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Functional Concepts in JavaScript with Ramda
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| <?xml version="1.0" encoding="UTF-8"?> | |
| <!--Xholon Workbook http://www.primordion.com/Xholon/gwt/ MIT License, Copyright (C) Ken Webb, Mon Mar 25 2019 18:43:25 GMT-0400 (Eastern Daylight Time)--> | |
| <XholonWorkbook> | |
| <Notes><![CDATA[ | |
| Xholon | |
| ------ | |
| Title: Functional Concepts in JavaScript with Ramda | |
| Description: | |
| Url: http://www.primordion.com/Xholon/gwt/ | |
| InternalName: dc314bcfd6a9c81948543c330d79656e | |
| Keywords: | |
| My Notes | |
| -------- | |
| March 21, 2019 | |
| To install ramda | |
| ---------------- | |
| cd ~/nodespace | |
| npm install ramda | |
| cd ~/nodespace/node_modules/ramda/dist | |
| this contains ramda.js and ramda.min.js | |
| To run this Xholon app | |
| ---------------------- | |
| http://127.0.0.1:8888/Xholon.html?app=Functional+Concepts+in+JavaScript+with+Ramda&src=lstr&gui=clsc&jslib=ramda.min | |
| http://www.primordion.com/Xholon/gwt/Xholon.html?app=dc314bcfd6a9c81948543c330d79656e&src=gist&gui=clsc&jslib=ramda.min | |
| Ramda R.clone() | |
| --------------- | |
| see: ~/gwtspace/Xholon/Xholon/script/javascript.ramda01.js (current contents) | |
| // Ramda JavaScript library | |
| // March 23, 2019 | |
| // http://127.0.0.1:8888/Xholon.html?app=HelloWorld&gui=clsc&jslib=ramda.min | |
| const rava = R.clone(xh.avatar()); | |
| rava.name(); | |
| rava.action("param transcript false;param debug true"); | |
| rava.action("who"); | |
| rava.action("where"); | |
| rava.action("look"); | |
| rava.action("first"); | |
| rava.action("go 0"); | |
| rava.action("help"); | |
| rava.action("build Zebra"); // FIXED TypeError: xhcEnt_0_g$ is null, TreeNodeFactoryNew .getXholonClassNode() line 925 | |
| rava.action("appear"); // causes rava to have a parent node, to actually be part of the Xholon tree | |
| R.toPairs(rava); | |
| rava.action("build Hello"); // this is OK; Hello already exists in the IH | |
| References | |
| ---------- | |
| (1) https://www.knowthen.com/blog | |
| 1 hour video course by James Moore | |
| I registered for the course, watched the videos, and feel that it was excellent | |
| (2) https://github.com/knowthen/ramdatutorial | |
| .json and .js files for the course | |
| (3) https://github.com/knowthen/ramdatutorial/blob/master/index.js | |
| (4) https://ramdajs.com/ | |
| Ramda | |
| A practical functional library for JavaScript programmers. | |
| (5) | |
| (6) https://stackoverflow.com/questions/40361059/where-can-i-find-an-explanation-summary-of-symbols-used-to-explain-functional-pr | |
| The API documentation for the JavaScript functional programming library Ramda.js contains symbolic abbreviations but does not provide a legend for understanding these. | |
| Is there a place (website, article, cheatsheet, etc.) that I can go to to decipher these? | |
| Some examples from the Ramda.js API documentation: | |
| Number -> Number -> Number | |
| Apply f => f (a -> b) -> f a -> f b | |
| Number -> [a] -> [[a]] | |
| (*... -> a) -> [*] -> a | |
| {k: ((a, b, ..., m) -> v)} -> ((a, b, ..., m) -> {k: v}) | |
| Filterable f => (a -> Boolean) -> f a -> f a | |
| Lens s a = Functor f => (a -> f a) -> s -> f s | |
| (acc -> x -> (acc, y)) -> acc -> [x] -> (acc, [y]) | |
| (Applicative f, Traversable t) => (a -> f a) -> t (f a) -> f (t a) | |
| It's called the Hindley-Milner type system | |
| (7) https://en.m.wikipedia.org/wiki/Hindley%E2%80%93Milner_type_system | |
| A Hindley–Milner (HM) type system is a classical type system for the lambda calculus with parametric polymorphism. | |
| It is also known as Damas–Milner or Damas–Hindley–Milner. | |
| It was first described by J. Roger Hindley and later rediscovered by Robin Milner. | |
| Luis Damas contributed a close formal analysis and proof of the method in his PhD thesis. | |
| (8) https://github.com/ramda/ramda/wiki | |
| (9) https://github.com/ramda/ramda/wiki/Type-Signatures | |
| Type Signatures | |
| (or "What are all those funny arrows about?") | |
| (10) https://github.com/fantasyland/fantasy-land | |
| Specification for interoperability of common algebraic structures in JavaScript | |
| ]]></Notes> | |
| <_-.XholonClass> | |
| <PhysicalSystem/> | |
| <Block/> | |
| <Cities/> | |
| <Reducer/> | |
