Building a custom RSS aggregator for real-time industry news

Information overload is no quiet problem for Australian operators running lean teams. A founder monitoring the ASX from a co-working space in Sydney, a content lead in Melbourne tracking AFR headlines, and a solo developer in Brisbane watching the Pilbara mining cycle all face the same drag: dozens of tabs, half-checked newsletters, and a calendar full of meetings that leave no room to actually read.

Most news that matters to Australian businesses arrives through a familiar pipeline. The Australian Financial Review publishes market-moving pieces before the open. ABC News drops regional updates on resources and agriculture. The Conversation and SmartCompany run longer analysis. Industry bodies such as AusBiotech, the Minerals Council of Australia, and the Australian Information Industry Association circulate technical briefs that rarely trend on social media. When you stitch those sources with global wires, the volume of useful content far exceeds what any human can scan in a working day.

Pre-built feed readers handle the basics. They struggle when you need to filter by Australian jurisdiction, weight results by industry code, or blend an Atom feed from a government portal with a custom XML endpoint from a private research subscription. They rarely expose clean APIs for downstream tools, and free tiers tend to throttle after a few dozen subscriptions. A purpose-built aggregator removes those ceilings.

This walkthrough covers the practical steps to design, code, deploy, and maintain a custom RSS aggregator tuned for industry intelligence. You will see how to set up a parser, normalise entries, run background jobs, and ship a small web interface your team in Perth or Adelaide can open on a phone between flights.

Why a custom aggregator beats pre-built readers

The case for building your own pipe comes down to three things: control, cost, and continuity. A self-hosted aggregator lets you decide what counts as a source, how entries are scored, and where the data lives afterwards. You can store raw XML in a local SQLite file, push structured items to a Postgres database, or fan the output into a Telegram channel for staff in regional offices.

Cost scales differently. A paid Inoreader or Feedly Pro account charges per seat, which gets expensive once a marketing team in Parramatta wants access. A small VPS in Sydney or a serverless function running on NBN-backed infrastructure costs a few dollars a month and serves the whole company. The marginal cost of an extra feed is effectively zero.

Continuity matters when feeds shift. Australian publishers change XML schemas, tighten robots.txt rules, or move from RSS to Atom without warning. A custom stack lets you patch one parser at a time, log the failures, and keep the rest of the dashboard running. Off-the-shelf products roll out blanket updates that often break niche configurations in ways you cannot fix.

Mapping the data sources that matter in Australia

Before writing any code, list the sources you actually want to track. A solid starting point for industry intelligence blends mainstream business press, sector-specific trade publications, and government open-data feeds. The AFR and The Australian cover the macro picture, while Stockhead, Mining.com.au, and Business News Australia focus on the ASX and resources sector.

Regional outlets add depth. The West Australian covers Perth and the wider Pilbara economy. The Brisbane Times and InDaily out of Adelaide track state-level policy moves. Industry associations such as the Australian Computer Society, the Australian Renewable Energy Agency, and FinTech Australia publish event announcements, grant rounds, and policy submissions that rarely surface on general news apps.

For a balanced pipeline, mix international wires with local commentary. Reuters, Bloomberg, and the Wall Street Journal supply the global frame, while The Conversation Australia and Crikey provide the analytical layer. Pair those with RSS endpoints from Reserve Bank of Australia press releases, university research offices, and the ASX company announcements feed. The richer the source list, the more value a well-tuned aggregator delivers.

Preparing the development environment

A modern aggregator fits comfortably on a small machine. Node.js with TypeScript or Python 3.11+ both work well. Pick a stack your team already understands, because the value of this project is maintenance as much as initial build. On a MacBook in a Melbourne café or a Linux box under a desk in Canberra, the same packages install cleanly.

Create a virtual environment, install a parser library, and set up a lightweight web framework. In Python, feedparser, httpx, and FastAPI cover fetch, parse, and serve. In Node, rss-parser, axios, and Express or Hono cover the same ground. Add better-sqlite3 for storage and pino for structured logs that you can ship to a free dashboard later.

Containerise early. A simple Dockerfile with a cron-based scheduler and a static front-end makes the project portable between a Sydney-region VPS, a Cloudflare Worker, and a Raspberry Pi under a desk in Hobart. Treat the aggregator as a long-lived service, not a script you run by hand.

