Концепти тврдог кодирања објашњени једноставним стварним аналогијама

Како 5-годишњаку објаснити концепте кодирања попут токова, обећања, повезивања и декларативног програмирања

Волим да размишљам о концептима кодирања упоређујући их са познатим стварима које знамо у животу. Постоји толико много аналогија о концептима кодирања. Неки од њих су добри, док су други збуњујући, углавном зато што се фокусирају на делимичне аспекте концепта, а занемарују многе. Овај чланак ће резимирати неке од аналогија за које сматрам да најбоље одговарају неколико концепата кодирања на потпун начин.

Ажурирање: Овај чланак је сада део моје књиге „Професионални програмер“. Прочитајте ажурирану верзију овог садржаја и више савета за програмирање на јсцомплете.цом/про-программер .

Почећу са једноставним концептима и прећи на оне теже. Почнимо са самим кодирањем. Кодирање се може упоредити са писањем рецепата за кување. Рецепт у овој аналогији је програм, а кувар је рачунар. Рецепт је списак упутстава које кувар треба да следи, а програм је списак упутстава за извршавање рачунара.

Ово је врло једноставна аналогија с обзиром на то да је рецепт написан на људском језику, а програм на рачунарском језику, а то су врло различити језици (осим ако ваши рецепти не садрже ограничења и обећања!). Такође у рецепту нема пуно неочекиваних ствари које треба планирати, док ће рачунарски програм имати много тога. Без обзира на његову једноставност, то је добар начин да покажете како рачунар секвенцијално извршава листу упутстава. Такође показује где једна линија инструкција може да користи било који резултат извршавања претходних линија инструкција.

Неки рецепти ће чак имати и изјаве иф: ако кувате 2, 4 или 8! Неки рецепти ће имати петље: туците ту комбинацију све док ...

Ова аналогија ми се такође допада због свих готових предмета и алата које можете користити у својим рецептима - попут мешавине колача од које можете правити колаче и оне посуде посебно обликованог облика која толико олакшава стварање колача.

Употреба готових предмета и алата је попут укључивања и коришћења пакета кода који су други написали у ваш властити код.

// The making of a cupcake// First steps:
$ npm install cake-mix$ npm install cupcake-pan

НПМ је менаџер пакета за Ноде.јс , који је веома популаран оквир за писање ЈаваСцрипт апликација. У овој аналогији, Ноде.јс је попут саме кухиње. Омогућава вам извршавање линија у вашим рецептима помоћу уграђених модула попут пећнице и судопере.

Говорећи о нездравој храни, следећа аналогија је за учење како се кодира и упоређује се са прехрамбеним навикама. Посебно ОБОЖАВАМ ову аналогију и оно што она преноси јер ми помаже да останем на правом путу на свом путу учења кода. За мене је ово почело у средњој школи и трајаће све док мој мозак не дође до последњег упутства: дие ();

Учење кодирања

Учење кодирања је као покушај мршављења. Ова аналогија се односи на стварно учење било чега, али учење кодирања овде се посебно подудара.

„Губитак килограма“ је негативан појам. Заиста бисмо то требали назвати „Стицање здравља“. У том смислу, веома је упоредиво са „Стицањем знања“. Образовни ресурси који су вам на располагању су попут опција за храну. Неки су сасвим у реду, неки су сјајни, а неки су потпуно лоши за вас. Здрава исхрана и вежбање главне су две активности које ће вам помоћи да стекнете здравље. Слично томе, потрошња добрих образовних ресурса и ручно вежбање кодирања главне су две активности које ће вам помоћи да стекнете добро знање о кодирању.

Па како научити „здраво“? Када се обавежете да ћете се хранити здраво, користите филтере попут органских , локалних , са смањеном масноћом , храњењем травом и не-гмо. Потпуно је исто са здравим образовним ресурсима, осим што ове ознаке још нису толико јасне. Надам се да ће образовни ресурси једног дана такође имати провериве и релевантне ознаке. Можда етикете попут „неспонзорисано“, „не-маркетиншко“, „одобрено од стране стручњака“, „добро уређено“ и „змајеви-напред“.

Ипак, уместо да филтрирате према садржају, лако можете да филтрирате према добрим брендовима. То радим и са храном. Знам неколико марки и верујем им, и углавном их користим. Ово је лакше. Уз образовне ресурсе постоје неки брендови (публикације и људи) које бисте требали стално пратити.

