How to Build a News Aggregator App with RSS Feeds (And Why You Should Use a News API Instead)

beginner 22 min read December 29, 2025

rss feedsnews aggregatornews apirss parserpython tutorialjavascript tutorialxml parsingnews app developmentapi vs rssweb scraping

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TL;DR: Learn how to build a basic news aggregator using RSS feeds with Python or JavaScript. While RSS is simple and free, you’ll discover why modern News APIs like NewsDataHub provide superior filtering, reliability, and structured data for production applications. Includes complete working code and real RSS feed URLs.

Quick Answer: This tutorial shows you how to build a news aggregator by parsing RSS feeds from major news sources. You’ll learn the fundamentals of RSS, XML parsing, and content aggregation. More importantly, you’ll understand why RSS feeds have serious limitations and why News APIs deliver better results for real-world applications.

Perfect for: Beginners learning news aggregation, developers evaluating RSS vs APIs, students building portfolio projects, and anyone exploring content syndication.

Time to complete: 20-25 minutes

Difficulty: Beginner

Stack: Python (feedparser) or JavaScript (rss-parser), with News API comparison

---

What You’ll Build

By the end of this tutorial, you’ll have:

• Working RSS news aggregator — Fetch and parse news from multiple sources
• Python implementation — Using feedparser library
• JavaScript implementation — Using rss-parser for Node.js
• Understanding of RSS limitations — Why RSS isn’t ideal for production
• News API comparison — How modern APIs solve RSS problems

---

What is RSS and How Does it Work?

RSS (Really Simple Syndication) is an XML-based format that allows websites to publish their content updates in a machine-readable format. When a news site publishes a new article, it adds an entry to its RSS feed—an XML file typically hosted at a URL like https://example.com/rss or https://example.com/feed.

RSS Feed Structure

A basic RSS feed looks like this:

<?xml version="1.0" encoding="UTF-8" ?>
<rss version="2.0">
  <channel>
    <title>Example News</title>
    <link>https://example.com</link>
    <description>Latest news from Example</description>
    <item>
      <title>Breaking: Major Technology Announcement</title>
      <link>https://example.com/article/tech-announcement</link>
      <description>Summary of the article...</description>
      <pubDate>Mon, 29 Dec 2025 10:30:00 +0000</pubDate>
      <guid>https://example.com/article/tech-announcement</guid>
    </item>
    <item>
      <title>Market Update: Stocks Rise</title>
      <link>https://example.com/article/market-update</link>
      <description>Financial markets overview...</description>
      <pubDate>Mon, 29 Dec 2025 09:15:00 +0000</pubDate>
    </item>
  </channel>
</rss>

Each <item> represents one article with basic metadata: title, link, description, and publication date.

How RSS Aggregation Works

1. Publisher updates feed — News site adds new articles to its RSS XML file
2. Aggregator fetches feed — Your app makes an HTTP GET request to the feed URL
3. Parse XML — Extract article data from the XML structure
4. Display content — Show articles to users

The key limitation: you’re entirely dependent on what the publisher includes in their feed. No filtering, no search, no customization.

---

Real RSS Feed URLs to Use

Here are working RSS feeds from major news sources you can use in this tutorial:

International News

• BBC News — http://feeds.bbci.co.uk/news/rss.xml
• The Guardian — https://www.theguardian.com/world/rss
• Al Jazeera — https://www.aljazeera.com/xml/rss/all.xml

US News

• NPR News — https://feeds.npr.org/1001/rss.xml
• ABC News — https://abcnews.go.com/abcnews/topstories
• CBS News — https://www.cbsnews.com/latest/rss/main
• NBC News — https://feeds.nbcnews.com/nbcnews/public/news

Technology

• TechCrunch — https://techcrunch.com/feed/
• Wired — https://www.wired.com/feed/rss
• Ars Technica — https://feeds.arstechnica.com/arstechnica/index
• The Verge — https://www.theverge.com/rss/index.xml

Business & Finance

• Financial Times — https://www.ft.com/?format=rss
• CNBC — https://www.cnbc.com/id/100003114/device/rss/rss.html

Note: Some feeds may require user agents or have rate limits. RSS feeds can break or change URLs without notice—one of many reasons production apps use APIs instead.

