudflareRate LimitingIP BlockingUser-Agent FilteringAI Bot Blocking

About Behance

Learn what Behance offers and what valuable data can be extracted from it.

Behance is the world's largest creative network, owned by Adobe, serving as a premier social media platform and portfolio hosting service for creators. It allows professionals across graphic design, photography, illustration, and UI/UX to showcase their work through project-based galleries. The platform is deeply integrated with the Adobe Creative Cloud ecosystem, making it the primary hub for creative talent globally.

The platform contains a massive repository of structured data, including project categories, specific tools used (like Photoshop or Figma), and detailed professional metadata. Each project listing usually includes high-resolution images, descriptions, view counts, appreciations, and direct links to the creator's profile. This makes it an essential resource for companies looking to understand visual trends or source high-end creative talent.

Scraping Behance is particularly valuable for competitive intelligence, trend forecasting in the design industry, and identifying top-tier talent for high-end creative roles. Because the data is rich with technical attributes, such as software used and project tags, it provides insights into how the creative industry is evolving and which tools are dominating the professional landscape.

Why Scrape Behance?

Discover the business value and use cases for extracting data from Behance.

Creative Talent Sourcing

Recruiters and creative agencies can build extensive databases of designers, architects, and photographers by filtering for specific skills and high engagement metrics.

Design Trend Forecasting

By analyzing the 'Curated' and 'Most Appreciated' galleries, businesses can identify emerging visual aesthetics and color palettes before they go mainstream.

Lead Gen for Design Tools

Extracting the 'Tools Used' metadata allows software companies to identify and target users of specific platforms like Figma, Cinema 4D, or Adobe Creative Cloud.

Competitive Brand Monitoring

Agencies can track the portfolios of competing firms to see their latest client collaborations and understand their project delivery style and technical capabilities.

AI Model Training Data

Behance provides a high-quality source of professionally tagged images and detailed descriptions ideal for training or fine-tuning generative AI models.

Market Sentiment Analysis

Scraping comment sections and appreciation-to-view ratios helps brands understand how specific creative directions are being received by a global professional audience.

Scraping Challenges

Technical challenges you may encounter when scraping Behance.

Advanced DataDome Protection

Behance employs DataDome to identify and block automated traffic, requiring advanced browser fingerprinting and stealth techniques to bypass.

JavaScript-Heavy Architecture

The site is a Single Page Application (SPA) where content is rendered dynamically, making traditional static HTML parsers nearly useless.

Infinite Scroll Loading

Galleries load projects as the user scrolls down, which requires a scraper capable of simulating real-time human interaction to reach deep results.

CDN Image Protection

Images are served through Adobe's CDN with specific resolution parameters and lazy-loading, making it difficult to capture high-res source URLs without interaction.

Scrape Behance with AI

No coding required. Extract data in minutes with AI-powered automation.

How It Works

Describe What You Need

Tell the AI what data you want to extract from Behance. Just type it in plain language — no coding or selectors needed.

AI Extracts the Data

Our artificial intelligence navigates Behance, handles dynamic content, and extracts exactly what you asked for.

Get Your Data

Receive clean, structured data ready to export as CSV, JSON, or send directly to your apps and workflows.

Why Use AI for Scraping

Native Stealth Technology: Automatio automatically handles complex bot detection systems like DataDome, ensuring your scraper remains undetected while gathering data.

No-Code Infinite Scrolling: Easily configure a scroll-to-bottom action to capture thousands of project listings from search results without writing a single line of code.

Visual Data Mapping: Point and click to select complex data points like appreciation counts, creator locations, and tool tags from the Behance UI.

Automated Cloud Scheduling: Set your Behance scrapers to run weekly or monthly to track new creative trends and talent updates without manual intervention.

Dynamic Data Integration: Sync your scraped creative data directly with Google Sheets or your own CRM via Webhooks for immediate recruitment or marketing outreach.

Start Scraping Free

No credit card requiredFree tier availableNo setup needed

No-Code Web Scrapers for Behance

Point-and-click alternatives to AI-powered scraping

Several no-code tools like Browse.ai, Octoparse, Axiom, and ParseHub can help you scrape Behance. These tools use visual interfaces to select elements, but they come with trade-offs compared to AI-powered solutions.