| <GroupByPropReducer/> | |
| <CalcScorer/> | |
| </_-.XholonClass> | |
| <xholonClassDetails> | |
| </xholonClassDetails> | |
| <PhysicalSystem> | |
| <Block/> | |
| <!-- cities.json from ref [2] --> | |
| <Cities><Attribute_String> | |
| [ | |
| { | |
| "name": "Bangkok", | |
| "country": "TH", | |
| "region": "SE Asia", | |
| "cost": 1380, | |
| "currency": "USD", | |
| "temp": 302.03888888888895, | |
| "humidity": 78, | |
| "internetSpeed": 20 | |
| }, | |
| { | |
| "name": "Chiang Mai", | |
| "country": "TH", | |
| "region": "SE Asia", | |
| "cost": 654, | |
| "currency": "USD", | |
| "temp": 299.8166666666667, | |
| "humidity": 83, | |
| "internetSpeed": 20 | |
| }, | |
| { | |
| "name": "Pattaya", | |
| "country": "TH", | |
| "region": "SE Asia", | |
| "cost": 1183, | |
| "currency": "USD", | |
| "temp": 301.48333333333335, | |
| "humidity": 88, | |
| "internetSpeed": 20 | |
| }, | |
| { | |
| "name": "Phuket", | |
| "country": "TH", | |
| "region": "SE Asia", | |
| "cost": 1040, | |
| "currency": "USD", | |
| "temp": 302.03888888888895, | |
| "humidity": 74, | |
| "internetSpeed": 20 | |
| }, | |
| { | |
| "name": "Hoi An", | |
| "country": "VN", | |
| "region": "SE Asia", | |
| "cost": 1083, | |
| "currency": "USD", | |
| "temp": 299.2611111111112, | |
| "humidity": 83, | |
| "internetSpeed": 20 | |
| }, | |
| { | |
| "name": "Prague", | |
| "country": "CZ", | |
| "region": "Europe", | |
| "cost": 1191, | |
| "currency": "USD", | |
| "temp": 292.03888888888895, | |
| "humidity": 77, | |
| "internetSpeed": 40 | |
| }, | |
| { | |
| "name": "Phnom Penh", | |
| "country": "KH", | |
| "region": "SE Asia", | |
| "cost": 936, | |
| "currency": "USD", | |
| "temp": 301.48333333333335, | |
| "humidity": 78, | |
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| { | |
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| "region": "Europe", | |
| "cost": 1490, | |
| "currency": "USD", | |
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| }, | |
| { | |
| "name": "Riga", | |
| "country": "LV", | |
| "region": "Europe", | |
| "cost": 1417, | |
| "currency": "USD", | |
| "temp": 286.48333333333335, | |
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| }, | |
| { | |
| "name": "Ho Chi Minh City", | |
| "country": "VN", | |
| "region": "SE Asia", | |
| "cost": 1329, | |
| "currency": "USD", | |
| "temp": 296.48333333333335, | |
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| { | |
| "name": "Penang", | |
| "country": "MY", | |
| "region": "SE Asia", | |
| "cost": 1065, | |
| "currency": "USD", | |
| "temp": 301.48333333333335, | |
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| { | |
| "name": "Budapest", | |
| "country": "HU", | |
| "region": "Europe", | |
| "cost": 2166, | |
| "currency": "USD", | |
| "temp": 298.15000000000003, | |
| "humidity": 53, | |
| "internetSpeed": 30 | |
| }, | |
| { | |
| "name": "Kuala Lumpur", | |
| "country": "MY", | |
| "region": "SE Asia", | |
| "cost": 1206, | |
| "currency": "USD", | |
| "temp": 299.2611111111112, | |
| "humidity": 83, | |
| "internetSpeed": 10 | |
| }, | |
| { | |
| "name": "Brasov", | |
| "country": "RO", | |
| "region": "Europe", | |
| "cost": 1824, | |
| "currency": "USD", | |
| "temp": 294.2611111111112, | |
| "humidity": 57, | |
| "internetSpeed": 80 | |
| }, | |
| { | |
| "name": "Bratislava", | |
| "country": "SK", | |
| "region": "Europe", | |
| "cost": 1551, | |
| "currency": "USD", | |
| "temp": 294.2611111111112, | |
| "humidity": 82, | |
| "internetSpeed": 20 | |
| }, | |
| { | |
| "name": "Kosice", | |
| "country": "SK", | |
| "region": "Europe", | |
| "cost": 1466, | |
| "currency": "USD", | |
| "temp": 292.03888888888895, | |
| "humidity": 72, | |
| "internetSpeed": 30 | |
| }, | |
| { | |
| "name": "Belgrade", | |
| "country": "RS", | |
| "region": "Europe", | |
| "cost": 1358, | |
| "currency": "USD", | |
| "temp": 293.15000000000003, | |
| "humidity": 93, | |
| "internetSpeed": 10 | |
| }, | |
| { | |
| "name": "Wroclaw", | |
| "country": "PL", | |
| "region": "Europe", | |
| "cost": 1764, | |
| "currency": "USD", | |
| "temp": 294.2611111111112, | |
| "humidity": 68, | |
| "internetSpeed": 20 | |
| }, | |
| { | |
| "name": "Davao", | |
| "country": "PH", | |
| "region": "SE Asia", | |
| "cost": 1054, | |
| "currency": "USD", | |
| "temp": 294.8166666666667, | |
| "humidity": 100, | |
