Static, fast, SEO-friendly bank holiday website

Hacker News

Hi all, made a tiny website in Jekyll that tells you if the current date is a bank holiday in England and Wales. It leverages the Gov UK Bank Holidays API ( https://www.api.gov.uk/gds/bank-holidays/ ), runs a script once a day and creates the static files for each day available in the API (see https://isitbankholiday.com/sitemap.xml ). The site is then deployed to Cloudflare Pages, where a CF Pages serverless function maps the request's current date to a static page to render, and renders it as the homepage. It's a nice exercise in static page generation and programmatic SEO. Already getting organic traffic from search engines and it's only been live 2 weeks. Let me know how I could improve it or if you have any questions about CloudFlare Pages hosting, Jekyll, etc!

Visit product View on Hacker NewsJun 14, 2024

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

64%64% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Product HuntOn track for Day 1 leaderboard · Strong signals: tiny · Missing: mac, agents, macos

57%57% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released

52%52% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoStrong fit for a featured deal · Strong signals: host, friendly · Missing: plus, platform, intuitive

51%51% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

46%46% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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