---

Prerequisites

For Python Implementation

• Python 3.7+
• pip package manager

For JavaScript Implementation

• Node.js 14+
• npm package manager

Knowledge Requirements

• Basic Python or JavaScript syntax
• Understanding of HTTP requests
• Familiarity with JSON/XML data structures

---

Implementation 1: Python News Aggregator

Step 1: Install Dependencies

pip install feedparser requests

feedparser is a robust Python library that handles RSS and Atom feed parsing, managing various XML formats and edge cases.

Step 2: Basic RSS Fetcher

Create news_aggregator.py:

import feedparser
from datetime import datetime

def fetch_rss_feed(feed_url):
    """
    Fetch and parse a single RSS feed.

    Args:
        feed_url (str): URL of the RSS feed

    Returns:
        list: Parsed articles with title, link, description, and date
    """
    feed = feedparser.parse(feed_url)

    articles = []
    for entry in feed.entries:
        article = {
            'title': entry.get('title', 'No title'),
            'link': entry.get('link', ''),
            'description': entry.get('summary', entry.get('description', 'No description')),
            'published': entry.get('published', entry.get('updated', 'Unknown date')),
            'source': feed.feed.get('title', 'Unknown source')
        }
        articles.append(article)

    return articles

# Test with a single feed
if __name__ == '__main__':
    feed_url = 'http://feeds.bbci.co.uk/news/rss.xml'
    articles = fetch_rss_feed(feed_url)

    print(f"Fetched {len(articles)} articles from BBC News\n")

    for article in articles[:5]:  # Show first 5
        print(f"Title: {article['title']}")
        print(f"Link: {article['link']}")
        print(f"Published: {article['published']}")
        print(f"Description: {article['description'][:100]}...")
        print("-" * 80)

Run it:

python news_aggregator.py

Step 3: Multi-Source Aggregator

Expand to fetch from multiple sources:

import feedparser
from datetime import datetime
from typing import List, Dict
import time

RSS_FEEDS = {
    'BBC News': 'http://feeds.bbci.co.uk/news/rss.xml',
    'TechCrunch': 'https://techcrunch.com/feed/',
    'The Guardian': 'https://www.theguardian.com/world/rss',
    'NPR': 'https://feeds.npr.org/1001/rss.xml'
}

def fetch_all_feeds(feed_dict: Dict[str, str]) -> List[Dict]:
    """
    Fetch articles from multiple RSS feeds.

    Args:
        feed_dict (dict): Dictionary mapping source names to RSS URLs

    Returns:
        list: Combined list of articles from all sources
    """
    all_articles = []

    for source_name, feed_url in feed_dict.items():
        print(f"Fetching {source_name}...")

        try:
            feed = feedparser.parse(feed_url)

            for entry in feed.entries:
                article = {
                    'title': entry.get('title', 'No title'),
                    'link': entry.get('link', ''),
                    'description': entry.get('summary', entry.get('description', 'No description')),
                    'published': entry.get('published', entry.get('updated', '')),
                    'source': source_name
                }
                all_articles.append(article)

            print(f"  ✓ Found {len(feed.entries)} articles")

        except Exception as e:
            print(f"  ✗ Error fetching {source_name}: {str(e)}")

        # Be respectful to servers
        time.sleep(0.5)

    return all_articles

def display_articles(articles: List[Dict], limit: int = 10):
    """Display articles in a readable format."""
    print(f"\n{'='*80}")
    print(f"Displaying {min(limit, len(articles))} of {len(articles)} total articles")
    print(f"{'='*80}\n")

    for idx, article in enumerate(articles[:limit], 1):
        print(f"{idx}. [{article['source']}] {article['title']}")
        print(f"   {article['link']}")
        print(f"   Published: {article['published']}")
        print(f"   {article['description'][:150]}...")
        print()

if __name__ == '__main__':
    # Fetch all articles
    articles = fetch_all_feeds(RSS_FEEDS)

    # Display results
    display_articles(articles, limit=15)

    # Simple filtering example (very limited compared to APIs)
    tech_articles = [a for a in articles if 'tech' in a['title'].lower() or 'tech' in a['description'].lower()]
    print(f"\nFound {len(tech_articles)} articles mentioning 'tech' (basic keyword match)")

Step 4: Add Sorting and Basic Filtering (extends Step 3)

Add these functions to your existing news_aggregator.py from Step 3. First, install the additional dependency:

pip install python-dateutil

Then add these new functions and imports to your file:

from datetime import datetime
from dateutil import parser as date_parser

def parse_date(date_string: str) -> datetime:
    """Attempt to parse various date formats."""
    try:
        return date_parser.parse(date_string)
    except:
        return datetime.min

def sort_articles_by_date(articles: List[Dict], reverse: bool = True) -> List[Dict]:
    """Sort articles by publication date."""
    return sorted(articles, key=lambda x: parse_date(x['published']), reverse=reverse)

def filter_articles(articles: List[Dict], keyword: str) -> List[Dict]:
    """
    Basic keyword filtering.

