# Ars Technica Rss Scraper (`real-estate-api/ars-technica-rss-scraper-202610120341`) Actor

Ars Technica RSS Scraper is a Python tool designed to parse RSS feeds from Ars Technica. It extracts technology news, article summaries, publication dates, author metadata, and links into clean CSV or JSON formats for media tracking.

- **URL**: https://apify.com/real-estate-api/ars-technica-rss-scraper-202610120341.md
- **Developed by:** [real-estate-api](https://apify.com/real-estate-api) (community)
- **Security:** Limited permissions
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $2.99 / 1,000 results

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

### Ars Technica RSS Scraper — Collect Technology News, Headlines, and Story Metadata

### Overview

Ars Technica RSS Scraper collects recent story listings from supported Ars Technica feeds and organizes them into structured dataset records. Each record can include the headline, story link, publication date, author, categories, comment count, short summary, image link, and unique story identifier.

Designed for technology news monitoring, topic research, and content analysis, the scraper supports JSON, CSV, and Excel exports. Schedule regular runs to build an ongoing collection of recent stories.

### Features

- **Story collection:** Collect recent stories from supported Ars Technica news and technology-lab feeds.
- **Keyword filtering:** Filter stories by keywords in headlines and short summaries.
- **Metadata extraction:** Collect publication dates, authors, categories, comment counts, and image links when available.
- **Plain-text summaries:** Convert HTML-formatted summaries into readable text.
- **Summary length control:** Limit summaries to 500 characters.
- **Duplicate detection:** Use `guid` identifiers to identify and skip duplicate stories.
- **Structured exports:** Export collected records to JSON, CSV, or Excel.
- **Lightweight collection:** Collect story listings and summaries without storing full article bodies.

### Use Cases

#### Technology News Monitoring

Track recent headlines and developments across technology topics and industry trends.

#### Section Monitoring

Collect stories from supported technology-lab and general news feeds to organize different areas of coverage.

#### Keyword Research

Find stories mentioning specific companies, products, technologies, or industry developments.

#### Research and Reporting

Organize headlines, publication dates, authors, categories, and summaries for research and reporting workflows.

#### Content Analysis

Review story categories, recurring topics, and publication patterns over time.

#### Data Processing

Export structured news records for filtering, sorting, analysis, and further processing.

### Input Parameters

| Parameter | Type | Default | Description |
|---|---|---|---|
| `feedUrls` | Array | Index and technology-lab feeds | List of supported Ars Technica feed locations. Only supported feed hosts are accepted. |
| `keyword` | String | Empty | Optional keyword filter applied to headlines and short summaries. |
| `maxItems` | Integer | `100` | Maximum number of stories to save, from 1 to 1,000. |
| `timeoutSecs` | Integer | `300` | Maximum run duration in seconds. |
| `requestTimeoutSecs` | Integer | `30` | Maximum wait time for an individual feed download, in seconds. |

### Example Input

This configuration collects up to 100 stories matching the keyword `technology` from two supported feeds.

```json id="f3h9qs"
{
  "feedUrls": [
    "FEED_URL_1",
    "FEED_URL_2"
  ],
  "keyword": "technology",
  "maxItems": 100,
  "timeoutSecs": 300,
  "requestTimeoutSecs": 30
}
```

Use supported Ars Technica feed locations for `feedUrls`. Unsupported feed locations are not processed.

### Extracted Data

Each successfully collected story is saved as a structured dataset record.

| Field | Type | Description |
|---|---|---|
| `itemTitle` | String | Story headline provided by the feed. |
| `link` | String | Link to the original story. |
| `comments` | String | Comment count, when available. |
| `author` | String | Story author, when provided. |
| `pubDate` | String | Publication date supplied by the feed. |
| `categories` | Array | Categories or tags associated with the story. |
| `guid` | String | Unique story identifier used to identify duplicate records. |
| `summary` | String | Plain-text story summary, limited to 500 characters. |
| `imageUrl` | String | Story image link, when available. |
| `scrapedAt` | String | UTC timestamp indicating when the record was collected. |

The fields `itemTitle` and `summary` are used instead of `title` and `description` to avoid conflicts with reserved dataset schema field names.

The scraper collects story listings and summaries rather than the full article body.

### Example Output

```json id="z2p7mk"
{
  "itemTitle": "Example technology headline",
  "link": "ARTICLE_URL",
  "comments": "29",
  "author": "Example Author",
  "pubDate": "Sun, 11 Oct 2026 14:50:24 +0000",
  "categories": [
    "Technology",
    "News"
  ],
  "guid": "STORY_UNIQUE_IDENTIFIER",
  "summary": "A short summary of the story.",
  "imageUrl": "IMAGE_URL",
  "scrapedAt": "2026-10-12T00:00:00+00:00"
}
```

This example illustrates the output structure. Actual values depend on the feed items available during collection and the configured keyword filter.

### Working with Your Dataset

Choose an export format according to your workflow:

- **JSON:** Suitable for structured data processing and application workflows.
- **CSV:** Convenient for spreadsheet analysis, filtering, and sorting.
- **Excel:** Useful for reporting, reviewing story metadata, and sharing research with a team.

