Marcio Lopes de Faria marciol

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

Scaling your API with rate limiters

The following are examples of the four types rate limiters discussed in the accompanying blog post. In the examples below I've used pseudocode-like Ruby, so if you're unfamiliar with Ruby you should be able to easily translate this approach to other languages. Complete examples in Ruby are also provided later in this gist.

In most cases you'll want all these examples to be classes, but I've used simple functions here to keep the code samples brief.

Request rate limiter

This uses a basic token bucket algorithm and relies on the fact that Redis scripts execute atomically. No other operations can run between fetching the count and writing the new count.

	#!/bin/sh

	STAGED_FILES=$(git diff-index HEAD --name-only --cached)
	if [[ -z $STAGED_FILES ]]
	then
	exit # no staged files, no need to run rubocop
	fi

	# Checks if any staged files have unstaged changes
	# otherwise rubocop isn't running on what is actually

	#!/usr/bin/env bash
	#_" -- mode: clojure; --"
	#_(
	"exec" "clojure" "-Sdeps" "{:deps {clj-kondo/clj-kondo {:mvn/version \"2020.12.12\"} org.clojure/tools.deps.alpha {:mvn/version \"0.9.857\"} org.slf4j/slf4j-nop {:mvn/version \"1.7.30\"} lambdaisland/deep-diff2 {:mvn/version \"2.0.108\"} juji/editscript {:mvn/version \"0.5.4\"}}}" "-M" "$0" "$@"
	)

	;; Example usage:
	;; api_diff.clj org.clojure/clojure "1.8.0" "1.10.1" > /tmp/diff.txt

	(require '[clj-kondo.core :as clj-kondo])

	(ns example.core
	(:require [vcr-clj.core :as vcr]
	[vcr-clj.clj-http :as vcr-http]
	[clj-http.client :as client]))

	(defn random [n]
	{:number (+ 10 (rand-int n))
	:username "admin"
	:password "Lol, Ima Password!"})

	;; see https://github.com/borkdude/grasp for a more elaborate implementation

	(ns script
	(:require [clojure.java.io :as io]
	[clojure.pprint :refer [pprint]]
	[edamame.core :as e]))

	(def clojure-core (slurp (io/resource "clojure/core.clj")))
	(def parsed (e/parse-string-all clojure-core
	{:all true :auto-resolve '{:current clojure.core}}))

	#Clojerl
	./bin/clje \
	-e "(do (require 'clojure.core.server) \
	(clojure.core.server/start-server \
	{:name \"socket-repl\" \
	:port 4444 \
	:accept 'clojure.main/repl \
	:address \"localhost\"}))" -r

	#CLR

	```
	#!/bin/sh
	echo "\nRunning rubocop 🚓 💨 💨 💨\n"

	declare -a ERRORS=()

	for file in $(git diff --cached --name-only \| grep -E '.rb')
	do
	ERRORS+=("$(rubocop $file \| grep -e 'C:' -e 'E:')")
	done

	WITH
	-- write the new values
	n(ip,visits,clicks) AS (
	VALUES ('192.168.1.1',2,12),
	('192.168.1.2',6,18),
	('192.168.1.3',3,4)
	),
	-- update existing rows
	upsert AS (
	UPDATE page_views o

	--- Actions ---
	$Copy <M-C>
	$Cut <M-X> <S-Del>
	$Delete <Del> <BS> <M-BS>
	$LRU
	$Paste <M-V>
	$Redo <M-S-Z> <A-S-BS>
	$SearchWeb <A-S-G>
	$SelectAll <M-A>
	$Undo <M-Z>