    Note: This is very limited compared to News APIs which offer
    boolean search, topic filters, country filters, etc.
    """
    keyword_lower = keyword.lower()
    return [
        a for a in articles
        if keyword_lower in a['title'].lower() or keyword_lower in a['description'].lower()
    ]

# Update the main block to use the new functions:
if __name__ == '__main__':
    articles = fetch_all_feeds(RSS_FEEDS)

    # Sort by date
    sorted_articles = sort_articles_by_date(articles)

    # Filter for technology news
    tech_news = filter_articles(sorted_articles, 'technology')

    print(f"Technology news: {len(tech_news)} articles")
    display_articles(tech_news, limit=10)

See the complete standalone script on GitHub: rss-feeds-tutorial-script.py

---

Implementation 2: JavaScript/Node.js News Aggregator

Step 1: Initialize Project and Install Dependencies

mkdir rss-news-app
cd rss-news-app
npm init -y
npm install rss-parser axios

Step 2: Basic RSS Fetcher

Create aggregator.js:

const Parser = require('rss-parser');
const parser = new Parser({
  timeout: 10000,
  headers: {'User-Agent': 'rss-parser'}
});

const RSS_FEEDS = {
  'BBC News': 'http://feeds.bbci.co.uk/news/rss.xml',
  'TechCrunch': 'https://techcrunch.com/feed/',
  'The Guardian': 'https://www.theguardian.com/world/rss',
  'NPR': 'https://feeds.npr.org/1001/rss.xml'
};

async function fetchRSSFeed(feedUrl, sourceName) {
  /**
   * Fetch and parse a single RSS feed
   * @param {string} feedUrl - URL of the RSS feed
   * @param {string} sourceName - Name of the news source
   * @returns {Array} Parsed articles
   */
  try {
    const feed = await parser.parseURL(feedUrl);

    const articles = feed.items.map(item => ({
      title: item.title || 'No title',
      link: item.link || '',
      description: item.contentSnippet || item.description || 'No description',
      published: item.pubDate || item.isoDate || 'Unknown date',
      source: sourceName
    }));

    return articles;
  } catch (error) {
    console.error(`Error fetching ${sourceName}:`, error.message);
    return [];
  }
}

// Test with single feed
(async () => {
  try {
    const articles = await fetchRSSFeed('http://feeds.bbci.co.uk/news/rss.xml', 'BBC News');
    console.log(`Fetched ${articles.length} articles from BBC News\n`);

    articles.slice(0, 5).forEach((article, idx) => {
      console.log(`${idx + 1}. ${article.title}`);
      console.log(`   ${article.link}`);
      console.log(`   Published: ${article.published}`);
      console.log(`   ${article.description.substring(0, 100)}...`);
      console.log('-'.repeat(80));
    });

    // Exit explicitly since rss-parser keeps event loop alive
    setTimeout(() => process.exit(0), 100);
  } catch (error) {
    console.error('Error:', error.message);
    process.exit(1);
  }
})();

Run it:

node aggregator.js

Step 3: Multi-Source Aggregator

const Parser = require('rss-parser');
const parser = new Parser({
  timeout: 10000,
  headers: {'User-Agent': 'rss-parser'}
});

const RSS_FEEDS = {
  'BBC News': 'http://feeds.bbci.co.uk/news/rss.xml',
  'TechCrunch': 'https://techcrunch.com/feed/',
  'The Guardian': 'https://www.theguardian.com/world/rss',
  'NPR': 'https://feeds.npr.org/1001/rss.xml',
  'Wired': 'https://www.wired.com/feed/rss'
};

async function fetchAllFeeds(feedsObject) {
  /**
   * Fetch articles from multiple RSS feeds concurrently
   * @param {Object} feedsObject - Object mapping source names to feed URLs
   * @returns {Array} Combined array of all articles
   */
  const feedPromises = Object.entries(feedsObject).map(async ([sourceName, feedUrl]) => {
    console.log(`Fetching ${sourceName}...`);

    try {
      const feed = await parser.parseURL(feedUrl);
      const articles = feed.items.map(item => ({
        title: item.title || 'No title',
        link: item.link || '',
        description: item.contentSnippet || item.description || 'No description',
        published: item.pubDate || item.isoDate || '',
        source: sourceName,
        categories: item.categories || []
      }));

      console.log(`  ✓ Found ${articles.length} articles from ${sourceName}`);
      return articles;