| "internetSpeed": 5 | |
| }, | |
| { | |
| "name": "Timisoara", | |
| "country": "RO", | |
| "region": "Europe", | |
| "cost": 1999, | |
| "currency": "USD", | |
| "temp": 294.2611111111112, | |
| "humidity": 94, | |
| "internetSpeed": 60 | |
| }, | |
| { | |
| "name": "Ubud", | |
| "country": "ID", | |
| "region": "SE Asia", | |
| "cost": 1185, | |
| "currency": "USD", | |
| "temp": 298.15000000000003, | |
| "humidity": 83, | |
| "internetSpeed": 5 | |
| }, | |
| { | |
| "name": "Ljubljana", | |
| "country": "SI", | |
| "region": "Europe", | |
| "cost": 2162, | |
| "currency": "USD", | |
| "temp": 293.15000000000003, | |
| "humidity": 77, | |
| "internetSpeed": 20 | |
| }, | |
| { | |
| "name": "Warsaw", | |
| "country": "PL", | |
| "region": "Europe", | |
| "cost": 1987, | |
| "currency": "USD", | |
| "temp": 291.48333333333335, | |
| "humidity": 63, | |
| "internetSpeed": 30 | |
| }, | |
| { | |
| "name": "Zagreb", | |
| "country": "HR", | |
| "region": "Europe", | |
| "cost": 1539, | |
| "currency": "USD", | |
| "temp": 295.37222222222226, | |
| "humidity": 82, | |
| "internetSpeed": 10 | |
| }, | |
| { | |
| "name": "Shanghai", | |
| "country": "CN", | |
| "region": "East Asia", | |
| "cost": 1656, | |
| "currency": "USD", | |
| "temp": 298.15000000000003, | |
| "humidity": 83, | |
| "internetSpeed": 20 | |
| }, | |
| { | |
| "name": "San Juan", | |
| "country": "US", | |
| "region": "Central America", | |
| "cost": 2164, | |
| "currency": "USD", | |
| "temp": 297.03888888888895, | |
| "humidity": 94, | |
| "internetSpeed": 10 | |
| }, | |
| { | |
| "name": "Cochabamba", | |
| "country": "BO", | |
| "region": "South America", | |
| "cost": 829, | |
| "currency": "USD", | |
| "temp": 297.03888888888895, | |
| "humidity": 25, | |
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| }, | |
| { | |
| "name": "Taipei", | |
| "country": "TW", | |
| "region": "East Asia", | |
| "cost": 2137, | |
| "currency": "USD", | |
| "temp": 304.8166666666667, | |
| "humidity": 69, | |
| "internetSpeed": 40 | |
| }, | |
| { | |
| "name": "Montreal", | |
| "country": "CA", | |
| "region": "North America", | |
| "cost": 2305, | |
| "currency": "USD", | |
| "temp": 297.5944444444445, | |
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| "internetSpeed": 20 | |
| }, | |
| { | |
| "name": "Las Vegas", | |
| "country": "US", | |
| "region": "North America", | |
| "cost": 2148, | |
| "currency": "USD", | |
| "temp": 307.5944444444445, | |
| "humidity": 20, | |
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| }, | |
| { | |
| "name": "Lima", | |
| "country": "PE", | |
| "region": "South America", | |
| "cost": 1099, | |
| "currency": "USD", | |
| "temp": 292.03888888888895, | |
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| }, | |
| { | |
| "name": "Curitiba", | |
| "country": "BR", | |
| "region": "South America", | |
| "cost": 2145, | |
| "currency": "USD", | |
| "temp": 299.8166666666667, | |
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| { | |
| "name": "Siem Reap", | |
| "country": "KH", | |
| "region": "SE Asia", | |
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| }, | |
| { | |
| "name": "Austin", | |
| "country": "US", | |
| "region": "North America", | |
| "cost": 2541, | |
| "currency": "USD", | |
| "temp": 299.2611111111112, | |
| "humidity": 73, | |
| "internetSpeed": 60 | |
| }, | |
| { | |
| "name": "Beijing", | |
| "country": "CN", | |
| "region": "East Asia", | |
| "cost": 1565, | |
| "currency": "USD", | |
| "temp": 300.9277777777778, | |
| "humidity": 93, | |
| "internetSpeed": 30 | |
| }, | |
| { | |
| "name": "Cairo", | |
| "country": "EG", | |
| "region": "Africa", | |
| "cost": 917, | |
| "currency": "USD", | |
| "temp": 305.37222222222226, | |
| "humidity": 38, | |
| "internetSpeed": 5 | |
| }, | |
| { | |
| "name": "Dallas", | |
| "country": "US", | |
| "region": "North America", | |
| "cost": 2265, | |
| "currency": "USD", | |
| "temp": 306.48333333333335, | |
| "humidity": 55, | |
| "internetSpeed": 20 | |
| }, | |
| { | |
| "name": "Park City", | |
| "country": "US", | |
| "region": "North America", | |
| "cost": 2862, | |
| "currency": "USD", | |
| "temp": 302.03888888888895, | |
| "humidity": 21, | |
| "internetSpeed": 40 | |
| }, | |
| { | |
| "name": "Lisbon", | |
| "country": "PT", | |
| "region": "Europe", | |
| "cost": 2455, | |
