
Hacker News Scraper
hipersoft/hackernews-scraper
Scrape Hacker News: keyword search across all stories & comments, live Top/New/Best/Ask/Show/Job front pages, user profiles and full comment threads. Filter by points, date and comment count. One clean row per item as JSON, CSV or Excel.
Total users
2Monthly users
1Total runs
44Per item scraped
$0.003Last rebuilt
Oct 26, 2026Overview
Turn Hacker News into clean, structured data. Run a keyword search across every story and comment, pull the live Top / New / Best / Ask HN / Show HN / Jobs front pages, look up user profiles, or grab a story with its full comment thread — and get one tidy row per item. Export to JSON, CSV or Excel, or pull straight from the API.
Perfect for tech trend monitoring, startup and product research, developer sentiment analysis, building datasets for LLMs, tracking mentions of your company or competitors, lead lists from "Who is hiring?" threads, and feeding Hacker News data into your own app, dashboard or workflow.
What you get
One flat, ready-to-use record per item — story, comment, job or user:
| Field | Description |
|---|---|
id |
Hacker News item ID |
type |
story, comment, job, poll or user |
title |
Story / job title |
text |
Body text (Ask HN posts, comments, job posts) |
url |
The story's outbound link |
hnUrl |
Direct link to the item on Hacker News |
author |
Username of the poster |
points |
Score / upvotes |
numComments |
Number of comments |
createdAt / time |
When it was posted (ISO 8601 + unix) |
parentId / storyId |
Parent comment / owning story (for comments) |
depth |
Reply depth within a thread (for comments) |
karma / about / submittedCount |
Profile stats (for users) |
source |
Which feed / mode the row came from |
collectedAt |
When the row was scraped |
How to use
1. Search by keyword
Add one or more keywords and the scraper searches across all of Hacker News. Narrow it down with type, score, comment count and date filters.
{
"searchQueries": ["openai", "rust"],
"tags": "story",
"minPoints": 100,
"sortByDate": false,
"maxItems": 200
}
- Search: item type — Stories, Comments, Ask HN, Show HN, Polls, or Stories + comments.
- Search: min points / min comments — only keep items above a threshold.
- Search: from / to date — restrict to a date range (
YYYY-MM-DD). - Search: newest first — sort chronologically instead of by relevance.
2. Front-page feeds
Scrape the live front pages — pick any combination:
{
"feeds": ["top", "ask", "show"],
"maxItems": 100
}
Top stories, New stories, Best stories, Ask HN, Show HN and Jobs are all supported.
3. User profiles
Look up any Hacker News user — karma, account age, about text and submission count:
{
"usernames": ["pg", "dang"]
}
4. Specific stories & full comment threads
Paste story URLs or IDs and optionally pull every comment:
{
"itemUrls": ["https://news.ycombinator.com/item?id=1"],
"includeComments": true,
"maxCommentsPerItem": 300,
"maxCommentDepth": 10
}
Turn on Include comments with any front-page feed or specific item to add each comment as its own row, with reply depth preserved.
Example output
{
"id": 1,
"type": "story",
"title": "Y Combinator",
"url": "http://ycombinator.com",
"hnUrl": "https://news.ycombinator.com/item?id=1",
"author": "pg",
"points": 57,
"numComments": 3,
"createdAt": "2006-10-09T18:21:51.000Z",
"source": "feed:top",
"collectedAt": "2026-09-20T01:30:00.000Z"
}
Common use cases
- Tech trend & topic monitoring — track how often a technology, framework or company is discussed and how sentiment shifts over time.
- Startup & product research — mine Show HN launches, Ask HN threads and comment discussions.
- Hiring intelligence — extract companies and roles from the monthly "Who is hiring?" threads.
- LLM & research datasets — build clean corpora of stories and comments with points, authors and timestamps.
- Brand & competitor tracking — get alerted to mentions and read the full discussion around them.
