Pikabu Search Scraper

Extract public Pikabu search results by keyword or search URL. Export structured posts with titles, authors, timestamps, ratings, comment counts, tags, excerpts, and public media URLs.

What does Pikabu Search Scraper do?

Pikabu Search Scraper turns public Pikabu search pages into clean datasets. Run searches for Russian keywords, brand names, products, memes, communities, or news topics. The actor uses HTTP-first extraction from server-rendered Pikabu HTML, so it is lightweight and fast.

Who is it for?

🧭 Brand monitoring teams tracking Russian-language mentions. 📈 Social listening analysts watching topic momentum and engagement. 📰 Journalists and OSINT researchers collecting public discussion evidence. 🎮 Community managers researching memes, fandoms, and user reactions. 🛒 Market researchers comparing product chatter and complaints.

Why use this scraper?

It exports repeatable data instead of manual copy-paste from Pikabu search. You can schedule it, connect it to webhooks, or send results to spreadsheets and BI tools. The output keeps both content and crawl metadata so teams can audit where each post came from.

What data can you extract?

Each result contains the search query, source page, post URL, post ID, title, author, author URL, publication time, rating, comments count, tags, excerpt, image URLs, video URLs, page number, and scrape timestamp.

How much does it cost to scrape Pikabu search results?

This actor uses pay-per-event pricing with a small start charge and a per-post result event. Use low maxItems values for trial runs and increase limits after you confirm the query quality. Large monitoring jobs become cheaper per item on higher Apify subscription tiers.

How to scrape Pikabu by keyword

1. Add one or more terms to queries.
2. Set maxItems to the total number of posts you need.
3. Set maxPages high enough for deeper historical coverage.
4. Run the actor and export the dataset as JSON, CSV, Excel, or via API.

How to scrape a Pikabu search URL

Paste a full Pikabu /search?q=... URL into startUrls. This is useful when you copied an encoded Russian query from your browser. The actor preserves the source URL on every output item.

Input options

queries accepts keyword strings. startUrls accepts full Pikabu search URLs. maxItems limits saved posts across the run. maxPages limits result pages per seed. requestDelayMs adds a polite delay between page requests.

Output example

{
  "query": "нейросети",
  "postUrl": "https://pikabu.ru/story/example_123",
  "title": "Example Pikabu post",
  "author": "nickname",
  "rating": 42,
  "commentsCount": 7,
  "tags": ["AI", "Новости"],
  "imageUrls": [],
  "videoUrls": [],
  "pageNumber": 1
}

Tips for better results

Use Russian-language keywords where possible. Run separate jobs for unrelated topics so exports are easier to analyze. Increase maxPages for broad topics and keep it small for fresh monitoring. Use exact product or brand spelling variants as separate queries.

Scheduling and monitoring workflows

Schedule daily or hourly runs for reputation monitoring. Send dataset items to Slack, Google Sheets, Make, Zapier, or your data warehouse. Compare ratings and comments over time to detect fast-moving community discussions.

Integrations

Use Apify webhooks for new-run notifications. Use dataset API URLs in BI dashboards. Connect the actor to Make or Zapier for no-code enrichment. Combine it with other automation-lab social and search scrapers for broader monitoring.

API usage with Node.js

import { ApifyClient } from 'apify-client';
const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('automation-lab/pikabu-search-scraper').call({
  queries: ['нейросети'], maxItems: 50, maxPages: 2
});
console.log(run.defaultDatasetId);

API usage with Python

from apify_client import ApifyClient
client = ApifyClient("<APIFY_TOKEN>")
run = client.actor("automation-lab/pikabu-search-scraper").call(run_input={
    "queries": ["нейросети"], "maxItems": 50, "maxPages": 2
})
print(run["defaultDatasetId"])

API usage with cURL

curl -X POST "https://api.apify.com/v2/acts/automation-lab~pikabu-search-scraper/runs?token=$APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"queries":["нейросети"],"maxItems":50,"maxPages":2}'

MCP usage

Use the Apify MCP server with Claude Desktop or Claude Code. MCP URL: https://mcp.apify.com/?tools=automation-lab/pikabu-search-scraper