Typical Workflow with No-Code Tools

Install browser extension or sign up for the platform

Navigate to the target website and open the tool

Point-and-click to select data elements you want to extract

Configure CSS selectors for each data field

Set up pagination rules to scrape multiple pages

Handle CAPTCHAs (often requires manual solving)

Configure scheduling for automated runs

Export data to CSV, JSON, or connect via API

Common Challenges

Learning curve

Understanding selectors and extraction logic takes time

Selectors break

Website changes can break your entire workflow

Dynamic content issues

JavaScript-heavy sites often require complex workarounds

CAPTCHA limitations

Most tools require manual intervention for CAPTCHAs

IP blocking

Aggressive scraping can get your IP banned

Code Examples

import requests
from bs4 import BeautifulSoup

# Note: This will likely trigger Cloudflare if run from a data center IP
url = "https://www.behance.net/search/projects?field=graphic+design"
headers = {
    "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/119.0.0.0 Safari/537.36"
}

try:
    response = requests.get(url, headers=headers, timeout=10)
    if response.status_code == 200:
        soup = BeautifulSoup(response.text, 'html.parser')
        # Behance renders content via JS; static scraping will find limited data
        projects = soup.find_all('div', class_='ProjectCover-root-167')
        for project in projects:
            title = project.find('a', class_='ProjectCover-title-3_1').text
            print(f"Found Project: {title}")
    else:
        print(f"Blocked or error: {response.status_code}")
except Exception as e:
    print(f"Request failed: {e}")

When to Use

Best for static HTML pages where content is loaded server-side. The fastest and simplest approach when JavaScript rendering isn't required.

Advantages

●Fastest execution (no browser overhead)
●Lowest resource consumption
●Easy to parallelize with asyncio
●Great for APIs and static pages

Limitations

●Cannot execute JavaScript
●Fails on SPAs and dynamic content
●May struggle with complex anti-bot systems

from playwright.sync_api import sync_playwright

def scrape_behance():
    with sync_playwright() as p:
        browser = p.chromium.launch(headless=True)
        page = browser.new_page()
        page.goto("https://www.behance.net/search/projects?field=architecture")
        # Wait for dynamic content to load
        page.wait_for_selector(".ProjectCover-root-167")
        # Scroll down to trigger lazy loading
        page.mouse.wheel(0, 5000)
        page.wait_for_timeout(2000)
        projects = page.query_selector_all(".ProjectCover-root-167")
        data = []
        for p_elem in projects:
            title = p_elem.query_selector(".ProjectCover-title-3_1").inner_text()
            owner = p_elem.query_selector(".ProjectCover-username-28M").inner_text()
            data.append({"title": title, "owner": owner})
        print(data)
        browser.close()

scrape_behance()

When to Use

Use when content loads dynamically via JavaScript, or when you need to interact with the page (clicks, scrolls, form fills). Handles modern anti-bot detection better.

Advantages

●Executes JavaScript like a real browser
●Handles SPAs and dynamic content
●Better anti-bot evasion with stealth plugins
●Can take screenshots and PDFs

Limitations

●Slower than HTTP requests
●Higher memory/CPU usage
●More complex to set up

import scrapy
from scrapy_playwright.page import PageMethod

class BehanceSpider(scrapy.Spider):
    name = "behance"
    start_urls = ["https://www.behance.net/search/projects?field=interaction"]

    def start_requests(self):
        for url in self.start_urls:
            yield scrapy.Request(
                url,
                meta={"playwright": True, "playwright_page_methods": [
                    PageMethod("wait_for_selector", ".ProjectCover-root-167"),
                ]},
            )

    def parse(self, response):
        for project in response.css(".ProjectCover-root-167"):
            yield {
                "title": project.css(".ProjectCover-title-3_1::text").get(),
                "url": project.css("a::attr(href)").get(),
            }

When to Use

Ideal for large-scale crawling projects that need to scrape thousands of pages. Built-in support for rate limiting, retries, and data pipelines.

Advantages

●Built for scale (millions of pages)
●Automatic request throttling
●Built-in data export pipelines
●Middleware system for proxies/headers

Limitations

●Steeper learning curve
●Overkill for small projects
●No native JavaScript rendering

const puppeteer = require('puppeteer');

(async () => {
  const browser = await puppeteer.launch();
  const page = await browser.newPage();
  await page.goto('https://www.behance.net/search/projects?field=branding');
  // Ensure content is loaded
  await page.waitForSelector('.ProjectCover-content-3Z_');
  const projects = await page.evaluate(() => {
    return Array.from(document.querySelectorAll('.ProjectCover-root-167')).map(el => ({
      title: el.querySelector('.ProjectCover-title-3_1')?.innerText,
      owner: el.querySelector('.ProjectCover-username-28M')?.innerText
    }));
  });
  console.log(projects);
  await browser.close();
})();

When to Use

Choose this if you're in a Node.js/JavaScript ecosystem or need tight integration with frontend tools. Similar capabilities to Playwright.