| "currency": "USD", | |
| "temp": 300.37222222222226, | |
| "humidity": 64, | |
| "internetSpeed": 30 | |
| }, | |
| { | |
| "name": "Santa Monica", | |
| "country": "US", | |
| "region": "North America", | |
| "cost": 2601, | |
| "currency": "USD", | |
| "temp": 302.03888888888895, | |
| "humidity": 69, | |
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| }, | |
| { | |
| "name": "Singapore", | |
| "country": "SG", | |
| "region": "SE Asia", | |
| "cost": 2678, | |
| "currency": "USD", | |
| "temp": 298.15000000000003, | |
| "humidity": 94, | |
| "internetSpeed": 80 | |
| }, | |
| { | |
| "name": "Medellin", | |
| "country": "CO", | |
| "region": "South America", | |
| "cost": 1296, | |
| "currency": "USD", | |
| "temp": 294.2611111111112, | |
| "humidity": 52, | |
| "internetSpeed": 10 | |
| }, | |
| { | |
| "name": "Toronto", | |
| "country": "CA", | |
| "region": "North America", | |
| "cost": 2825, | |
| "currency": "USD", | |
| "temp": 300.37222222222226, | |
| "humidity": 69, | |
| "internetSpeed": 20 | |
| }, | |
| { | |
| "name": "Tokyo", | |
| "country": "JP", | |
| "region": "East Asia", | |
| "cost": 2392, | |
| "currency": "USD", | |
| "temp": 298.15000000000003, | |
| "humidity": 83, | |
| "internetSpeed": 30 | |
| }, | |
| { | |
| "name": "Porto", | |
| "country": "PT", | |
| "region": "Europe", | |
| "cost": 2686, | |
| "currency": "USD", | |
| "temp": 299.2611111111112, | |
| "humidity": 99, | |
| "internetSpeed": 30 | |
| }, | |
| { | |
| "name": "Tucson", | |
| "country": "US", | |
| "region": "North America", | |
| "cost": 2882, | |
| "currency": "USD", | |
| "temp": 309.8166666666667, | |
| "humidity": 31, | |
| "internetSpeed": 30 | |
| }, | |
| { | |
| "name": "Palawan", | |
| "country": "PH", | |
| "region": "SE Asia", | |
| "cost": 1255, | |
| "currency": "USD", | |
| "temp": 295.9277777777778, | |
| "humidity": 96, | |
| "internetSpeed": 5 | |
| }, | |
| { | |
| "name": "Hong Kong", | |
| "country": "HK", | |
| "region": "East Asia", | |
| "cost": 2634, | |
| "currency": "USD", | |
| "temp": 304.8166666666667, | |
| "humidity": 79, | |
| "internetSpeed": 90 | |
| }, | |
| { | |
| "name": "Playa del Carmen", | |
| "country": "MX", | |
| "region": "North America", | |
| "cost": 1887, | |
| "currency": "USD", | |
| "temp": 303.7055555555556, | |
| "humidity": 70, | |
| "internetSpeed": 10 | |
| }, | |
| { | |
| "name": "Manchester", | |
| "country": "UK", | |
| "region": "Europe", | |
| "cost": 2641, | |
| "currency": "USD", | |
| "temp": 294.2611111111112, | |
| "humidity": 64, | |
| "internetSpeed": 30 | |
| }, | |
| { | |
| "name": "Tel Aviv", | |
| "country": "IL", | |
| "region": "Europe", | |
| "cost": 2519, | |
| "currency": "USD", | |
| "temp": 301.48333333333335, | |
| "humidity": 61, | |
| "internetSpeed": 20 | |
| }, | |
| { | |
| "name": "Bucharest", | |
| "country": "RO", | |
| "region": "Europe", | |
| "cost": 2064, | |
| "currency": "USD", | |
| "temp": 295.37222222222226, | |
| "humidity": 77, | |
| "internetSpeed": 80 | |
| }, | |
| { | |
| "name": "Vancouver", | |
| "country": "CA", | |
| "region": "North America", | |
| "cost": 2843, | |
| "currency": "USD", | |
| "temp": 292.5944444444445, | |
| "humidity": 87, | |
| "internetSpeed": 40 | |
| }, | |
| { | |
| "name": "Bordeaux", | |
| "country": "FR", | |
| "region": "Europe", | |
| "cost": 3077, | |
| "currency": "USD", | |
| "temp": 300.9277777777778, | |
| "humidity": 36, | |
| "internetSpeed": 30 | |
| }, | |
| { | |
| "name": "Buenos Aires", | |
| "country": "AR", | |
| "region": "South America", | |
| "cost": 1724, | |
| "currency": "USD", | |
| "temp": 291.48333333333335, | |
| "humidity": 88, | |
| "internetSpeed": 10 | |
| }, | |
| { | |
| "name": "Detroit", | |
| "country": "US", | |
| "region": "North America", | |
| "cost": 2301, | |
| "currency": "USD", | |
| "temp": 300.37222222222226, | |
| "humidity": 44, | |
| "internetSpeed": 30 | |
| }, | |
| { | |
| "name": "Seoul", | |
| "country": "KR", | |
| "region": "East Asia", | |
| "cost": 2934, | |
| "currency": "USD", | |
| "temp": 293.15000000000003, | |
| "humidity": 82, | |
| "internetSpeed": 60 | |
| }, | |
| { | |
| "name": "Cebu", | |
| "country": "PH", | |
| "region": "SE Asia", | |
| "cost": 1808, | |
| "currency": "USD", | |
| "temp": 299.2611111111112, | |
| "humidity": 88, | |
| "internetSpeed": 5 | |
| }, | |