    } catch (error) {
      console.error(`  ✗ Error fetching ${sourceName}:`, error.message);
      return [];
    }
  });

  const resultsArray = await Promise.all(feedPromises);
  return resultsArray.flat();
}

function displayArticles(articles, limit = 10) {
  /**
   * Display articles in readable format
   */
  console.log('\n' + '='.repeat(80));
  console.log(`Displaying ${Math.min(limit, articles.length)} of ${articles.length} total articles`);
  console.log('='.repeat(80) + '\n');

  articles.slice(0, limit).forEach((article, idx) => {
    console.log(`${idx + 1}. [${article.source}] ${article.title}`);
    console.log(`   ${article.link}`);
    console.log(`   Published: ${article.published}`);
    console.log(`   ${article.description.substring(0, 150)}...`);
    console.log();
  });
}

function sortByDate(articles, descending = true) {
  /**
   * Sort articles by publication date
   */
  return articles.sort((a, b) => {
    const dateA = new Date(a.published);
    const dateB = new Date(b.published);
    return descending ? dateB - dateA : dateA - dateB;
  });
}

function filterByKeyword(articles, keyword) {
  /**
   * Basic keyword filtering
   * Note: Very limited compared to News API filtering capabilities
   */
  const keywordLower = keyword.toLowerCase();
  return articles.filter(article =>
    article.title.toLowerCase().includes(keywordLower) ||
    article.description.toLowerCase().includes(keywordLower)
  );
}

// Main execution
(async () => {
  try {
    // Fetch all feeds
    const allArticles = await fetchAllFeeds(RSS_FEEDS);

    // Sort by date
    const sortedArticles = sortByDate(allArticles);

    // Display all
    displayArticles(sortedArticles, 15);

    // Example: Filter for artificial intelligence related news
    const aiNews = filterByKeyword(sortedArticles, 'artificial intelligence');
    console.log(`\nFiltered for "artificial intelligence": ${aiNews.length} articles found`);
    displayArticles(aiNews, 5);

    // Exit explicitly since rss-parser keeps event loop alive
    setTimeout(() => process.exit(0), 100);
  } catch (error) {
    console.error('Error:', error.message);
    process.exit(1);
  }
})();

Run it:

node aggregator.js

See the complete standalone script on GitHub: rss-feeds-tutorial-script.js

---

The Problem with RSS Feeds: Why They’re Limited

Now that you’ve built a working RSS aggregator, let’s discuss why RSS feeds are problematic for production applications:

1. No Advanced Filtering

With RSS, you get what the publisher provides—period. You cannot:

• Filter by topic or category across sources
• Search by keyword across all feeds simultaneously
• Filter by country, language, or source type
• Exclude specific topics or keywords
• Query by date range beyond what’s in the feed

Example limitation: If you want “technology news from US sources published in the last 7 days,” you’d need to:

1. Manually identify US technology RSS feeds
2. Fetch each feed individually
3. Parse and filter each feed’s XML
4. Implement your own date filtering
5. Combine and deduplicate results

With a News API, this is a single request:

fetch('https://api.newsdatahub.com/v1/news?topic=technology&country=US&start_date=2025-12-22&per_page=50', {
  headers: {
    'X-API-Key': 'YOUR_KEY',
    'User-Agent': 'RSS-Tutorial-NewsAggregator/1.0-js'
  }
})

2. Inconsistent Data Formats

Every publisher implements RSS slightly differently:

• Some use RSS 2.0, others use Atom
• Field names vary (pubDate vs published vs updated)
• Some include full content, others just snippets
• Media attachments have no standard format
• Categories/tags are publisher-specific

Your parser must handle all these variations, leading to fragile code that breaks when publishers change their feed structure.

3. No Historical Data

RSS feeds typically show only the 10-25 most recent articles. Want to:

• Analyze trends over the past month?
• Backfill data for research?
• Compare today’s coverage to last week’s?