Advantages

●Native JavaScript/TypeScript support
●Chrome DevTools Protocol access
●Large ecosystem and community
●Good for JS-heavy projects

Limitations

●Chrome-only (vs Playwright's multi-browser)
●Similar overhead to Playwright
●Less mature stealth options

How to Scrape Behance with Code

Python + Requests

import requests
from bs4 import BeautifulSoup

# Note: This will likely trigger Cloudflare if run from a data center IP
url = "https://www.behance.net/search/projects?field=graphic+design"
headers = {
    "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/119.0.0.0 Safari/537.36"
}

try:
    response = requests.get(url, headers=headers, timeout=10)
    if response.status_code == 200:
        soup = BeautifulSoup(response.text, 'html.parser')
        # Behance renders content via JS; static scraping will find limited data
        projects = soup.find_all('div', class_='ProjectCover-root-167')
        for project in projects:
            title = project.find('a', class_='ProjectCover-title-3_1').text
            print(f"Found Project: {title}")
    else:
        print(f"Blocked or error: {response.status_code}")
except Exception as e:
    print(f"Request failed: {e}")

Python + Playwright

from playwright.sync_api import sync_playwright

def scrape_behance():
    with sync_playwright() as p:
        browser = p.chromium.launch(headless=True)
        page = browser.new_page()
        page.goto("https://www.behance.net/search/projects?field=architecture")
        # Wait for dynamic content to load
        page.wait_for_selector(".ProjectCover-root-167")
        # Scroll down to trigger lazy loading
        page.mouse.wheel(0, 5000)
        page.wait_for_timeout(2000)
        projects = page.query_selector_all(".ProjectCover-root-167")
        data = []
        for p_elem in projects:
            title = p_elem.query_selector(".ProjectCover-title-3_1").inner_text()
            owner = p_elem.query_selector(".ProjectCover-username-28M").inner_text()
            data.append({"title": title, "owner": owner})
        print(data)
        browser.close()

scrape_behance()

Python + Scrapy

import scrapy
from scrapy_playwright.page import PageMethod

class BehanceSpider(scrapy.Spider):
    name = "behance"
    start_urls = ["https://www.behance.net/search/projects?field=interaction"]

    def start_requests(self):
        for url in self.start_urls:
            yield scrapy.Request(
                url,
                meta={"playwright": True, "playwright_page_methods": [
                    PageMethod("wait_for_selector", ".ProjectCover-root-167"),
                ]},
            )

    def parse(self, response):
        for project in response.css(".ProjectCover-root-167"):
            yield {
                "title": project.css(".ProjectCover-title-3_1::text").get(),
                "url": project.css("a::attr(href)").get(),
            }

Node.js + Puppeteer

const puppeteer = require('puppeteer');

(async () => {
  const browser = await puppeteer.launch();
  const page = await browser.newPage();
  await page.goto('https://www.behance.net/search/projects?field=branding');
  // Ensure content is loaded
  await page.waitForSelector('.ProjectCover-content-3Z_');
  const projects = await page.evaluate(() => {
    return Array.from(document.querySelectorAll('.ProjectCover-root-167')).map(el => ({
      title: el.querySelector('.ProjectCover-title-3_1')?.innerText,
      owner: el.querySelector('.ProjectCover-username-28M')?.innerText
    }));
  });
  console.log(projects);
  await browser.close();
})();

What You Can Do With Behance Data

Explore practical applications and insights from Behance data.

Creative Trend Analysis

Agencies can track which creative fields and design styles are gaining the most appreciations to forecast industry trends.

How to implement:

1Scrape 5,000 top projects monthly based on specific creative fields.
2Group data by creative category and appreciation-to-view ratio.
3Visualize growth and engagement over time to identify emerging aesthetics.

Use Automatio to extract data from Behance and build these applications without writing code.

More than just prompts

Supercharge your workflow with AI Automation

Automatio combines the power of AI agents, web automation, and smart integrations to help you accomplish more in less time.

AI Agents

Web Automation

Smart Workflows

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Pro Tips for Scraping Behance

Expert advice for successfully extracting data from Behance.