Након филтрирања уноса знања само на добре ресурсе, само треба да вежбате! Вежбајте све што научите, али не само тако што ћете поново радити тачно оно што сте научили. Такође се изазовите да учините нешто мало другачије око тема које сте научили. Ако имате среће, заглавићете се! Тада ћете трајно научити нешто друго кад се одлепите.

Вежба је намењена и телу и уму.

Променљиве

Варијабле се користе у рачунарским програмима за чување података . Ово је врло поједностављена изјава и по многим мерилима је једноставно погрешна.

Променљиве не садрже податке. Они само указују на то. Подаци се чувају у меморији рачунара. Можете упоређивати променљиве са ознакама које постављате на е-поруке (или белешке или датотеке).

Сви узорци кода у овом чланку написани су на ЈаваСцрипт-у. ЈаваСцрипт је веома лак за учење рачунарског језика.

У Гмаил-у ознака је показивач на е-пошту или листу е-адреса. Много налепница може да упућује на исту е-пошту. Ово је слично додељивању друге променљиве постојећој променљивој:

let work = [email1, email2, email3];let important = work;

И рад и важно су сада ознаке које упућују на потпуно исту листу е-адреса.

Неке променљиве представљају константне референце . Не могу се променити. Ово је попут ознаке „ послато “ у Гмаил-у. Иако можемо променити горњу радну ознаку и усмерити је ка другој листи е-адреса, послату ознаку не можемо променити. Послату етикету не можете усмерити на другу листу е-адреса. Можете само указати на више е-адреса.

const sent = [];
// You cannot change the meaning of sent now// But you can add more values to it:
sent.push(new Email());

Грешке и изузеци

Стручност програмера углавном се односи на то како се бавити грешкама. Стручни програмери воле грешке јер за њих грешке значе напредак.

Понекад очекујемо да видимо ове дивне црвене поруке, а ако не знамо, код је једноставно погрешан!

Волим фразу „ слушај свој код“, јер мислим да се код развија тако што нам комуницира користећи грешке.

Ово је потпуно попут васпитања деце.

The most important parenting concept that I realized, with practice, is how kids communicate by misbehaving. This is because they do not have a logical brain yet. I think programs do the exact same thing. They also communicate by misbehaving (producing errors) because programs are not completely logical. Your task as a programmer is to add more logic in the code to handle the cases that originally produced errors. This is just like how a parent’s task is to teach the misbehaving kid what is wrong with that bad behavior and what to do differently next time.

Some errors are not recoverable and a program encountering those should just exit (and be rebooted). This is like if your heart stops. There is not much that can be done except to reboot it with an electric shock. This is why we monitor our programs and reboot them when they get to that state. Luckily, the process of rebooting a program is not as dramatic.

Most errors that happen during the early development of programs help improve these programs so that the errors never happen. This is how good kids are raised. They do not repeat the misbehaving because now they have good logic to guide them in a good direction.

Some errors evolve to be exceptions. Exceptions are expected errors. Errors that we can plan for and recover from. The best coding example here is a Network Connection error while we make a program, for example, download some data. This is very much expected because we know network connections could be unreliable so we plan for that error. When that error happens, let’s label the task of downloading that data as incomplete. Queue it somewhere, and re-try it at a later time (see below for an analogy for queuing).

What we did with this planned exception is give the computer a different set of instructions (a different recipe) to do when that error happens. We do exactly that with our kids as well. We give them instructions about what to do in certain future scenarios that we expect (or fear in this case).

// Hey kidsif (stranger.offersYou(chocolate)) { doNotAccept(); doNotTalkTo(stranger); walkAway();}
if (stranger.triesToForceYouToDoSomething()) { screamFor(help); runAway(); call(911);}

Reactive Programming and Streams

Reactive programming is a popular method for writing code that is based on reacting to changes. It is inspired by our everyday life and how we take actions and communicate with others. When performing everyday life activities, we try to multitask when we can but the brain cannot multitask no matter how hard we try. The only way we humans can multitask is to switch tasks and split them efficiently during their lifetime. This makes more sense when the tasks that we need to do require some amount of waiting, which is almost always the case. We actually always switch-tasks, even when we are not aware of it.

Reactive programming is simply to program using, and relying on, events instead of the order of lines in the code. Usually, this involves more than one event, and those events happen in a sequence over time. We call this sequence of events a “stream”.

