Product Launch Tracker

🚀 Product Launch Tracker is a powerful Apify Actor designed to discover, track, and collect newly posted product and startup launch stories directly from Hacker News' own public search API. This tool provides comprehensive Product Launch Tracker intelligence including product name, launch date, inferred category, description, website, upvotes, comment count, and a direct link to the discussion thread for any search query. Whether you're building a product-discovery feed, tracking startup launch trends, or conducting market research, the Product Launch Tracker delivers actionable Product Launch Tracker insights efficiently.

With direct Hacker News Algolia API access, keyword-based category inference, automatic pagination, and reliable Apify Dataset delivery, the Product Launch Tracker ensures comprehensive Product Launch Tracker coverage across any search query. It focuses on key Product Launch Tracker signals including category, engagement (upvotes/comments), and launch date, making it an essential tool for product discovery and startup trend research.

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📋 Table of Contents

• Features
• Data Source
• How It Works
• Input
• Output
• Technical Stack
• Data Fields
• Use Cases
• Quick Start
• Configuration
• Performance
• Important Notes
• License & Legal

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🔥 Features

• Direct Algolia API Access – Queries Hacker News' official Algolia-powered search API (hn.algolia.com) directly for fast, structured Product Launch Tracker data.
• Date-Sorted Search – Uses the search_by_date endpoint so the newest matching stories surface first.
• Automatic Pagination – Pages through search results until the configured maximum item count is reached.
• Keyword-Based Category Inference – Classifies each result into a category (AI, SaaS, DevTools, Productivity, Finance, Health, Design, Mobile, Web, Tech, or Other) using rule-based keyword matching against the title and text.
• Favicon Thumbnail Generation – Builds a thumbnail URL for each product's website domain using Google's favicon service.
• Text Cleanup – Normalizes whitespace in extracted description text.
• Proxy Support – Optional Apify proxy with configurable groups and country targeting.
• Incremental Dataset Push – Pushes each qualifying item to Apify Dataset as it's found, not just at the end.
• Graceful Error Handling – Stops cleanly on request errors without crashing the run.

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📊 Data Source

Hacker News Algolia Search API

• Authority: Hacker News' official Algolia-powered public search API (hn.algolia.com/api/v1/search_by_date)
• Access Method: Direct HTTP GET requests via requests
• Coverage: Any Hacker News story matching the given search query, sorted by most recent
• Data: Structured JSON story records including title, URL, points, comment count, and timestamps
• Access: Public API, no API key required
• Update Frequency: Reflects Hacker News' current live story index at time of run

ℹ️ This Actor sources its data from Hacker News, not Product Hunt — despite the internal ph_url field name, every link points to the corresponding Hacker News discussion thread. See Important Notes for details.

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⚙️ How It Works

The Product Launch Tracker accepts a search query and queries Hacker News' Algolia search API for stories matching that query, sorted by most recent first. The Actor pages through results, 100 at a time, until it collects the configured number of items or runs out of matching stories. For each story, it extracts the title, URL, points (upvotes), comment count, and creation date, then applies a simple rule-based keyword classifier to infer a category from the title and available text. A thumbnail URL is generated from the linked website's domain using Google's public favicon service. Every story with a non-empty title is pushed to the Apify Dataset immediately as it's processed.

Key Processing Steps:

1. Input Parsing – Accept a search query and a max result count
2. Proxy Setup – Configure Apify proxy with optional group and country targeting
3. Page Loop – Query the Algolia search API page by page, sorted by date
4. Story Extraction – Pull title, URL, points, comments, and creation date from each hit
5. Category Inference – Match title/text against keyword rules to assign a category label
6. Thumbnail Generation – Build a favicon-based thumbnail URL from the linked website's domain
7. Text Cleanup – Normalize whitespace in the extracted description text
8. Dataset Push – Push each qualifying item to the Dataset immediately
9. Pagination Control – Continue to the next page until the result cap or total page count is reached
10. Rate Limiting – Apply a short delay between paginated requests

