Rainbow Parentheses Highlighting on GitHub (Clojure etc.)

Hacker News

Run it in console (i.e., devtools or other) on a github source view page. (E.g., https://github.com/LightTable/LightTable/blob/master/src/lt/object.cljs) If someone wants to make this into a Chrome Extension, that would be cool. I realize the code is terrible; I just threw it together in dev tools. var rainbow_parens = function(jq_el) { var html = jq_el.html(); var processed_html = ""; var nesting_level = -160; var color; for (var i = 0; i < html.length; i++) { if (html[i] == '(') { nesting_level += 160; color = 'rgba(' + Math.min(Math.max((nesting_level % 510) - 255, 0), 255) + ',0,' + Math.min((nesting_level % 510), 255) + ',1)'; processed_html += '<span style="color: ' + color + '; text-shadow: -1px 0px 0px ' + color + '">(</span>'; } else if (html[i] == ')') { color = 'rgba(' + Math.min(Math.max((nesting_level % 510) - 255, 0), 255) + ',0,' + Math.min((nesting_level % 510), 255) + ',1)'; processed_html += '<span style="color: ' + color + '; text-shadow: 1px 0px 0px ' + color + '">)</span>'; nesting_level -= 160; } else { processed_html += html[i]; } } jq_el.html(processed_html); };rainbow_parens($('.code-body'));

Visit product View on Hacker NewsJan 11, 2014

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Actual performance

2points

Did not reach leaderboard

Launch Intel predictions

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Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

47%47% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

44%44% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: code · Missing: mac, agents, macos

41%41% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

36%36% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

25%25% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

23%23% 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

7%7% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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