Not possible with RSS. Feeds only show what’s currently in the XML file.

4. Limited Metadata

RSS provides basic fields: title, link, description, date. You don’t get:

• Topics — Automatic categorization (politics, technology, health, etc.)
• Sentiment scores — Positive/negative/neutral sentiment analysis
• Source metadata — Political leaning, reliability scores, source type
• Keywords — Extracted key terms from content
• Related articles — Semantic similarity to find connected stories

All this metadata requires running your own NLP/ML pipelines—expensive and complex.

5. Reliability and Maintenance Issues

RSS feeds break. Often. They:

• Change URLs without notice
• Return 404 errors when sites redesign
• Have inconsistent update schedules
• Lack error messages when problems occur
• Provide no SLA or uptime guarantees

Real scenario: You’re aggregating 50 RSS feeds. Over 6 months:

• 5 feeds change URLs (your app breaks)
• 3 feeds get discontinued entirely
• 7 feeds change their XML structure (parsing errors)
• 2 feeds start rate-limiting you (random failures)

You’re now maintaining a list of broken feeds and debugging XML parsing errors instead of building features.

6. Scalability Challenges

To aggregate comprehensive news coverage, you need hundreds of RSS feeds. This means:

• Hundreds of HTTP requests to fetch feeds
• XML parsing for each feed (CPU intensive)
• Storage and caching infrastructure
• Deduplication logic (same stories appear on multiple feeds)
• Monitoring to detect broken feeds

Your infrastructure cost and complexity grow linearly with feed count.

7. No Search Capability

Want to find all articles mentioning “cybersecurity breach” from the past week? With RSS:

1. Fetch all feeds (hundreds of requests)
2. Parse all XML
3. Implement keyword search yourself
4. Filter by date yourself
5. Deduplicate results yourself
6. Rank/sort yourself

With a News API:

import requests

response = requests.get(
    'https://api.newsdatahub.com/v1/news',
    headers={
        'X-API-Key': 'YOUR_KEY',
        'User-Agent': 'RSS-Tutorial-NewsAggregator/1.0-py'
    },
    params={
        'q': '(cybersecurity AND breach)',
        'start_date': '2025-12-22',
        'per_page': 50
    }
)

articles = response.json()['data']

Done. One request, structured JSON response, no parsing, no deduplication.

---

The Superior Alternative: News APIs

Modern News APIs like NewsDataHub solve every RSS limitation:

Comparison Table

Feature	RSS Feeds	NewsDataHub API
Sources	One per feed	6,500+ sources in one API
Daily articles	~20 per feed	200,000+ aggregated daily
Filtering	None	Topic, country, language, source type, political leaning, date range
Search	No	Full-text search with AND/OR/NOT operators
Historical data	Last 10-25 items only	30 days (free) to 3+ years (enterprise)
Data format	Inconsistent XML	Consistent JSON
Metadata	Basic (title, link, date)	Rich (topics, keywords, sentiment, source metadata)
Related articles	No	/related endpoint for semantic similarity
Pagination	No	Cursor-based pagination
Reliability	Feeds break frequently	Production SLA, monitoring
Rate limiting	No control	Defined limits per tier
Setup complexity	Parse XML for each feed	Single API endpoint
Maintenance	Constant (broken feeds)	Minimal (API handles source changes)

Why News APIs Are Better for Production

1. One Request Instead of Hundreds

Instead of fetching 50+ RSS feeds, one API call retrieves articles from 6,500+ sources:

// RSS approach: 50+ requests
const feeds = [/* 50 feed URLs */];
const allArticles = await Promise.all(
  feeds.map(url => fetchAndParseRSSFeed(url))
);

// News API approach: 1 request
const response = await fetch('https://api.newsdatahub.com/v1/news?topic=technology&per_page=100', {
  headers: {
    'X-API-Key': 'YOUR_KEY',
    'User-Agent': 'RSS-Tutorial-NewsAggregator/1.0-js'
  }
});
const articles = await response.json();

2. Powerful Filtering Built-In

import requests

# Get English technology news from US sources, excluding sports, from the last 3 days
response = requests.get(
    'https://api.newsdatahub.com/v1/news',
    headers={
        'X-API-Key': 'YOUR_KEY',
        'User-Agent': 'RSS-Tutorial-NewsAggregator/1.0-py'
    },
    params={
        'topic': 'technology',
        'country': 'US',
        'language': 'en',
        'exclude_topic': 'sports',
        'start_date': '2025-12-26',
        'per_page': 50
    }
)

articles = response.json()['data']

This would require manually maintaining a list of US tech RSS feeds, fetching all of them, parsing XML, implementing date filtering, and excluding sports content yourself with RSS.