Key Benefits:

• Pull Product Launch Tracker data for any keyword without manually browsing Hacker News
• Get an automatically categorized feed of product-related discussions
• Track engagement (points, comments) alongside each discovered product
• Feed product-discovery dashboards, startup trend research, or market monitoring tools
• Automate recurring Product Launch Tracker checks as new stories are posted

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📥 Input

The Actor accepts the following input parameters:

Field	Type	Default	Description
query	string	"launch"	Search term used to find matching Hacker News stories.
max_results	integer	20	Maximum number of Product Launch Tracker items to collect.
proxyConfiguration	object	(none)	Optional Apify proxy configuration, with proxyGroups and apifyProxyCountry sub-fields.

Example Input:

{
  "query": "launch",
  "max_results": 20,
  "proxyConfiguration": {
    "proxyGroups": ["RESIDENTIAL"],
    "apifyProxyCountry": "US"
  }
}

Search a Different Query:

{
  "query": "Show HN",
  "max_results": 50
}

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📤 Output

The Actor pushes Product Launch Tracker records with the following structure:

Field	Type	Description
product_name	string	The story's title, used as the product/launch name
company	string	Always empty — not populated from Hacker News data
launch_date	string/null	Story creation date (YYYY-MM-DD), or null if unavailable
category	string	Inferred category based on keyword matching (see below)
description	string	Cleaned comment or story text, when available
website	string	The URL linked in the story, if any
source	string	Always "Hacker News"
upvotes	integer	The story's Hacker News point score
comments	integer	The story's comment count
ph_url	string	Direct link to the story's Hacker News discussion thread
thumbnail	string/null	Favicon-based thumbnail URL for the linked website's domain

Example Product Launch Tracker Record:

{
  "product_name": "Show HN: I built an open-source AI note-taking app",
  "company": "",
  "launch_date": "2026-08-20",
  "category": "AI",
  "description": "Been working on this for the past few months, would love feedback...",
  "website": "https://example-notes-ai.com",
  "source": "Hacker News",
  "upvotes": 214,
  "comments": 87,
  "ph_url": "https://news.ycombinator.com/item?id=41234567",
  "thumbnail": "https://www.google.com/s2/favicons?domain=example-notes-ai.com&sz=128"
}

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🧰 Technical Stack

• HTTP Client: requests for direct access to the Hacker News Algolia API
• Pattern Matching: re for whitespace normalization in description text
• URL Parsing: urllib.parse for domain extraction used in thumbnail generation
• SSL Verification: certifi for trusted certificate handling
• Async: asyncio for the Actor's run loop and pacing delays
• Proxy: Apify Proxy with configurable groups and country targeting
• Logging: Apify Actor logging system
• Platform: Apify Actor serverless environment

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📊 Data Fields Explained

Product Identity

• product_name: The Hacker News story title, treated as the product/launch name
• website: The external URL linked in the story, when present

Classification

• category: A best-effort label assigned via keyword rule matching — not a verified or authoritative classification
• source: Always "Hacker News", identifying the true data origin

Engagement

• upvotes / comments: The story's point score and comment count on Hacker News
• launch_date: The story's creation date, used as a proxy for "launch" date

Access

• ph_url: Despite the field name, this links to the Hacker News discussion thread, not Product Hunt
• thumbnail: A generated favicon image for the linked website, not an official product screenshot

Not Populated

• company: Always returned as an empty string — this field is not currently extracted from any data source

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🎯 Use Cases

• Product Discovery – Surface newly discussed products and launches from Hacker News
• Startup Trend Research – Track which categories (AI, SaaS, DevTools, etc.) are generating the most launch activity
• Market Research – Study community reception (upvotes, comments) for new product announcements
• Content Curation – Source material for a newsletter or feed covering new product launches
• Competitive Monitoring – Watch for new entrants in a specific category or keyword space
• Academic Research – Study public product-launch and community engagement patterns at scale