| { | |
| "name": "Tallinn", | |
| "country": "EE", | |
| "region": "Europe", | |
| "cost": 3161, | |
| "currency": "USD", | |
| "temp": 289.2611111111112, | |
| "humidity": 82, | |
| "internetSpeed": 40 | |
| }, | |
| { | |
| "name": "Boulder", | |
| "country": "US", | |
| "region": "North America", | |
| "cost": 3070, | |
| "currency": "USD", | |
| "temp": 307.5944444444445, | |
| "humidity": 20, | |
| "internetSpeed": 20 | |
| }, | |
| { | |
| "name": "Salzburg", | |
| "country": "AT", | |
| "region": "Europe", | |
| "cost": 2748, | |
| "currency": "USD", | |
| "temp": 290.9277777777778, | |
| "humidity": 82, | |
| "internetSpeed": 20 | |
| }, | |
| { | |
| "name": "Madrid", | |
| "country": "ES", | |
| "region": "Europe", | |
| "cost": 2798, | |
| "currency": "USD", | |
| "temp": 308.15000000000003, | |
| "humidity": 17, | |
| "internetSpeed": 30 | |
| }, | |
| { | |
| "name": "Vienna", | |
| "country": "AT", | |
| "region": "Europe", | |
| "cost": 3096, | |
| "currency": "USD", | |
| "temp": 292.5944444444445, | |
| "humidity": 82, | |
| "internetSpeed": 20 | |
| }, | |
| { | |
| "name": "Manila", | |
| "country": "PH", | |
| "region": "SE Asia", | |
| "cost": 1371, | |
| "currency": "USD", | |
| "temp": 298.15000000000003, | |
| "humidity": 100, | |
| "internetSpeed": 5 | |
| }, | |
| { | |
| "name": "Dubai", | |
| "country": "AE", | |
| "region": "Middle East", | |
| "cost": 3233, | |
| "currency": "USD", | |
| "temp": 309.2611111111112, | |
| "humidity": 37, | |
| "internetSpeed": 30 | |
| }, | |
| { | |
| "name": "Recife", | |
| "country": "BR", | |
| "region": "South America", | |
| "cost": 1994, | |
| "currency": "USD", | |
| "temp": 299.2611111111112, | |
| "humidity": 97, | |
| "internetSpeed": 20 | |
| }, | |
| { | |
| "name": "Saint Petersburg", | |
| "country": "RU", | |
| "region": "Europe", | |
| "cost": 2124, | |
| "currency": "USD", | |
| "temp": 289.2611111111112, | |
| "humidity": 63, | |
| "internetSpeed": 20 | |
| }, | |
| { | |
| "name": "Orlando", | |
| "country": "US", | |
| "region": "North America", | |
| "cost": 2436, | |
| "currency": "USD", | |
| "temp": 306.48333333333335, | |
| "humidity": 55, | |
| "internetSpeed": 20 | |
| }, | |
| { | |
| "name": "Seattle", | |
| "country": "US", | |
| "region": "North America", | |
| "cost": 3254, | |
| "currency": "USD", | |
| "temp": 292.03888888888895, | |
| "humidity": 72, | |
| "internetSpeed": 30 | |
| }, | |
| { | |
| "name": "Salt Lake City", | |
| "country": "US", | |
| "region": "North America", | |
| "cost": 3729, | |
| "currency": "USD", | |
| "temp": 301.48333333333335, | |
| "humidity": 20, | |
| "internetSpeed": 30 | |
| }, | |
| { | |
| "name": "Berlin", | |
| "country": "DE", | |
| "region": "Europe", | |
| "cost": 3508, | |
| "currency": "USD", | |
| "temp": 293.7055555555556, | |
| "humidity": 49, | |
| "internetSpeed": 30 | |
| }, | |
| { | |
| "name": "Wellington", | |
| "country": "NZ", | |
| "region": "Oceania", | |
| "cost": 3539, | |
| "currency": "USD", | |
| "temp": 284.2611111111111, | |
| "humidity": 87, | |
| "internetSpeed": 30 | |
| }, | |
| { | |
| "name": "Cambridge", | |
| "country": "UK", | |
| "region": "Europe", | |
| "cost": 3270, | |
| "currency": "USD", | |
| "temp": 295.37222222222226, | |
| "humidity": 49, | |
| "internetSpeed": 30 | |
| }, | |
| { | |
| "name": "Portland", | |
| "country": "US", | |
| "region": "North America", | |
| "cost": 3266, | |
| "currency": "USD", | |
| "temp": 289.8166666666667, | |
| "humidity": 62, | |
| "internetSpeed": 20 | |
| }, | |
| { | |
| "name": "Granada", | |
| "country": "ES", | |
| "region": "Europe", | |
| "cost": 2855, | |
| "currency": "USD", | |
| "temp": 301.48333333333335, | |
| "humidity": 25, | |
| "internetSpeed": 30 | |
| }, | |
| { | |
| "name": "Barcelona", | |
| "country": "ES", | |
| "region": "Europe", | |
| "cost": 3431, | |
| "currency": "USD", | |
| "temp": 298.15000000000003, | |
| "humidity": 60, | |
| "internetSpeed": 30 | |
| }, | |
| { | |
| "name": "Dublin", | |
| "country": "IE", | |
| "region": "Europe", | |
| "cost": 3214, | |
| "currency": "USD", | |
| "temp": 290.37222222222226, | |
| "humidity": 82, | |
| "internetSpeed": 30 | |
| }, | |
| { | |
| "name": "Auckland", | |
| "country": "NZ", | |
| "region": "Oceania", | |
| "cost": 2869, | |
| "currency": "USD", | |
| "temp": 284.8166666666667, | |