Add it in Claude Code:

$claude mcp add --transport http apify-pikabu-search "https://mcp.apify.com/?tools=automation-lab/pikabu-search-scraper"

Claude Desktop JSON configuration:

{
  "mcpServers": {
    "apify-pikabu-search": {
      "url": "https://mcp.apify.com/?tools=automation-lab/pikabu-search-scraper"
    }
  }
}

Example prompt: "Run the Pikabu Search Scraper for нейросети and summarize the most discussed posts." Example prompt: "Export Pikabu posts for my brand keyword and list titles with negative engagement signals."

Data quality notes

Pikabu search pages are public and server-rendered. Some counters may be hidden or loading placeholders depending on Pikabu markup. Media arrays include URLs present in the search result HTML; full post pages may contain additional media not shown in search snippets.

Limitations

The actor does not log in and does not access private content. It does not post comments, vote, or interact with users. Very broad queries may require many pages and should use reasonable delays.

Legality and responsible use

Only scrape public pages you are allowed to access. Respect Pikabu terms, privacy laws, and your organization’s compliance rules. Do not use exported data for harassment, spam, or intrusive profiling.

Troubleshooting

If you get no results, verify the query returns posts in a normal browser. If Russian text looks unexpected, use dataset JSON/CSV exports with UTF-8-aware tools. If a run is too small, increase maxPages or try broader keywords.

FAQ

Can I scrape private Pikabu content? No, only public search result pages are supported. Can I use URLs instead of queries? Yes, use startUrls. Can I monitor multiple keywords? Yes, add several strings to queries. Does it use a browser? No, it is HTTP-first for speed and cost control.

Related scrapers

Use Pikabu Search Scraper when you need Russian-language community discussion from Pikabu specifically. For broader monitoring, combine the dataset with these automation-lab actors:

• Google Search Scraper — find indexed pages and web mentions for the same keywords.
• Google News Scraper — compare Pikabu community reactions with mainstream news coverage.
• Reddit Scraper — monitor English-language community threads around the same topic.
• Bluesky Scraper — track short-form social posts and emerging conversations.
• Twitter Followers Scraper — enrich social audience research when a monitored brand or creator also uses X/Twitter.

Join datasets on normalized keywords, domains, brand names, or campaign IDs in your downstream database. Keep the original sourceUrl and postUrl fields so analysts can trace every row back to its public page.

Common use cases

Brand and product monitoring

Track Russian-language mentions of a product, game, app, marketplace seller, or public figure. Save the title, excerpt, rating, and comment count to identify discussions that deserve manual review.

Campaign and launch tracking

Run the same query before and after a launch. Comparing result volume, ratings, and discussion counts can show whether Pikabu users are reacting to announcements, ads, pricing changes, or support incidents.

OSINT and journalism research

Collect public post metadata for a defined keyword set. The actor records the search seed, result page, post URL, and scrape time, which helps maintain a reproducible evidence trail.

Meme and community trend discovery

Search slang, hashtags, character names, and meme phrases. Export tags and excerpts to cluster recurring topics before deciding which posts need full manual reading.

Working with exported data

• Use postUrl as the stable primary link for deduplication.
• Use sourceUrl to see which search URL or query produced a row.
• Use pageNumber to understand result depth and freshness.
• Use scrapedAt to compare scheduled runs over time.
• Keep query in downstream tables when monitoring multiple terms in one run.
• Treat rating and commentsCount as engagement indicators, not sentiment labels.

Recommended run sizes

For quick tests, start with maxItems between 10 and 50 and maxPages between 1 and 2. For recurring monitoring, schedule several smaller keyword-specific runs instead of one very broad job. This keeps exports easier to audit and helps you spot which terms produce useful discussions.

For historical discovery, increase maxPages gradually and review sample output after each run. If the later pages become irrelevant, narrow the query or add more specific spelling variants.

Support

Open an Apify actor issue with your input, run ID, and expected output if you need help. Include a small reproducible query so support can verify quickly.