Fetching Behance Projects at Scale with /v2/projects/search Pagination

If you need thousands of Behance projects for market research or portfolio aggregation, the hard part is not the first page, it is staying consistent across many pages without hitting rate limits or drifting as new work is published. The useful takeaway is to follow the pagination links returned by the API and throttle requests, rather than blindly incrementing page numbers.

The bulk search problem

Behance project search is useful for trend analysis, competitor monitoring, and dataset building. A single query can match tens of thousands of projects. Pulling them all at once is not supported, and naive looping creates two risks: rate limiting and result drift when new projects are added between requests.

How /v2/projects/search paginates

The public REST API exposes /v2/projects/search. Common query parameters include search, sort, page_size and page. The default page size is 20 projects, with a documented maximum of 100.

The response shape described in available material includes a projects array and a next_page URL for continuation. Using the provided link avoids recalculating offsets on the client.

Note for review: research summaries conflict on whether this pagination is cursor-based or offset-based. Verify the current API documentation for the exact pagination model before relying on stability guarantees.

Worked example: iterating pages safely

Run locally with Node.js 18+ and an API key with read access. The script below shows the control flow for following next_page and logging titles and URLs. It does not claim to be tested.

// run with: node fetch-behance.js
// requires: API key with Behance read scope, outbound HTTPS

const API_KEY = process.env.BEHANCE_API_KEY;
const BASE = 'https://api.behance.net/v2/projects/search';

async function fetchPage(url) {
  const res = await fetch(url, {
    headers: { 'Authorization': `Bearer ${API_KEY}` }
  });
  if (!res.ok) throw new Error(`HTTP ${res.status}`);
  return res.json();
}

async function* paginate(query) {
  let url = `${BASE}?search=${encodeURIComponent(query)}&page_size=50&sort=appreciations`;
  while (url) {
    const data = await fetchPage(url);
    yield data.projects;
    url = data.next_page || null;
    // backoff placeholder
    await new Promise(r => setTimeout(r, 1000));
  }
}

(async () => {
  for await (const projects of paginate('generative art')) {
    for (const p of projects) {
      console.log(p.name, p.url);
    }
  }
})();

Expected checks: each response contains a projects array and either a next_page string or null. Stop when next_page is null. Risks: exceeding request rate may trigger temporary blocks, and changing query parameters mid-walk invalidates the sequence.

Trade-offs and limits

• Result drift: if pagination is offset-based, new projects inserted during traversal can cause duplicates or misses. Cursor-based links reduce but do not eliminate this if the underlying sort is not stable.
• Rate limits: material notes around 60 requests per minute. Implement exponential back-off and respect Retry-After headers when present.
• Versioning: API parameters such as page_size can be deprecated. Monitor changelogs before upgrading clients.

To verify behavior, request the first page, inspect the presence and format of next_page, and confirm that successive calls return a decreasing overlap of project IDs when the sort is stable.

Actionable next steps

1. Register for a Behance developer account and obtain an API key.
2. Implement throttling and local caching of project IDs to avoid re-fetching.
3. Log next_page values and response sizes to detect unexpected changes.
4. Review official documentation for the current pagination contract and rate limits before production use.