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🚀 Quick Start

1. Prepare Input

Go to Apify Console and enter:

{
  "query": "launch"
}

2. Run the Actor

Click Start. The Actor will:

• Query Hacker News' Algolia API for stories matching the query, sorted by date
• Infer a category for each story via keyword matching
• Generate a favicon thumbnail for each linked website
• Push each qualifying item to the Dataset immediately

3. Monitor Progress

Console shows:

Starting fetch for query: launch
Scraping completed. Total products found: 20

4. View & Download Results

• Results Tab: All Product Launch Tracker records
• Export: JSON, CSV, Excel, or HTML
• Filter: By category or upvotes
• API Access: Available via the Apify API

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⚙️ Configuration

Default query:

{
  "query": "launch"
}

"Show HN" launches with a higher cap:

{
  "query": "Show HN",
  "max_results": 50
}

Country-specific proxy:

{
  "query": "launch",
  "proxyConfiguration": {
    "proxyGroups": ["RESIDENTIAL"],
    "apifyProxyCountry": "US"
  }
}

---

📈 Performance

Processing Speed

• Up to 100 results fetched per API request, paginated until the max cap is reached
• 1 second delay between paginated requests to stay within fair-use expectations
• No browser rendering required, so requests complete quickly

Resource Usage

• Memory: Low, since only lightweight JSON requests are made
• Network: One request per page of up to 100 results
• Proxy: One proxy connection shared across requests, if configured

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⚠️ Important Notes

Data Naming Notice

• The output field ph_url links to the Hacker News discussion thread for each story — it does not link to Product Hunt, despite the field name suggesting otherwise
• The source field correctly and consistently identifies the data origin as "Hacker News"
• category is assigned by simple keyword matching against the title/text, not a verified taxonomy — treat it as a best-effort label, not ground truth
• company is always an empty string in the current version — no company-name extraction logic is applied

Legal & Compliance

• Fair Use: Uses Hacker News' official public Algolia search API as intended, with pacing delays between paginated requests
• Public Data Only: Retrieves only publicly posted Hacker News story data
• Legal: Not legal advice — consult qualified professionals before using this data for compliance-sensitive decisions

Data Quality

• Freshness: Reflects Hacker News' current live story index at time of run
• Completeness: Not every story has a linked website, description text, or resolvable category — some fields may be empty or default to "Other"
• Accuracy: Sourced directly from Hacker News' own Algolia-powered API
• Verification: Cross-check high-stakes product details against the live Hacker News thread

Best Practices

• Use specific queries (e.g., "Show HN", a technology name) to focus on genuine launch-style posts
• Treat the category field as a helpful starting filter, not a definitive classification
• Re-run periodically to catch newly posted launch stories
• Increase max_results for broader coverage of a query's activity
• Manually verify high-interest results before using them in downstream reporting

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📄 License & Legal

Terms of Use:

• Use for legitimate research, product discovery, and market analysis purposes
• Respect Hacker News' Terms of Service and API usage guidelines
• Use Product Launch Tracker data responsibly and in compliance with applicable laws

Disclaimer: Product Launch Tracker is provided as-is for research and discovery purposes. All data is sourced from Hacker News, not Product Hunt. Category labels are inferred via keyword matching and are not authoritative. Users are responsible for compliance with Hacker News' terms and all applicable laws. This is not legal advice.

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⚖️ Product Launch Tracker Summary

This Actor is optimized for Product Launch Tracker research with:

• ✅ Direct, official Hacker News Algolia API access
• ✅ Date-sorted, paginated search coverage
• ✅ Rule-based category inference
• ✅ Favicon-based thumbnail generation
• ✅ Incremental Dataset push
• ⚠️ Category and company fields are best-effort/not fully populated — see Important Notes