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https://github.com/HabitRPG/habitica.git
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Upgrade lodash to v4 and lint more files (#8495)
* common: import lodash modules separately * remove test/content from .eslintignore, fix with eslint --fix content/index * lint test/content * lint content/index except for lodash methods * upgrade server/models * upgrade server/middlewares and server/libs * port server/controllers/top-level * port server/controllers/api-v3 * port views and tests * client old port lodash and _(, missing _. * upgrade client-old * port common/script (root level files only) * port common/script/fns * port common/libs * port common/script/ops * port common/script/content and common/script/libs/shops.js * misc fixes * misc fixes * misc fixes * more tests fixes * fix payments test stubbing, down to 2 failing tests * remove more instances of lodash wrapping * fix bug where toObject does not clone object * fix tests * upgrade migration or add lodash 4 note * update shrinkwrap * fix linting * upgrade eslint-config-habitrpg * update shrinkwrap * recompile shrinkwrap
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@@ -1,4 +1,10 @@
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import _ from 'lodash';
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import min from 'lodash/min';
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import pick from 'lodash/pick';
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import values from 'lodash/values';
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import invert from 'lodash/invert';
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import findIndex from 'lodash/findIndex';
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import max from 'lodash/max';
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import splitWhitespace from '../libs/splitWhitespace';
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/*
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@@ -14,8 +20,8 @@ function getStatToAllocate (user) {
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switch (user.preferences.allocationMode) {
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case 'flat': {
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let stats = _.pick(statsObj, splitWhitespace('con str per int'));
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return _.invert(stats)[_.min(stats)];
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let stats = pick(statsObj, splitWhitespace('con str per int'));
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return invert(stats)[min(values(stats))];
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}
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case 'classbased': {
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let preference;
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@@ -47,14 +53,14 @@ function getStatToAllocate (user) {
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statsObj[preference[3]] - ideal[3],
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];
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suggested = _.findIndex(diff, (val) => {
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if (val === _.min(diff)) return true;
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suggested = findIndex(diff, (val) => {
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if (val === min(diff)) return true;
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});
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return suggested !== -1 ? preference[suggested] : 'str';
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}
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case 'taskbased': {
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suggested = _.invert(statsObj.training)[_.max(statsObj.training)];
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suggested = invert(statsObj.training)[max(values(statsObj.training))];
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user.stats.training.str = 0;
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user.stats.training.int = 0;
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