A campus events page is easy for a person to read and hard to search. A scraper bot fixes that by fetching the listings, splitting each one into fields (title, date, place, link), and storing them as records you can sort, filter and revisit. That is the idea behind campus-bot, a project filed for MLH Global Hack Week: Data. This article doesn’t describe that project’s code. Its stack, source page and deployment plan aren’t stated anywhere we could confirm. Instead it lays out the design choices that decide whether a small events database is trustworthy or quietly wrong.
What the pipeline does
Any events-to-database bot has the same five stages:
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- Fetch the source, preferably from an official feed or API.
- Extract raw fields from each listing.
- Normalize them: parse dates into one format, tidy whitespace, standardize locations.
- Deduplicate and store the records.
- Serve them through a sortable, searchable interface that links back to the original listing.
Comparable public hackathon and opportunity directories are built the same way. They document per-source adapters, normalized fields, deduplication, caching and outbound links to the original listing. Treat those as design precedents. They don’t show that campus-bot does any of this.
Start with an authorized source
Prefer a feed or API
Many campus event systems publish an RSS, iCal or JSON feed. If one exists, use it: it’s more stable than page markup and is clearly meant for reuse. One comparable opportunity aggregator explicitly favors official API/JSON sources, falls back to polite scraping of public pages, and links back to the original.
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If you must scrape HTML
- Read the site’s terms and its robots.txt before writing any code.
- Fetch only public pages, at a low rate, with a descriptive User-Agent and a contact address.
- Cache responses so you don’t re-request unchanged pages.
- Show attribution and keep a link to each original listing.
- Skip anything behind a login. The same aggregator documents avoiding some restricted sources, which is a sound rule for a student project too.
Design the record
The fields you extract decide what users can sort and filter. Start from what the campus page actually shows, then add only fields you can fill reliably. A comparable hackathon directory’s event data includes an identifier, source, URL, start and end times, format, location, themes and status. A campus-scale version could look like this:
| Field | Purpose | Notes |
|---|---|---|
| id | Stable key for deduplication | Derive from source + original URL, not from a row counter |
| title | Display and keyword search | Strip stray markup and whitespace |
| start / end (or deadline) | Sorting and “upcoming” filters | Store as ISO 8601 with a timezone |
| format and location | Filter for in-person, online or hybrid | Keep the raw text if parsing fails |
| source_url | Link back to the original listing | Never drop this |
| source | Which page or feed it came from | Needed once you add a second source |
| last_seen / updated_at | Freshness | Lets the interface show when data was last refreshed |
| status | Active, cancelled, past | Mark records missing from the source rather than silently deleting them |
An “opportunities” database, as opposed to a plain events calendar, also benefits from a type or tag field (workshop, career fair, hackathon, scholarship) and a deadline separate from the event date. Add those only if the source text supports them.
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Normalize and deduplicate
- Dates are the usual failure point. Listings mix “Oct 14”, “10/14/26”, “Tuesday, 2 PM” and ranges. Parse into one format with an explicit timezone, and flag unparseable values instead of guessing.
- Duplicates appear when an event is posted under several departments or recurs weekly. Match on the original URL first, then on a normalized title plus start time. Treat recurring events as separate occurrences that share a series.
- Malformed listings (missing date, empty title) should be stored with a flag or logged, not crash the run or vanish silently.
Plan for source failure
Pages get redesigned and servers go down. Comparable directories handle this with independent adapters per source and per-source health reporting, so one broken scraper doesn’t take everything down and a partial outage is visible. For a single-source bot, the minimum is:
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- If a run returns zero records or far fewer than usual, keep the previous data and mark the source unhealthy.
- Show “last updated” in the interface so users can judge freshness.
Make it sortable and searchable
For a few hundred records, SQLite with a full-text index, or even a static JSON file searched in the browser, is enough. Sort by start date by default, and let users filter by format, type and date range. Each result should link out to the original listing, since that page is the source of truth for changes and registration.
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Context: MLH and Global Hack Week: Data
Major League Hacking says on its organizer guide that it supports more than 65,000 developers, designers and makers each semester through 200+ official hackathons worldwide; the page shows no year for those figures. MLH’s member-event guidelines for the 2026–27 academic year cover event websites, check-in, project data and reporting. Its project-submission data includes the project title, team members and school, project URL, description, prize categories and technologies. That describes MLH’s member-event reporting, not a schema every project must follow, and nothing confirms that campus-bot is an MLH member event.
A secondary GitHub issue listing gives September 11–17, 2026 as the dates for Global Hack Week: Data. That isn’t primary confirmation, so check MLH’s official event page for dates and participation rules, and the project issue for what the bot actually does.
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Publishing it
If the database goes public, it needs a host that can run a scheduled job and serve the site. The right choice depends on the stack, which isn’t established for this project. Whatever you pick, schedule refreshes at a modest interval (daily is typically plenty for campus events), and keep the scraper’s rate and attribution rules in the README.
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