Behance Projects Scraper

Behance Projects Scraper collects detailed project data from public Behance profiles using a username-based approach. It helps creators, analysts, and researchers transform portfolio information into structured datasets for analysis, archiving, or integration workflows.

     

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Introduction

This project extracts comprehensive project-level data from Behance user profiles, handling pagination and large portfolios with consistency and accuracy. It solves the challenge of manually collecting structured portfolio data from Behance. It is built for designers, agencies, recruiters, analysts, and developers working with creative datasets.

Portfolio Data Extraction at Scale

• Retrieves all projects published under a single Behance username
• Handles pagination using cursor-based continuation
• Captures rich metadata including media, tools, stats, and owners
• Outputs clean, structured JSON ready for analysis or storage

Features

Feature	Description
Full Profile Coverage	Extracts all projects associated with a Behance username.
Rich Project Metadata	Collects covers, fields, tools, stats, and ownership details.
Cursor Resume Support	Resume interrupted runs from a saved cursor position.
Flexible Proxy Support	Optional single-proxy usage for stable multi-page collection.
Structured Output	Delivers normalized JSON suitable for pipelines and dashboards.

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What Data This Scraper Extracts

Field Name	Field Description
id	Unique project identifier.
name	Project title as displayed on Behance.
slug	URL-friendly project slug.
url	Direct link to the project page.
covers	Image URLs in multiple resolutions.
fields	Creative categories associated with the project.
tools	Software and tools used in the project.
owners	Creator profile and availability information.
stats.views	Total project view count.
stats.appreciations	Number of appreciations received.
stats.comments	Total comment count.
publishedOn	Unix timestamp of publication date.
modifiedOn	Unix timestamp of last update.
privacyLevel	Visibility status of the project.

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Example Output

[
    {
        "__typename": "Project",
        "id": 210524379,
        "name": "Reel 2024",
        "slug": "Reel-2024",
        "url": "https://www.behance.net/gallery/210524379/Reel-2024",
        "publishedOn": 1729268209,
        "modifiedOn": 1744365623,
        "privacyLevel": "PUBLIC",
        "covers": {
            "size_202": {
                "url": "https://mir-s3-cdn-cf.behance.net/projects/202/92665c210524379.png"
            },
            "size_404": {
                "url": "https://mir-s3-cdn-cf.behance.net/projects/404/92665c210524379.png"
            }
        },
        "fields": [
            {
                "id": 3,
                "label": "Animation"
            },
            {
                "id": 145,
                "label": "3D Art"
            }
        ],
        "tools": [
            {
                "title": "Adobe After Effects",
                "categoryLabel": "Software"
            }
        ],
        "stats": {
            "views": {
                "all": 5279
            },
            "appreciations": {
                "all": 458
            },
            "comments": {
                "all": 21
            }
        }
    }
]

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Directory Structure Tree

Behance Projects Scraper/
├── src/
│   ├── main.py
│   ├── handlers/
│   │   ├── profile_fetcher.py
│   │   ├── project_parser.py
│   │   └── cursor_manager.py
│   ├── utils/
│   │   ├── http_client.py
│   │   └── validators.py
│   └── config/
│       └── settings.example.json
├── data/
│   ├── sample_input.json
│   └── sample_output.json
├── requirements.txt
└── README.md

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Use Cases

• Recruiters use it to analyze designer portfolios, so they can shortlist candidates faster.
• Agencies use it to archive client work, so they can maintain structured records.
• Market researchers use it to study creative trends, so they can generate insights.
• Developers use it to feed portfolio data into apps, so they can build creative platforms.
• Designers use it to back up their work, so they retain long-term access to projects.

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FAQs

Can I resume a stopped extraction? Yes, by providing a cursor value, the scraper continues from the last processed position without duplicating data.

Does it support large portfolios? Yes, the cursor-based pagination ensures stable extraction even for profiles with hundreds of projects.

Is proxy usage required? No, proxies are optional. If used, a single static proxy is recommended for consistency.

What output format is generated? The scraper outputs structured JSON with normalized fields suitable for analysis or integration.

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Performance Benchmarks and Results

Primary Metric: Processes an average of 40–60 projects per minute depending on media density.

Reliability Metric: Maintains over 98% successful project retrieval across multi-page profiles.

Efficiency Metric: Low memory footprint with streaming-based pagination handling.

Quality Metric: Captures complete project metadata including media, tools, and engagement stats.

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