# Behance Project Search Scraper (`klondikeking/behance-project-scraper`) Actor Scrape Behance projects by search keywords. Extract project titles, creators, thumbnails, appreciation counts, and view counts for design research, competitive analysis, and talent discovery. - **URL**: https://apify.com/klondikeking/behance-project-scraper.md - **Developed by:** [Pierrick McD0nald](https://apify.com/klondikeking) (community) - **Categories:** Developer tools, Lead generation - **Stats:** 2 total users, 1 monthly users, 0.0% runs succeeded, NaN 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/platform/actors/running/actors-in-store#pay-per-usage ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. 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. Actors are written with capital "A". ## 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. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Behance Project Search Scraper — Extract Design Projects by Keyword Scrape Behance projects using search keywords to discover trending design work, analyze competitors, and identify talented creators. This Actor extracts project titles, creator names, thumbnails, appreciation counts, view counts, and direct project URLs from Behance search results. ### Use Cases - **Design Research** — Monitor trends in graphic design, branding, UI/UX, and illustration by scraping projects for specific keywords - **Competitive Analysis** — Track how competitors' projects perform on Behance by extracting appreciation and view counts - **Talent Discovery** — Find skilled designers and creatives for hiring or collaboration opportunities - **Market Intelligence** — Analyze which design styles and project types gain the most engagement on Behance - **Portfolio Monitoring** — Keep track of new projects in your niche or category ### Input | Field | Type | Required | Description | |-------|------|----------|-------------| | `searchKeywords` | Array | Yes | List of keywords to search on Behance (e.g., `["logo design", "brand identity"]`). Each keyword spawns a separate search. | | `maxItems` | Number | No | Maximum total projects to scrape across all keywords (default: 100) | | `proxyConfiguration` | Object | No | Proxy configuration. Uses Apify proxy by default. | ### Output The Actor outputs a dataset with the following fields: ```json { "title": "Asahi OTOYA", "projectUrl": "https://www.behance.net/gallery/245585895/Asahi-OTOYA", "projectId": "245585895", "creatorName": "Like Minded Studio", "creatorUrl": "https://www.behance.net/Likeminded", "thumbnailUrl": "https://mir-s3-cdn-cf.behance.net/projects/404/de8b73245585895.png", "appreciations": 426, "views": 5160, "searchQuery": "logo design", "scrapedAt": "2026-04-19T12:00:00.000Z" } ```` ### Pricing Pay per event: **$0.002 per project scraped** (equivalent to $2.00 per 1,000 projects). Pricing is based on the number of projects successfully extracted and pushed to the dataset. No charge for failed requests or empty pages. ### Limitations - Behance serves approximately 24 projects per search page before requiring login. The Actor scrapes all available pages per keyword up to the `maxItems` limit. - Search results are subject to Behance's ranking algorithm and may vary over time. - Very high-volume scraping may be rate-limited. Use proxy rotation for best results. - Project statistics (appreciations and views) are approximate and reflect the count at the time of scraping. ### FAQ **Q: Can I scrape a specific Behance user's portfolio?** A: This Actor is optimized for keyword-based search. For user portfolio scraping, consider using the project URLs extracted here as input to a dedicated profile scraper. **Q: How many projects can I scrape per keyword?** A: Each keyword typically yields 24 projects per page, with pagination available. The Actor respects the `maxItems` limit across all keywords combined. **Q: Do I need a proxy?** A: Proxy is recommended for consistent results and to avoid rate limiting. The Actor uses Apify's built-in proxy by default. ### Changelog - **v1.0.0** — Initial release. Keyword-based Behance project search with pagination, PPE charging, and comprehensive metadata extraction. # Actor input Schema ## `searchKeywords` (type: `array`): Keywords to search for on Behance (e.g., \['logo design', 'brand identity']) ## `maxItems` (type: `integer`): Maximum number of projects to scrape across all keywords ## `proxyConfiguration` (type: `object`): Proxy settings for scraping ## Actor input object example ```json { "searchKeywords": [ "logo design" ], "maxItems": 50, "proxyConfiguration": { "useApifyProxy": true } } ``` # Actor output Schema ## `projects` (type: `string`): Dataset containing scraped Behance projects ## `stats` (type: `string`): Key-value store with scrape statistics # 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 '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "searchKeywords": [ "logo design" ], "maxItems": 50, "proxyConfiguration": { "useApifyProxy": true } }; // Run the Actor and wait for it to finish const run = await client.actor("klondikeking/behance-project-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 '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "searchKeywords": ["logo design"], "maxItems": 50, "proxyConfiguration": { "useApifyProxy": True }, } # Run the Actor and wait for it to finish run = client.actor("klondikeking/behance-project-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "searchKeywords": [ "logo design" ], "maxItems": 50, "proxyConfiguration": { "useApifyProxy": true } }' | apify call klondikeking/behance-project-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=klondikeking/behance-project-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Behance Project Search Scraper", "description": "Scrape Behance projects by search keywords. Extract project titles, creators, thumbnails, appreciation counts, and view counts for design research, competitive analysis, and talent discovery.", "version": "1.0", "x-build-id": "H9y24evpIYIlfejCF" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/klondikeking~behance-project-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-klondikeking-behance-project-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/klondikeking~behance-project-scraper/runs": { "post": { "operationId": "runs-sync-klondikeking-behance-project-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/klondikeking~behance-project-scraper/run-sync": { "post": { "operationId": "run-sync-klondikeking-behance-project-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "searchKeywords" ], "properties": { "searchKeywords": { "title": "Search Keywords", "type": "array", "description": "Keywords to search for on Behance (e.g., ['logo design', 'brand identity'])", "items": { "type": "string" } }, "maxItems": { "title": "Maximum Projects", "type": "integer", "description": "Maximum number of projects to scrape across all keywords", "default": 100 }, "proxyConfiguration": { "title": "Proxy Configuration", "type": "object", "description": "Proxy settings for scraping" } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```