For ongoing monitoring, schedule regular runs and use `guid` to identify stories already collected. RSS feeds generally provide recent items rather than a complete historical archive, so maintaining your own dataset helps preserve records over time.

### Important Notes

- Only supported Ars Technica feed locations are processed.
- Keyword filtering applies to headlines and short summaries.
- Summary text is limited to 500 characters.
- Some fields, including author, comment count, categories, and image links, may be unavailable for individual stories.
- The scraper collects story listings and summaries, not full article bodies.
- Results depend on the items available in the selected feeds at collection time.

### FAQ

#### Can I collect stories from multiple feeds in one run?

Yes. Provide multiple supported feed locations in the `feedUrls` array.

#### Can I filter stories by keyword?

Yes. Set `keyword` to the term you want to find in headlines and short summaries. Leave it empty to collect stories without a keyword filter.

#### How many stories can one run collect?

The default limit is 100 stories. You can increase `maxItems` to a maximum of 1,000.

#### Does the scraper collect full articles?

No. It collects story listings, metadata, and short summaries rather than full article bodies.

#### Why might some fields be empty or missing?

Not every feed item includes all metadata. Author names, comment counts, categories, and image links depend on the information available for each story.

#### What export formats are supported?

You can export the dataset as JSON, CSV, or Excel.

#### How can I maintain a collection of stories over time?

Schedule regular runs and retain your dataset between collections. Use `guid` to help identify previously collected stories and avoid duplicates.

### Disclaimer

This Actor is an independent tool and is not affiliated with, endorsed by, sponsored by, or otherwise officially associated with Ars Technica or its owners. Users are responsible for complying with applicable source terms and collection restrictions.

### Is Web Scraping Legal?

Collecting information that is already public is generally legal. Scraping is not the same thing as hacking, and there is no single law that bans it. The limits are the usual ones: do not break into accounts, do not take private or confidential data, and be careful with personal data and copyrighted works. A site's terms can also restrict how you access it. Facts such as a public name, price, or rating are not the same thing as republishing someone's article or photo.

This actor collects information from public pages. It does not log in and it does not bypass access controls.

For a longer explanation, see Apify's article [Is web scraping legal?](https://blog.apify.com/is-web-scraping-legal/).

# Actor input Schema

## `feedUrls` (type: `array`):

Public Ars Technica RSS feed URLs on feeds.arstechnica.com. Each URL is fetched once per run. The two defaults are the verified index and technology-lab feeds.

## `keyword` (type: `string`):

Optional client-side filter. Keeps items whose headline or short summary contains this text, case insensitive. Leave empty to keep every item.

## `maxItems` (type: `integer`):

Maximum number of feed items to save in one run. Values are clamped between 1 and 1000.

## `timeoutSecs` (type: `integer`):

Overall run time limit in seconds. The actor stops fetching more feeds when this limit is reached.

## `requestTimeoutSecs` (type: `integer`):

Per-request HTTP timeout in seconds for each feed download.

## `proxyConfiguration` (type: `object`):

Optional proxy settings. The default sends requests directly, with no Apify proxy. Turn on a proxy only if you need one.

## Actor input object example

```json
{
  "feedUrls": [
    "https://feeds.arstechnica.com/arstechnica/index",
    "https://feeds.arstechnica.com/arstechnica/technology-lab"
  ],
  "keyword": "",
  "maxItems": 100,
  "timeoutSecs": 300,
  "requestTimeoutSecs": 30,
  "proxyConfiguration": {
    "useApifyProxy": false
  }
}
```

# Actor output Schema

## `dataset` (type: `string`):

No description

## `datasetUrl` (type: `string`):

No description

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "feedUrls": [
        "https://feeds.arstechnica.com/arstechnica/index",
        "https://feeds.arstechnica.com/arstechnica/technology-lab"
    ],
    "keyword": "",
    "proxyConfiguration": {
        "useApifyProxy": false
    }
};

// Run the Actor and wait for it to finish
const run = await client.actor("real-estate-api/ars-technica-rss-scraper-202610120341").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "feedUrls": [
        "https://feeds.arstechnica.com/arstechnica/index",
        "https://feeds.arstechnica.com/arstechnica/technology-lab",
    ],
    "keyword": "",
    "proxyConfiguration": { "useApifyProxy": False },
}

# Run the Actor and wait for it to finish
run = client.actor("real-estate-api/ars-technica-rss-scraper-202610120341").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "feedUrls": [
    "https://feeds.arstechnica.com/arstechnica/index",
    "https://feeds.arstechnica.com/arstechnica/technology-lab"
  ],
  "keyword": "",
  "proxyConfiguration": {
    "useApifyProxy": false
  }
}' |
apify call real-estate-api/ars-technica-rss-scraper-202610120341 --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,real-estate-api/ars-technica-rss-scraper-202610120341"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/74MFRcCLTt42t6Rgs/builds/6YV1lr7qt3J44nTUM/openapi.json