Intercept Internal JSON API

Watch the Network tab for calls to 'api.behance.net'; these endpoints often return structured JSON which is much easier to scrape than HTML.

Parse the be-state Script

Check the page source for the 'be-state' script tag, which frequently contains a pre-rendered JSON object of the page's current data.

Modify CDN URL Parameters

You can often get higher-resolution versions of images by manually changing the path segments in the image URL (e.g., from /404/ to /max_1200/).

Use Residential IP Proxies

Adobe's servers frequently block data center IP ranges; using residential proxies mimics real home user traffic and dramatically increases success rates.

Randomize Scroll Behavior

Vary your scrolling speed and add random pauses to your scraping workflow to avoid triggering behavioral detection systems.

Testimonials

What Our Users Say

Join thousands of satisfied users who have transformed their workflow

Jonathan Kogan

Co-Founder/CEO, rpatools.io

Automatio is one of the most used for RPA Tools both internally and externally. It saves us countless hours of work and we realized this could do the same for other startups and so we choose Automatio for most of our automation needs.

Mohammed Ibrahim

CEO, qannas.pro

I have used many tools over the past 5 years, Automatio is the Jack of All trades.. !! it could be your scraping bot in the morning and then it becomes your VA by the noon and in the evening it does your automations.. its amazing!

Ben Bressington

CTO, AiChatSolutions

Automatio is fantastic and simple to use to extract data from any website. This allowed me to replace a developer and do tasks myself as they only take a few minutes to setup and forget about it. Automatio is a game changer!

Sarah Chen

Head of Growth, ScaleUp Labs

We've tried dozens of automation tools, but Automatio stands out for its flexibility and ease of use. Our team productivity increased by 40% within the first month of adoption.

David Park

Founder, DataDriven.io

The AI-powered features in Automatio are incredible. It understands context and adapts to changes in websites automatically. No more broken scrapers!

Emily Rodriguez

Marketing Director, GrowthMetrics

Automatio transformed our lead generation process. What used to take our team days now happens automatically in minutes. The ROI is incredible.

Jonathan Kogan

Co-Founder/CEO, rpatools.io

Mohammed Ibrahim

CEO, qannas.pro

Ben Bressington

CTO, AiChatSolutions

Sarah Chen

Head of Growth, ScaleUp Labs

We've tried dozens of automation tools, but Automatio stands out for its flexibility and ease of use. Our team productivity increased by 40% within the first month of adoption.

David Park

Founder, DataDriven.io

The AI-powered features in Automatio are incredible. It understands context and adapts to changes in websites automatically. No more broken scrapers!

Emily Rodriguez

Marketing Director, GrowthMetrics

Automatio transformed our lead generation process. What used to take our team days now happens automatically in minutes. The ROI is incredible.

Related Web Scraping

Frequently Asked Questions About Behance

Find answers to common questions about Behance

How to Scrape Behance: A Step-by-Step Guide for Creative Data Extraction

About Behance

Why Scrape Behance?

Creative Talent Sourcing

Design Trend Forecasting

Lead Gen for Design Tools

Competitive Brand Monitoring

AI Model Training Data

Market Sentiment Analysis

Scraping Challenges

Advanced DataDome Protection

JavaScript-Heavy Architecture

Infinite Scroll Loading

CDN Image Protection

Scrape Behance with AI

How It Works

Why Use AI for Scraping

How to scrape with AI:

Why use AI for scraping:

No-Code Web Scrapers for Behance

Typical Workflow with No-Code Tools

Common Challenges

No-Code Web Scrapers for Behance

Typical Workflow with No-Code Tools

Common Challenges

Code Examples

How to Scrape Behance with Code

Python + Requests

Python + Playwright

Python + Scrapy

Node.js + Puppeteer

What You Can Do With Behance Data

Creative Trend Analysis

Lead Gen for Design Tools

Recruitment Sourcing at Scale

Visual Competitor Benchmarking

What You Can Do With Behance Data

Supercharge your workflow with AI Automation

Pro Tips for Scraping Behance

Intercept Internal JSON API

Parse the be-state Script

Modify CDN URL Parameters

Use Residential IP Proxies

Randomize Scroll Behavior

What Our Users Say

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Frequently Asked Questions About Behance

Is it legal to scrape Behance?

Does Behance have an official public API?

How do I avoid getting blocked by Behance?

What format will the extracted data be in?

Can I scrape high-resolution images from Behance?

What proxies work best for Behance?

How often should I scrape Behance for trend analysis?

Do I need to be logged in to scrape Behance?