| "humidity": 100, | |
| "internetSpeed": 20 | |
| }, | |
| { | |
| "name": "Stockholm", | |
| "country": "SE", | |
| "region": "Europe", | |
| "cost": 3714, | |
| "currency": "USD", | |
| "temp": 295.37222222222226, | |
| "humidity": 68, | |
| "internetSpeed": 50 | |
| }, | |
| { | |
| "name": "Denver", | |
| "country": "US", | |
| "region": "North America", | |
| "cost": 3229, | |
| "currency": "USD", | |
| "temp": 307.5944444444445, | |
| "humidity": 20, | |
| "internetSpeed": 30 | |
| }, | |
| { | |
| "name": "Basel", | |
| "country": "CH", | |
| "region": "Europe", | |
| "cost": 3795, | |
| "currency": "USD", | |
| "temp": 291.48333333333335, | |
| "humidity": 82, | |
| "internetSpeed": 40 | |
| }, | |
| { | |
| "name": "Amsterdam", | |
| "country": "NL", | |
| "region": "Europe", | |
| "cost": 3772, | |
| "currency": "USD", | |
| "temp": 293.7055555555556, | |
| "humidity": 68, | |
| "internetSpeed": 40 | |
| }, | |
| { | |
| "name": "Johannesburg", | |
| "country": "ZA", | |
| "region": "Africa", | |
| "cost": 2072, | |
| "currency": "USD", | |
| "temp": 293.15000000000003, | |
| "humidity": 12, | |
| "internetSpeed": 10 | |
| }, | |
| { | |
| "name": "Lyon", | |
| "country": "FR", | |
| "region": "Europe", | |
| "cost": 3680, | |
| "currency": "USD", | |
| "temp": 295.37222222222226, | |
| "humidity": 49, | |
| "internetSpeed": 50 | |
| }, | |
| { | |
| "name": "Rome", | |
| "country": "IT", | |
| "region": "Europe", | |
| "cost": 3250, | |
| "currency": "USD", | |
| "temp": 297.03888888888895, | |
| "humidity": 88, | |
| "internetSpeed": 10 | |
| }, | |
| { | |
| "name": "Copenhagen", | |
| "country": "DK", | |
| "region": "Europe", | |
| "cost": 3514, | |
| "currency": "USD", | |
| "temp": 292.03888888888895, | |
| "humidity": 77, | |
| "internetSpeed": 40 | |
| }, | |
| { | |
| "name": "Los Angeles", | |
| "country": "US", | |
| "region": "North America", | |
| "cost": 4178, | |
| "currency": "USD", | |
| "temp": 301.48333333333335, | |
| "humidity": 73, | |
| "internetSpeed": 30 | |
| }, | |
| { | |
| "name": "Cape Town", | |
| "country": "ZA", | |
| "region": "Africa", | |
| "cost": 2564, | |
| "currency": "USD", | |
| "temp": 288.7055555555556, | |
| "humidity": 84, | |
| "internetSpeed": 10 | |
| }, | |
| { | |
| "name": "Rotterdam", | |
| "country": "NL", | |
| "region": "Europe", | |
| "cost": 3736, | |
| "currency": "USD", | |
| "temp": 293.15000000000003, | |
| "humidity": 63, | |
| "internetSpeed": 50 | |
| }, | |
| { | |
| "name": "Oslo", | |
| "country": "NO", | |
| "region": "Europe", | |
| "cost": 4294, | |
| "currency": "USD", | |
| "temp": 293.15000000000003, | |
| "humidity": 59, | |
| "internetSpeed": 30 | |
| }, | |
| { | |
| "name": "Columbus", | |
| "country": "US", | |
| "region": "North America", | |
| "cost": 4208, | |
| "currency": "USD", | |
| "temp": 301.48333333333335, | |
| "humidity": 65, | |
| "internetSpeed": 20 | |
| }, | |
| { | |
| "name": "Dusseldorf", | |
| "country": "DE", | |
| "region": "Europe", | |
| "cost": 3910, | |
| "currency": "USD", | |
| "temp": 295.9277777777778, | |
| "humidity": 68, | |
| "internetSpeed": 30 | |
| }, | |
| { | |
| "name": "Philadelphia", | |
| "country": "US", | |
| "region": "North America", | |
| "cost": 4358, | |
| "currency": "USD", | |
| "temp": 303.15000000000003, | |
| "humidity": 45, | |
| "internetSpeed": 30 | |
| }, | |
| { | |
| "name": "Minneapolis", | |
| "country": "US", | |
| "region": "North America", | |
| "cost": 3724, | |
| "currency": "USD", | |
| "temp": 293.15000000000003, | |
| "humidity": 82, | |
| "internetSpeed": 20 | |
| }, | |
| { | |
| "name": "New York City", | |
| "country": "US", | |
| "region": "North America", | |
| "cost": 4674, | |
| "currency": "USD", | |
| "temp": 302.03888888888895, | |
| "humidity": 35, | |
| "internetSpeed": 40 | |
| }, | |
| { | |
| "name": "Chicago", | |
| "country": "US", | |
| "region": "North America", | |
| "cost": 3911, | |
| "currency": "USD", | |
| "temp": 300.9277777777778, | |
| "humidity": 50, | |
| "internetSpeed": 30 | |
| }, | |
| { | |
| "name": "Paris", | |
| "country": "FR", | |
| "region": "Europe", | |
| "cost": 4656, | |
| "currency": "USD", | |
| "temp": 296.48333333333335, | |
| "humidity": 49, | |
| "internetSpeed": 70 | |
| }, | |
| { | |
| "name": "Miami", | |
| "country": "US", | |
| "region": "North America", | |