3. Consistent Structure

Every response follows the same JSON structure:

{
  "data": [
    {
      "id": "abc123",
      "title": "Article Title",
      "description": "Article summary",
      "content": "Full article text...",
      "article_link": "https://example.com/article",
      "source_title": "TechCrunch",
      "source_link": "https://techcrunch.com",
      "pub_date": "2025-12-29T10:30:00Z",
      "creator": "Author Name",
      "keywords": ["AI", "technology"],
      "topics": ["technology"],
      "language": "en",
      "sentiment": {
        "pos": 0.7,
        "neg": 0.1,
        "neu": 0.2
      },
      "source": {
        "country": "US",
        "political_leaning": "center",
        "reliability_score": 8.5,
        "type": "digital_native"
      }
    }
  ],
  "total_results": 15678,
  "per_page": 50,
  "next_cursor": "eyJvZmZzZXQiOjUwfQ=="
}

No XML parsing. No handling format inconsistencies. Just clean, predictable JSON.

4. Built-In Semantic Search

Find related articles using the /related endpoint:

# Find articles semantically similar to a given article
article_id = "abc123"
response = requests.get(
    f'https://api.newsdatahub.com/v1/news/{article_id}/related',
    headers={
        'X-API-Key': 'YOUR_KEY',
        'User-Agent': 'RSS-Tutorial-NewsAggregator/1.0-py'
    },
    params={'per_page': 10}
)

related_articles = response.json()['data']

This analyzes title, description, topics, and keywords to surface contextually similar articles—impossible with RSS feeds unless you build your own NLP pipeline.

5. Production-Ready Infrastructure

• Uptime monitoring — API status at status.newsdatahub.com
• Rate limiting — Defined per tier, prevents overload
• Error handling — Clear HTTP status codes and error messages
• Documentation — Comprehensive API reference at newsdatahub.com/docs
• Support — Help when you need it

RSS feeds provide none of this. When a feed breaks, you’re on your own.

---

When to Use RSS vs News APIs

Use RSS Feeds When:

• Learning XML parsing or building a portfolio project
• Aggregating 3-5 specific sources you personally follow
• Building a simple personal news reader
• Budget is $0 and requirements are minimal
• You don’t need filtering, search, or historical data

Use News APIs When:

• Building production applications
• Need filtering by topic, country, language, source type
• Require full-text search across all sources
• Want historical data for trend analysis
• Need reliable infrastructure with SLAs
• Building news monitoring, media intelligence, or analytics products
• Want to access 6,500+ sources without managing individual feeds
• Require rich metadata (sentiment, topics, source reliability)
• Need semantic similarity for related articles
• Want to scale without infrastructure complexity

---

Migration Path: From RSS to News API

If you’ve built an RSS aggregator and want to upgrade to a News API:

Before (RSS):

import feedparser

feeds = [
    'http://feeds.bbci.co.uk/news/rss.xml',
    'https://techcrunch.com/feed/',
    # ... 50 more feeds
]

all_articles = []
for feed_url in feeds:
    feed = feedparser.parse(feed_url)
    for entry in feed.entries:
        all_articles.append({
            'title': entry.title,
            'link': entry.link,
            'published': entry.published
        })

# Now manually filter, deduplicate, etc.

After (NewsDataHub API):

import requests

response = requests.get(
    'https://api.newsdatahub.com/v1/news',
    headers={
        'X-API-Key': 'YOUR_KEY',
        'User-Agent': 'RSS-Tutorial-NewsAggregator/1.0-py'
    },
    params={
        'topic': 'technology',
        'language': 'en',
        'per_page': 100
    }
)

articles = response.json()['data']
# Already filtered, deduplicated, structured

What You Gain:

• ✓ 60-80% less code — No XML parsing, no deduplication logic
• ✓ 50x more sources — 6,500+ sources vs your 50 RSS feeds
• ✓ Advanced filtering — Topic, country, language, date range, and more
• ✓ Consistent data — Predictable JSON vs unpredictable XML
• ✓ Minimal maintenance — No broken feeds to fix
• ✓ Better performance — One API call vs dozens/hundreds of HTTP requests