Think of events as anything that might happen in the future. For example, you know that Jane (a store owner) is always tweeting interesting things on Twitter. Every time she tweets something we call that an “event”. If you look at Jane’s Twitter feed, you have a sequence of “events” happening over time (a stream of events). Reactive programming is named so because we get to “react” to those events. For example, imagine that you are waiting for Jane to tweet a promotional code about something cool she sells in her store. You want to “react” to that tweet and buy the cool thing using the promotional code. In a simplified picture, that is exactly what Reactive programming is all about.

To be able to react to an event, we have to be monitoring it. If we do not track the event, we will never know when to react to it. On Twitter, to monitor the events of Jane tweeting, we follow Jane and set our phone to notify us every time she tweets. When she does, we look at the tweet and make a decision on whether we need to further react to it or not.

In reactive programming, the process of monitoring an event is known as listening or subscribing to the event. This is, in fact, very similar to subscribing to a newsletter. When you subscribe to a newsletter on the Web, you supply your email address. Every time there is a new issue of the newsletter your email address will be used as the way for you to get a copy of the issue. Similarly, we subscribe to an event stream with a function. Every time there is a new event, the stream will use the function to enable our code to react to the event. In this analogy, the newsletter platform is the event stream. Every issue of the newsletter is an event and your email is the function you use to subscribe to the event stream.

Now imagine a dynamic newsletter that allows you to select topics and send you only the news items that match your topics. You are basically filtering the newsletter issues to your liking and that is something we can do on event streams as well. Also, imagine that you have subscribed to several newsletters using different email addresses. You later decided that you want all issues of the newsletters to be sent to a new single email address. One easy thing you can do is to set an email rule that forwards any issues from any newsletter to the new email address. You are basically merging multiple newsletter issues into one email address, which is another thing we can do with event streams.

Another way to think about event streams is to compare them to regular arrays. They are actually very similar. Arrays are a sequence of values in space while event streams are a sequence of values over time. In reactive programming, all the functional operations that we can do on an array. Filtering, reducing, mapping, combining, piping can all be done on event streams. We can filter an event stream, reduce the values of an event stream, map an event stream to another, combine streams, and make one stream an input to another. These are all options that yield new streams of values over time.

Callbacks and Promises

Imagine you ask someone to give you something that needs some time to be prepared. They take your order and your name and tell you to wait to be called when your order is ready. After a while, they call your name and give you what you asked for.

The name you originally gave them is the callback function here. They called it with the object that was requested.

This is like when you order a latte from Starbucks (in the store, not in the drive-thru). They synchronously record your order and name and then you wait until your name is called. When that happens, you receive your latte:

starbucks.makeMeALatte({ type: 'Vanilla', size: 'Grande' }, Samer);
// "Samer" here is the callback function.// When the Latte is ready, the barista will call Samer // with the ready object// We define a function Samer to process the ready object
function Samer(readyLatte) { // drink readyLatte}

Now imagine you ask someone to give you something, but they give you something else. Let’s call it a mystery object. They promise you that this mystery object might eventually turn into the thing you originally asked for.

This promise mystery object can turn into one of two possible forms. One form is associated with success and the other with failure.

This is like when we ask a chicken for a chick and the chicken gives us an egg. That egg might successfully turn into a chick or it might die and be useless.

const egg = chicken.makeChick(); // It's a promise!
egg.then(chick => raiseChick()) // Success outcome .catch(badEgg => throwBadEgg()) // Fail outcome

Queues and Stacks

When we work with elements of data, there are two popular data structures to store and use these elements: A LIFO Stack and a FIFO queue.

LIFO stands for Last In First Out and FIFO stands for First In First Out.

The simplest analogy of a data stack is the stack of dirty dishes in your sink. When you are done using a dish, you stack it on top of the existing dirty dishes until you are ready to wash them.

When you are ready to wash them, you take the last dirty dish that you stacked and you wash that. In computer terminologies, we say you “popped” a dish.

The last dish you stacked is the first dish you washed. This is LIFO.

The simplest analogy of a data queue is the line of people that forms in front of a checkout or order station. When you are ready to pay for your groceries and take them home, you might need to queue yourself in a line until it is your turn.

The first person to arrive at that queue will be the first person to be done with it. This is FIFO.

Pair Programming

You can drive your car on your own when you go to familiar places, but when it is time to go somewhere far for the first time you use a GPS. If you have someone else in the car with you, a better option would be to have them navigate by giving you the instructions on where to turn next. If you do not follow the instructions and end up taking a bad turn, they will let you know immediately and advise you on how to correct it.

Having a navigator next to you when you drive is like having a pair-programmer. You are not driving alone. You are a team with the same goal: to arrive at your destination safely, without any problems, and with the least amount of time and effort.