| "cost": 4119, | |
| "currency": "USD", | |
| "temp": 304.2611111111112, | |
| "humidity": 74, | |
| "internetSpeed": 30 | |
| }, | |
| { | |
| "name": "San Francisco", | |
| "country": "US", | |
| "region": "North America", | |
| "cost": 4854, | |
| "currency": "USD", | |
| "temp": 295.37222222222226, | |
| "humidity": 82, | |
| "internetSpeed": 30 | |
| }, | |
| { | |
| "name": "London", | |
| "country": "UK", | |
| "region": "Europe", | |
| "cost": 4504, | |
| "currency": "USD", | |
| "temp": 295.37222222222226, | |
| "humidity": 60, | |
| "internetSpeed": 30 | |
| } | |
| ] | |
| </Attribute_String></Cities> | |
| <Reducer/> | |
| <GroupByPropReducer/> | |
| <CalcScorer/> | |
| </PhysicalSystem> | |
| <Blockbehavior implName="org.primordion.xholon.base.Behavior_gwtjs"><![CDATA[ | |
| // video 2 | |
| // note that nothing is mutated, vs using a for loop where the array and the array index both get mutated | |
| const numbers = [1, 2, 3]; | |
| function double(number) { | |
| return number * 2; | |
| } | |
| const doubledNumbers = numbers.map(double); | |
| this.println(doubledNumbers); | |
| //# sourceURL=Blockbehavior.js | |
| ]]></Blockbehavior> | |
| <Citiesbehavior implName="org.primordion.xholon.base.Behavior_gwtjs"><![CDATA[ | |
| // video 2 and 3 | |
| const VERSION = 2; | |
| var me, updatedCities, index, R, beh = { | |
| postConfigure: function() { | |
| me = this.cnode.parent(); | |
| index = 0; | |
| R = $wnd.R; // ramda | |
| switch (VERSION) { | |
| case 1: this.version1(); break; | |
| case 2: this.version2(); break; | |
| default: break; | |
| } | |
| }, | |
| version1: function() { | |
| me.println("version 1 ..."); | |
| const cities = $wnd.JSON.parse(me.first().remove().text()); | |
| const KtoC = k => k - 273.15; | |
| const updateTemperature = city => { | |
| const temp = Math.round(KtoC(city.temp)); | |
| //return temp; | |
| return R.merge(city, { temp }); | |
| } | |
| //const updatedCitiesConst = cities.map(updateTemperature); | |
| //updatedCities = updatedCitiesConst; //cities.map(updateTemperature); // updatedCities should be immutable (const) | |
| updatedCities = cities.map(updateTemperature); | |
| Object.freeze(updatedCities); | |
| me.println(updatedCities.length); | |
| }, | |
| version2: function() { | |
| me.println("version 2 ..."); | |
| const cities = $wnd.JSON.parse(me.first().remove().text()); | |
| const KtoC = k => k - 273.15; | |
| const KtoF = k => k * 9 / 5 - 459.67; | |
| const updateTemperature = R.curry((convertFn, city) => { | |
| const temp = Math.round(convertFn(city.temp)); | |
| return R.merge(city, { temp }); | |
| }); | |
| updatedCities = R.map(updateTemperature(KtoF), cities); | |
| Object.freeze(updatedCities); | |
| me.println(updatedCities.length); | |
| }, | |
| processReceivedSyncMessage: function(msg) { | |
| return updatedCities; | |
| }, | |
| act: function() { | |
| me.println($wnd.JSON.stringify(updatedCities[index++])); | |
| } | |
| } | |
| //# sourceURL=Citiesbehavior.js | |
| ]]></Citiesbehavior> | |
| <Reducerbehavior implName="org.primordion.xholon.base.Behavior_gwtjs"><![CDATA[ | |
| // video 4 | |
| var me, cities, R, beh = { | |
| postConfigure: function() { | |
| me = this.cnode.parent(); | |
| R = $wnd.R; // ramda | |
| cities = me.prev().call(101, null, me).data; | |
| me.println(cities.length); | |
| this.reduce1(); | |
| this.reduce2(); | |
| }, | |
| reduce1: function() { | |
| const numbers = [1, 2, 3]; | |
| function sum(x, y) {return x + y;} | |
| const total = numbers.reduce(sum, 0); | |
| me.println(total); | |
| }, | |
| reduce2: function() { | |
| const totalCostReducer = (acc, city) => { | |
| const { cost = 0 } = city; | |
| return acc + cost; | |
| } | |
| const totalCost = R.reduce(totalCostReducer, 0, cities); | |
| const cityCount = R.length(cities); | |
| // the following print the values obtained in refs [1, 2] | |
| me.println(totalCost); // 250891 | |
| me.println(cityCount); // 100 | |
| me.println(totalCost / cityCount); // 2508.91 | |
| } | |
| } | |
| //# sourceURL=Reducerbehavior.js | |
| ]]></Reducerbehavior> | |
| <GroupByPropReducerbehavior implName="org.primordion.xholon.base.Behavior_gwtjs"><![CDATA[ | |
| // video 5 | |
| var me, cities, groupedByPropVar, R, beh = { | |
| postConfigure: function() { | |
| me = this.cnode.parent(); | |
| R = $wnd.R; // ramda | |