- Newsletters & dashboards — pipe the daily Top or Best stories straight into your own product.
Frequently asked questions
Do I need any login, cookies or tokens? No. Just set your inputs and run.
How many results can I get? Set Max items to whatever you need (0 = no limit). Keyword search paginates through all matches; front-page feeds cover up to 500 stories each.
Can I get every comment on a story? Yes — enable Include comments and set the per-item cap and depth. Comments come back as individual rows with parentId, storyId and depth.
What format is the data? A flat table you can export as JSON, CSV, or Excel, or fetch from the Apify API.
Is the data live? Yes — front-page feeds and items reflect Hacker News in real time; search covers the full history.
Related scrapers
Looking for more data sources? Check out our other scrapers on Apify Store for news, tech communities, job boards and developer platforms — all with the same clean, one-row-per-item output.
Input
| Field | Type | Description |
|---|---|---|
searchQueriesSearch keywords | array | Keywords to search across Hacker News stories and comments — e.g. 'openai', 'rust', 'yc s24'. Each keyword runs its own search and the results are combined. Leave empty if you only want front-page feeds, users or specific items below. |
feedsFront-page feeds | array | Scrape live Hacker News front pages. Pick any combination of Top, New, Best, Ask HN, Show HN and Jobs. |
tagsSearch: item type | string · story, comment, all, ask_hn, show_hn, poll | For keyword search — restrict to stories, comments, Ask HN, Show HN, polls, or both stories and comments. Default: "story" |
sortByDateSearch: newest first | boolean | Sort keyword-search results by date (newest first) instead of by relevance. Default: false |
minPointsSearch: min points | integer | Only return search results with at least this many points (0 = no minimum). Default: 0 |
minCommentsSearch: min comments | integer | Only return search results with at least this many comments (0 = no minimum). Default: 0 |
dateFromSearch: from date | string | Only return search results created on or after this date (YYYY-MM-DD). Leave empty for no lower bound. |
dateToSearch: to date | string | Only return search results created on or before this date (YYYY-MM-DD). Leave empty for no upper bound. |
usernamesUser profiles | array | Hacker News usernames (or profile URLs) to fetch — returns karma, account age, about text and submission count for each. |
itemUrlsStory / item URLs or IDs | array | Specific Hacker News items to fetch — paste story URLs (https://news.ycombinator.com/item?id=…) or bare item IDs. Enable 'Include comments' to also pull each item's full comment thread. |
includeCommentsInclude comments | boolean | For front-page stories and the specific items above, also scrape the full comment thread (each comment is one extra row). Default: false |
maxCommentsPerItemMax comments per item | integer | Cap on how many comments to collect per story when 'Include comments' is on. Default: 200 |
maxCommentDepthMax comment depth | integer | How deep to follow reply chains when collecting comments (1 = top-level replies only). Default: 10 |
maxItemsMax items | integer | Maximum number of rows to collect across everything (0 = no limit). Default: 100 |
API
curl -X POST "https://api.apify.com/v2/acts/hipersoft~hackernews-scraper/run-sync-get-dataset-items?token=$APIFY_TOKEN" \
-H "Content-Type: application/json" \
-d '{
"searchQueries": [
"openai"
]
}'from apify_client import ApifyClient
client = ApifyClient("YOUR_APIFY_TOKEN")
run = client.actor("hipersoft/hackernews-scraper").call(run_input={
"searchQueries": [
"openai"
]
})
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
print(item)import { ApifyClient } from 'apify-client';
const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' });
const run = await client.actor('hipersoft/hackernews-scraper').call({
"searchQueries": [
"openai"
]
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);Pricing
| Event | Price | Paid plans from |
|---|---|---|
| Item scraped Charged for each Hacker News item returned — a story, comment, job, poll or user profile. | $0.003 | $0.0015 |
You pay only for what the run returns. Set a maximum cost per run and it stops cleanly at that limit.
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