---

Getting Started with NewsDataHub API

NewsDataHub offers a free tier with 100 requests per day—perfect for testing and small projects:

1. Sign up at newsdatahub.com/login
2. Get API key instantly (no credit card required)
3. Make your first request:

curl -X GET "https://api.newsdatahub.com/v1/news?topic=technology&per_page=10" \
  -H "X-API-Key: YOUR_KEY" \
  -H "User-Agent: RSS-Tutorial-NewsAggregator/1.0-curl"

Example: Technology News

import requests

API_KEY = 'your_api_key_here'

response = requests.get(
    'https://api.newsdatahub.com/v1/news',
    headers={
        'X-API-Key': API_KEY,
        'User-Agent': 'RSS-Tutorial-NewsAggregator/1.0-py'
    },
    params={
        'topic': 'technology',
        'language': 'en',
        'per_page': 20
    }
)

if response.status_code == 200:
    data = response.json()

    print(f"Found {data['total_results']} articles\n")

    for article in data['data']:
        print(f"[{article['source_title']}] {article['title']}")
        print(f"Topics: {', '.join(article['topics'])}")
        print(f"Published: {article['pub_date']}")
        print(f"Link: {article['article_link']}\n")
else:
    print(f"Error: {response.status_code}")

For complete API documentation, visit newsdatahub.com/docs.

---

Conclusion

RSS feeds are a great learning tool and work fine for simple personal projects aggregating a handful of sources. However, for production applications requiring comprehensive news coverage, advanced filtering, reliable infrastructure, and rich metadata, modern News APIs like NewsDataHub provide a dramatically superior experience.

RSS limitations:

• No filtering or search
• Inconsistent XML formats
• No historical data
• Limited metadata
• Feeds break frequently
• Doesn’t scale beyond dozens of sources

NewsDataHub API advantages:

• 6,500+ sources in one API
• Advanced filtering (topic, country, language, date, source type)
• Full-text search with boolean operators
• Consistent JSON responses
• Rich metadata (topics, sentiment, source details)
• Semantic similarity for related articles
• Production-ready reliability

Ready to upgrade from RSS to a modern News API? Start free at newsdatahub.com and access 6,500+ news sources with a single API call.

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FAQ

• Can I use RSS feeds for a production news application?

  Technically yes, but it’s not recommended. RSS feeds lack filtering, search, historical data, and reliable infrastructure. Production apps need consistent data structure, comprehensive coverage, and uptime guarantees—all of which News APIs provide but RSS doesn’t.

• How many RSS feeds would I need to match NewsDataHub’s coverage?

  NewsDataHub aggregates from 6,500+ sources. Managing even 100 RSS feeds is challenging due to XML parsing, broken feeds, format inconsistencies, and maintenance overhead. A News API replaces thousands of RSS feeds with a single, reliable endpoint.

• Are RSS feeds free while News APIs cost money?

  RSS feeds are free, but they come with hidden costs: development time for XML parsing, infrastructure for fetching hundreds of feeds, maintenance when feeds break, and opportunity cost of limited features. NewsDataHub offers a free tier (100 requests/day) for testing and small projects, with paid tiers providing higher limits and advanced features.

• Can I filter RSS feeds by topic or country?

  No. RSS feeds provide a fixed list of articles—you get what the publisher includes. Filtering requires fetching all feeds, parsing all XML, and implementing your own filtering logic. News APIs offer built-in filtering by topic, country, language, source type, political leaning, and date range.

• What happens when an RSS feed changes its URL or structure?

  Your application breaks. RSS feeds frequently change URLs during site redesigns, alter their XML structure, or get discontinued without notice. You must monitor each feed and update your code when changes occur. News APIs abstract this away—the API provider handles source changes.

• How do I search across multiple RSS feeds?

  You can’t search across feeds natively. You must fetch all feeds, parse all XML, store the content, and implement your own search indexing. News APIs provide full-text search across all sources with a single API request using boolean operators (AND, OR, NOT).

• Do RSS feeds provide sentiment analysis or topic classification?

  No. RSS feeds provide basic fields (title, link, description, date). Advanced metadata like sentiment scores, automatic topic categorization, and source reliability ratings require running your own ML/NLP pipelines. NewsDataHub API includes this metadata in every article response.

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Olga S.

Founder of NewsDataHub — Distributed Systems & Data Engineering

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