| cities = me.prev().prev().call(101, null, me).data; | |
| me.println(cities.length); | |
| this.reduce1(); | |
| //this.reduce2(); | |
| }, | |
| reduce1: function() { | |
| const groupByPropReducer = (acc, city) => { | |
| const { cost = [], internetSpeed = [] } = acc; | |
| return R.merge(acc, { | |
| cost: R.append(city.cost, cost), | |
| internetSpeed: R.append(city.internetSpeed, internetSpeed), | |
| }); | |
| } | |
| const groupedByProp = R.reduce(groupByPropReducer, {}, cities); | |
| groupedByPropVar = groupedByProp; | |
| console.log(groupedByProp); | |
| }, | |
| processReceivedSyncMessage: function(msg) { | |
| return groupedByPropVar; | |
| } | |
| } | |
| //# sourceURL=GroupByPropReducerbehavior.js | |
| ]]></GroupByPropReducerbehavior> | |
| <CalcScorerbehavior implName="org.primordion.xholon.base.Behavior_gwtjs"><![CDATA[ | |
| // video 6 and 7 | |
| var me, cities, groupedByProp, scoredCities, R, beh = { | |
| postConfigure: function() { | |
| me = this.cnode.parent(); | |
| R = $wnd.R; // ramda | |
| cities = me.prev().prev().prev().call(101, null, me).data; | |
| groupedByProp = me.prev().call(101, null, me).data; | |
| me.println(cities.length); | |
| this.calcScores(); | |
| this.filterAndSort(); | |
| }, | |
| calcScores: function() { | |
| const percentile = (array, value) => { | |
| const length = R.length(array); | |
| const eqVal = R.equals(value); | |
| const alen = !R.any(eqVal, array) | |
| ? R.range(0, length + 1) | |
| : R.range(0, length); | |
| const sortedArray = R.sort((a, b) => a - b, array); | |
| const idx = R.map(eqVal, sortedArray); | |
| const alenTrue = R.filter((v, i) => { | |
| return idx[alen.indexOf(v)] === true; | |
| }, alen); | |
| const mean = R.mean(alenTrue); | |
| const percent = mean / length; | |
| return percent; | |
| }; | |
| const calcScore = city => { | |
| const { cost = 0, internetSpeed = 0 } = city; | |
| const costPercentile = percentile(groupedByProp.cost, cost); | |
| const internetSpeedPercentile = percentile( | |
| groupedByProp.internetSpeed, | |
| internetSpeed, | |
| ); | |
| const score = | |
| 100 * (1.0 - costPercentile) + | |
| 20 * internetSpeedPercentile; | |
| return R.merge(city, { score }); | |
| } | |
| const scoredCitiesConst = R.map(calcScore, cities); | |
| scoredCities = scoredCitiesConst; | |
| console.log(scoredCities); | |
| }, | |
| filterAndSort: function() { | |
| const filterByWeather = city => { | |
| const { temp = 0, humidity = 0 } = city; | |
| return temp > 68 && temp < 85 && humidity > 30 && humidity < 70; | |
| } | |
| const filteredCities = R.filter(filterByWeather, scoredCities); | |
| me.println(filteredCities.length); // 26 | |
| me.println(R.length(filteredCities)); // 26 | |
| const sortedCities = R.sortWith( | |
| [R.descend(city => city.score)], | |
| filteredCities, | |
| ); | |
| console.log(sortedCities); | |
| const top10 = R.take(10, sortedCities); | |
| console.log(top10); | |
| me.println(R.length(top10)); | |
| } | |
| } | |
| //# sourceURL=CalcScorerbehavior.js | |
| ]]></CalcScorerbehavior> | |
| <!-- TODO | |
| const cityToArray = city => { | |
| const { name, country, score, cost, temp, internetSpeed } = city; | |
| return [name, country, score, cost, temp, internetSpeed]; | |
| }; | |
| const interestingProps = [ | |
| 'Name', | |
| 'Country', | |
| 'Score', | |
| 'Cost', | |
| 'Temp', | |
| 'Internet', | |
| ]; | |
| const topCities = R.pipe( | |
| R.map(updateTemperature(KtoF)), | |
| R.filter(filterByWeather), | |
| R.map(calcScore), | |
| R.sortWith([R.descend(city => city.score)]), | |
| R.take(10), | |
| R.map(cityToArray), | |
| R.prepend(interestingProps), | |
| table, | |
| )(cities); | |
| console.log(topCities); | |
| --> | |
| <SvgClient><Attribute_String roleName="svgUri"><![CDATA[data:image/svg+xml, | |
| <svg width="100" height="50" xmlns="http://www.w3.org/2000/svg"> | |
| <g> | |
| <title>Block</title> | |
| <rect id="PhysicalSystem/Block" fill="#98FB98" height="50" width="50" x="25" y="0"/> | |
| <g> | |
| <title>Cities</title> | |
| <rect id="PhysicalSystem/Cities" fill="#6AB06A" height="50" width="10" x="80" y="0"/> | |
| </g> | |
| </g> | |
| </svg> | |
| ]]></Attribute_String><Attribute_String roleName="setup">${MODELNAME_DEFAULT},${SVGURI_DEFAULT}</Attribute_String></SvgClient> | |
| </XholonWorkbook> |
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