You can probably do it yourself without a human navigator or a fancy GPS by using the old-school way and checking a map before you leave. If needed, you can check the map again. If you check the map while driving, you might accidentally hit a curb or put a dent in the car. If you stop to check the map, you will be losing time. Without that pair navigator, you are not as safe and/or the journey will take a lot longer.

The experience of your pair navigator might also teach you new things. They might know of a new shortcut that you do not and one that is not on the map. You learn from their relevant experience, and this is beyond valuable.

If you need to go to two destinations and you have two cars. You might be tempted to think that it would be faster to drive solo and do the destinations in parallel. This might be faster in the short term, but all things considered, time might not be the most important factor here. When it comes to computer programs, using one car and making sure it is dent-free at the end of both journeys might be a far more important factor. This why we love pair programming.

Linting and Task Automation

If you have to drive alone on that long trip, you can still make your journey safer by relying on tools. A map is a tool. The GPS is a better tool. Cruise control is another tool.

Tools that automatically warn you if you do something wrong while driving are similar to linting tools for coding. In JavaScript, the best linting tool today is ESLint. It will warn you about so many wrong things you should not be doing while coding. Best of all, it can do that even before you run your program.

Examples of tools that warn you while you are driving are evolving in modern cars. Cars can now warn you when you cross a lane line unexpectedly, or when you try to turn or change a lane while not seeing that hidden car in your blind spot. Additionally, they warn you when you drive over the speed limit, or when you are about to hit something while trying to park in a tight spot.

Linting tools also evolve to provide more accurate and helpful warnings. ESlint always surprises me with very accurate warnings. Additionally, its default recommendations are getting better with each upgrade.

Another analogy that I love in modern cars is automation. Any task that you repeat often should be automated once its purpose and value are clear. Instead of restarting that program every time you save the file, have a monitor process that automates that. Rather than running a format command on your code before you share it with others, have a command that automatically does that every time you commit your code to source control.

Modern cars automate so many things as well. The obvious example here is adaptive cruise control, but other subtle examples include automatic windshield wipers and automatic high beams at night (my favorite!).

Imperative vs Declarative Programming

When you need to do something, there is always the what and the how aspects of it. What exactly needs to be done and how do we do it.

Imperative programming is about the how. Declarative programming is about the what.

What? How? And why should you care?

An imperative approach represents a list of steps. Do this first, then do that, and after that do something else. For example: Go over a list of numbers one by one and for every one add its value to a running sum.

A declarative approach represents what we have and what we need. For example: We have a list of numbers and we need the sum of those numbers. The imperative language is closer to the computers of today because they only know how to execute instructions. The declarative language is closer to how we think and command. Get it done, please. Somehow!

The good news is computer languages have evolved. Computer languages offer declarative ways to do the needed imperative computer instructions. Just as cars have evolved from manual stick shift into automatic and self-driving ones!

Imperative programming is like driving a stick shift car. You need to do manual steps (press the clutch, depress it slowly, change gears incrementally, etc). Declarative programming is like driving an automatic car — you just specify the “what”: Park or Drive.

You cannot program declaratively unless you have the tools that enable you to do so. While you can imperatively drive an automatic car (by switching to manual mode) you cannot declaratively drive a stick shift car. If all you have is a stick shift car, imperative programming is your only obvious choice. This is unless you take the time to install an automatic gear shifter, which might be worth it in the long term. If you can afford a new car, you will probably go with an automatic one unless you are that true nerd who still likes to program with Assembly!

Assemblyis the original true imperative low-level computer language with pure instructions that directly translate into machine code.

Note that imperative programming might produce faster programs. Additionally, declarative programming requires less effort from you. In general, it will also require less effort to be maintained. Coding does not have to be one way or the other. Any non-trivial computer program will most likely have a little bit of both approaches. Also, knowing how to code declaratively is great, but it does not mean that you do not need to learn the imperative ways as well. You should simply be confident using both.

Алати који вам омогућавају декларативно програмирање еволуирају у боље и брже начине да вас доведу тамо где идете. Крајње декларативно искуство са модерним аутомобилима је самовозеће. „Шта“ постаје одредиште, а аутомобил ће урадити све остало. Ово је некако, вероватно, и будућност програмирања. Имаћемо програме који разумеју све циљеве и они могу само на своју магију створити логику да нас доведу до тих циљева.

Која је ваша омиљена аналогија? Обавестите ме у одељку са одговорима испод.

Хвала за читање!