cdbkr

(ns demo.core-test
  (:require [cljs.test :refer [deftest
                               testing
                               is
                               use-fixtures]]
            [clojure.string :refer [lower-case]]
            [demo.components :refer [title-component
                                     counter-component]]
            [reagent.core :as r]
            ["react-testing-library" :as rtl]))

mhuebert

material-ui allows for customizing CSS via a higher-order component called withStyles. Like many higher-order components which expect render props, the purpose of withStyles is to accept some parameters, and then introduce a new variable into the scope of the component tree.

One succinct and simple way to translate the concept of scope into Clojure is via a custom let macro. Usage of such a macro is demonstrated here:

(:require [material-ui.styles :as m])

(m/let [{:keys [leftPad]} {:leftPad 
                           {:paddingLeft 8}}]
 ;; `leftPad` is now the _className_ associated with {:paddingLeft 8} 

swlkr

(ns switch
  (:require [clojure.pprint :as pprint]))

(defn project-clj-map [filename]
  (->> (slurp filename)
       (read-string)
       (drop 1)
       (partition 2)
       (map vec)
       (into {})))

levand

Since it has come up a few times, I thought I’d write up some of the basic ideas around domain modeling in Clojure, and how they relate to keyword names and Specs. Firmly grasping these concepts will help us all write code that is simpler, cleaner, and easier to understand.

Clojure is a data-oriented language: we’re all familiar with maps, vectors, sets, keywords, etc. However, while data is good, not all data is equally good. It’s still possible to write “bad” data in Clojure.

“Good” data is well defined and easy to read; there is never any ambiguity about what a given data structure represents. Messy data has inconsistent structure, and overloaded keys that can mean different things in different contexts. Good data represents domain entities and a logical model; bad data represents whatever was convenient for the programmer at a given moment. Good data stands on its own, and can be reasoned about without any other knowledge of the codebase; bad data is deeply and tightly coupled to specific generating and

oantolin

(use-package smartparens
  :diminish smartparens-mode
  :init
  (smartparens-global-mode)
  :config
  (require 'smartparens-config)
  (add-hook 'eval-expression-minibuffer-setup-hook #'smartparens-mode)
  (custom-set-variables
   '(sp-base-key-bindings 'sp)
   '(sp-override-key-bindings

reborg

Rich Already Answered That!

A list of commonly asked questions, design decisions, reasons why Clojure is the way it is as they were answered directly by Rich (even when from many years ago, those answers are pretty much valid today!). Feel free to point friends and colleagues here next time they ask (again). Answers are pasted verbatim (I've made small adjustments for readibility, but never changed a sentence) from mailing lists, articles, chats.

How to use:

• The link in the table of content jumps at the copy of the answer on this page.
• The link on the answer itself points back at the original post.

Table of Content