🎬 HN Show HN Tracker — Indie Product Launch Stream

Stream every Show HN launch and Ask HN thread directly from Hacker News's Algolia search index. Filter by date, points, and stream type. Optionally pull the top 5 comments per story for built-in sentiment + discussion intel.

If you build for developers, write about technology, run a startup accelerator, or invest in early-stage SaaS — Show HN is the single best free signal for "this just shipped and devs care about it." This Actor turns that signal into a clean structured feed.

How this differs from our hacker-news-scraper: the existing actor scrapes HN's front page (top 30 stories at any moment). This Actor is stream-focused — it pulls the entire historical Show HN, Ask HN, or general story stream paginated by date. Different use cases, complementary tools.

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What you get per story

Each dataset row is one HN story (Show HN / Ask HN / front_page / story):

• Identity — object_id (HN item ID), stream (which feed it came from), tags (Algolia _tags)
• Title + content — title, url (the external link), story_text (Show HN's "this is what I built" body or Ask HN question text)
• Permalink — hn_url (https://news.ycombinator.com/item?id=...)
• Author — author (HN username)
• Engagement — points (upvotes), num_comments
• Timing — created_at (ISO 8601 UTC), created_at_i (Unix epoch), updated_at
• Comments (optional) — top 5 comments per story with comment_text, author, parent_id, created_at

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6 use cases

1. Product Manager trend hunting — Pull every Show HN with points >= 100 from the last 90 days. Cluster by keywords (AI, MCP, Postgres, Stripe) to see what devs actually upvote vs what gets ignored.
2. Indie founder peer benchmarking — See every Show HN this month sorted by points. Reverse-engineer the launch posts that hit the front page (title structure, time of day, body length) and copy what works.
3. Journalism / writeup pipeline — Filter Show HN to points >= 200 (top ~5%) — these are the genuine breakout launches. With includeComments: true you also get the dev-community reaction in one shot.
4. Recruiting / talent intel — Show HN authors are usually the founder/builder. Pulling Show HN authors who post repeatedly across multiple launches surfaces serial indie hackers.
5. Competitive intel — Set up a daily dateFrom: yesterday Show HN run; alert on any title containing your keywords. Catch competitor launches the same day they ship.
6. Investor / VC sourcing — Every Show HN with the founder's email or website in the body is a free pre-seed pipeline. Filter points >= 50 to skip the lottery posts.

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Quick start (JSON input)

{
  "streams": ["show_hn"],
  "dateFrom": "2025-01-01",
  "dateTo": "2025-01-31",
  "minPoints": 50,
  "includeComments": false,
  "maxStoriesPerStream": 500
}

Python SDK

from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("nexgendata/hn-show-hn-tracker").call(run_input={
    "streams": ["show_hn", "ask_hn"],
    "minPoints": 100,
    "maxStoriesPerStream": 200,
})
for story in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(f"[{story['stream']}] {story['points']} pts — {story['title']}")
    print(f"  link: {story['url']}  HN: {story['hn_url']}")

cURL

curl "https://api.apify.com/v2/acts/nexgendata~hn-show-hn-tracker/run-sync-get-dataset-items?token=YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"streams":["show_hn"],"minPoints":100,"maxStoriesPerStream":50}'

Integrations

Pipe results to Zapier, Make.com, or n8n for daily Slack digests, Google Sheets append, or CRM enrichment. Common pairings: Slack alert when a competitor name shows up in a Show HN body; Notion database for tracking weekly indie launches; Airtable view for editorial pipeline.

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Pricing (Pay Per Event)

Event	Price
Actor start	$0.00005
Per story returned	$0.02

Cost calculator:

• 100 stories = $2.00
• 500 stories (a month of Show HN) = $10.00
• 5,000 stories (~1 year of Show HN) = $100.00
• Full historical Show HN backfill (~520K stories) = $10,400 (one-time, only worth it for serious research)

For ongoing daily monitoring (~30–80 new Show HN posts/day), expect $0.60–$1.60 per day = under $50/month.

Compare to manual scraping (free + your time + getting blocked), or paying a research firm $500+ for a one-shot HN trend report.

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FAQ

Why not use the official HN API? The official hacker-news-firebaseio.com API is terrific for individual items but gives you no native search, no date filtering, no points filtering, and no per-stream tags. Algolia's HN search index — the same one powering hn.algolia.com — solves all that. We use it.

Are Show HN comments included by default? No, to keep cost predictable. Set includeComments: true to fetch the first 5 comments per story (1 extra API call per story; latency adds ~150ms/story).

Can I get older than 2007? No. HN itself launched February 2007 and Algolia indexes from then forward. Our dateFrom accepts any value back to that horizon.

What does front_page really mean? Algolia tags any story that ever appeared on the HN front page. It's the highest-quality filter for "broadly-noticed stories" (more selective than points >= 50 because front-page placement also requires moderator-friendly framing).

What happens if minPoints is too aggressive? You just get fewer results. The Actor caps at maxStoriesPerStream regardless and stops paginating when no hits remain.

Does this conflict with the existing nexgendata hacker-news-scraper? No — that Actor scrapes the live HN front page (top 30, point-in-time snapshot). This Actor pulls historical streams across years and supports per-stream tag filters. They cover different jobs.

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Related actors

• 📰 Hacker News Scraper — live front-page top stories (point-in-time, not historical)
• 💼 HN Who's Hiring Scraper — monthly Who's Hiring + Who Wants to Be Hired threads parsed
• ⭐ GitHub Trending — cross-reference Show HN launches with GitHub stargazer momentum

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