Fetching and parsing feed XML

Fetching is the easy half. Iterate through the source list, send a polite request with a real User-Agent that identifies your tool, and respect any Retry-After headers. Many Australian publishers rate-limit aggressive bots, so a 200-millisecond pause between requests keeps you on the right side of fair use.

Parsing is where the work lives. RSS 2.0, Atom 1.0, and RDF share the same intent but use different element names. feedparser and rss-parser handle the dialects for you, returning a normalised object with title, link, published date, summary, and author. Store the raw payload alongside the parsed object so you can replay entries when an upstream feed rewrites history.

Normalise timestamps to UTC, convert HTML entities in summaries, and strip tracking parameters from outbound links. Australian feeds often include UTM tags that pollute downstream analytics; clean them at ingestion so the front-end stays tidy. A small cleaning module with a few regexes and an HTML whitelist is usually enough.

Filtering, deduplicating, and normalising entries

A raw feed pipeline produces noise. The same BHP press release appears on the ASX feed, the AFR wire, and the Minerals Council newsletter within an hour. Without deduplication, the dashboard shows three identical headlines and readers stop trusting the tool.

Hash each entry on a combination of canonical link and normalised title, then drop matches against a sliding window in your database. A simple Levenshtein check catches near-duplicates where the title changed by a single word. Keep the original timestamps and source metadata, so a reader in Adelaide can still see which outlet broke the story first.

Layer in scoring next. Assign higher weight to trusted primary sources, lower weight to syndication mirrors. Tag entries with industry codes, then let a user-facing filter hide anything that does not match a chosen tag. This is where a custom aggregator pulls ahead of generic readers, because the rule set reflects your business rather than the average subscriber.

Designing a clean front-end for the feed

A working backend deserves a small, fast interface. Skip frameworks that ship megabytes of JavaScript. A server-rendered page with a touch of htmx or vanilla fetch calls keeps load times low on patchy regional 4G. Build three views: a chronological list, a category view, and a saved-search view that highlights flagged items.

Styling should be quiet. A neutral background, a single accent colour, and a clear date stamp let readers scan dozens of headlines without eye fatigue. Group entries by hour rather than by minute; a long list of 09:01, 09:02, 09:03 timestamps adds nothing and slows comprehension. Add a quiet badge for entries tagged with the user's watchlist keywords, such as a specific ASX code or a competitor's name.

For mobile users, the same interface should reflow into a single column with a sticky filter bar at the top. Test the layout on a real device over the Telstra or Optus network, not only on a fast office connection. A snappy front-end is what keeps the team opening the dashboard each morning instead of falling back to email.

Hosting, scheduling, and long-term maintenance

Deployment decisions shape the project's lifespan. A $5 VPS in the ap-southeast-2 region gives low latency for Australian readers and keeps data residency local. Pair it with a free Cloudflare account for caching and basic DDoS protection. If the budget is tight, a serverless function scheduled every fifteen minutes handles the fetch and parse, while a static page on a free host serves the results.

Schedule fetches with a cron job or a managed scheduler, and stagger sources so the load stays even. Run a daily health check that records the HTTP status of every feed, the number of new entries, and the median parse time. Email yourself a weekly digest; a quiet week of zero new entries often points to a publisher that has changed its endpoint or blocked your IP.

Approach Cost per month Setup effort Customisation depth Best fit
Self-hosted Node or Python aggregator on a Sydney VPS 5 to 15 AUD Moderate Full control of sources, scoring, and storage Teams of 5 to 50 that need Australian data residency
Feedly Pro 9 to 18 USD per seat Low Limited to built-in rules and integrations Solo readers who want a polished mobile app
Inoreader 8 to 16 USD per seat Low Strong filters, weaker downstream API Analysts who want shared boards and minimal setup
NewsBlur 12 USD per seat Low to moderate Trainable classifiers, no real API Researchers who need ML-based relevance tuning
Newsboat on a local workstation 0 AUD Low Reads what is on disk only Power users with one machine and no shared needs

Quick-start resources for the first build

Libraries that handle the heavy lifting

Sources that anchor an Australian feed mix

A working aggregator changes how a small team consumes industry news. Once the pipeline runs quietly in the background, the morning ritual shifts from chasing links to scanning a curated list, and the people who act on information first win the conversations that matter. Open the VTU Script community forum, drop the source list you plan to track, and trade parser patches with other builders shipping the same kind of tool across Nigeria, Australia, and beyond.