read write.as

I was on a camp with my brothers and sisters. There were lots of other people too. We could swim in a quite short swimming pool. I was happy about that, because I liked it, and wanted to try my new breathing mouthpiece.

Then then war broke out. We were transported to other countries by train. In there I fucked this not-so-good-looking-chick, but I didn't come. Then I think, I must've misplaced something of hers, and she wrote these long posts about it.

I think back in the days, when schwarzie wanted to go to america, it was because he wasn't satisfied with the little information he had about it.

Now you can follow your idols on insta stories, every day. So you're not getting only vague descriptions of what's generally happening overseas, but you can literally see their 'normal' life. You so much more! Infinite amount of information. And if you're lucky, there's probably a sex tape of your fav celeb already released.

Of course it's polished and sweetened, but you're satisfied for the time being. Until the next time, when desire of leaving what you have and going into the unknown appears. When you're getting too lonely, or frustrated. Fap, play a game, watch an interview.

Same is for passion, entrepreneurship etc. We read stories of people who really live. But we, we're not living.

About

My name is Michael and I write in order to figure out what I'm thinking.

If you'd like to talk, you can reach me at nazarianhar@gmail.com

11.13 (onbewerkt2)

Er is weinig op te merken. Rijp op de pannen die het dak bedekken. De schaduw van de kale takken op de wit geverfde omheining van het balkon. De reflectie van de boom die de takken heeft gemaakt in de ramen van het huis hier tegenover. Auto’s die gekrabd gaan worden. Het geluid van 2 stemmen, 2 gitaren een drum en een bas uit een kleine luidspreker. Geluid uit een telefoon die verder geen enkele aandacht nodig heeft.

Ik beleef herinneringen en mijn lichaam vraagt om energie.

Ik kan weinig opmerken. Ik zie een programma een schema van 2 dagen geleden. Ik kan zien wat er was en wat ik zag en hoorde als ik het wil weten maar niet meer weet. Dat ik herinneren op moet halen. Zoeken in een vooraf gemaakte herinneringsschema. Ik was daar toen. Dat was er toen nog.

Ik zie het zonlicht schaduwen maken en dat is al even geleden. Ik zie een pen die op een bord had kunnen schrijven en dat had ik dan later met een borstel weggeveegd. Ik zie een spiegel die van de deur naar beneden viel en niet brak, zelfs aan dat geluk ben ik ontsnapt. Ik voel een ruimte die gevuld moet worden, een gat waar eergisteren de toekomst leefde. Ik schrap mijn ongeschreven agenda leeg. Hier niet heen, daar niet heen.

Ik zie mijn renpaard op wielen dat ik zelf vooruit moet trappen. Het is omgeven met ruwe aarde en andere droge stukjes natuur. Het moet worden opgefrist en opgeknapt. We moeten later even rennen naar de stad ik word moe en het paard vies en versleten. De wielen aan de ketting en de ketting aan de trappers en mijn benen daar weer op. Duw de trappers naar benden en ik kom kilometers verderop tot stilstand.

Dan laat ik hem achter bij een raam op een parkeerplaats, altijd hetzelfde raam. Ik wil de schijn behouden dat alles altijd is waar het altijd is. Dat is geruststellend, zo zorg ik dat verrassing en verwarring niet te veel tijd in nemen. Ik wil graag een dag vol eeuwigheid.

Zodat ik alleen hoef te herinneren dat iedere dag hetzelfde was.

De rijp kleeft aan het gras en de schutting, rijp is het schuttingwoord van de dag. De kou stelt de groei uit, alles wil zijn energie bewaren. Alleen wij niet. Ik warm de vloer op, ik warm het water op zodat het lekker voelt als het me overspoeld. Ik merk het zonlicht op in mijn beeldscherm en zie mijn handen.

De details opzoeken om iets op te merken in het algemene niets. Ik zoek iets om te zien, te voelen, te denken, te horen, te bewonderen. Reden om lief te hebben en geliefd te zijn. Dat gat in de toekomst op te vullen met heden en zinnen. Iets om leegte te laten zien.

De stemmen en de instrumenten zijn stil gevallen, ik laat dit ook zo maar gaan. Ik ga even zijn als het gras vandaag moet zijn. Ik omhul me met rijp, ik koel af en wacht tot de temperatuur oploopt.

7.18

Heerluk Heldur Sociaal Glijmiddel (bewerkt en helemaal klaar mee , afgelopen, afgerond, afgemaakt, afgebroddeld)

Blijf de verveling voor, zorg voor genoeg bier. Valt het tegen dan valt de drank niet goed. Zorg dat je zo min mogelijk opmerkt van de plek waar je zit, zorg voor genoeg bier. Blijf de ergernis voor zorg voor genoeg bier. Let niet op je gedrag, zorg voor genoeg bier. Wil je herinneringen vervagen zorg voor bier. Wil je een levensfase innemen zorg voor genoeg bier. Wil je bier verkopen zorg voor een associatie. Verdoving met genoeg bier.
Hou het leuk zorg voor genoeg bier. Wil je geen zorgen zorg voor genoeg bier. Wil je niet zien of horen zorg voor genoeg bier. Horen ze je niet zorg voor genoeg bier. Val je anders niet op zorg voor genoeg bier. Durf je niets te zeggen, vinden zorg voor genoeg bier. Ben je waar je niet wilt zijn zorg voor genoeg bier. Hoor je jezelf stomme dingen zeggen zorg voor genoeg bier. Ben je een rotzak maar je wilt niet dat een ander dat ziet zorg voor genoeg bier. Heb je een klote humeur zorg voor genoeg bier. Heb je hoofdpijn zorg dan voor genoeg bier. Muziek aan de man brengen zorg voor bier. Bier aan de man brengen zorg voor muziek. Jezelf aan de man brengen zorg voor genoeg bier. Sta je stevig op je benen zorg voor genoeg bier. Jong publiek nodig zorg voor genoeg bier. Wil je anderen ontmoeten zorg voor genoeg bier. Wil je een ander zijn zorg voor genoeg bier. Verdoving zorg voor bier. Heb je een hekel aan jezelf zorg voor bier. Wil je de beest uithangen drink bier. Wil je relaties zonder communicatie zorg voor genoeg bier. Wil je je ergernis niet onder stoelen of banken steken drink je bier op. Wil je opscheppen drink bier, wil je een kater drink bier. Wil je opscheppen over een kater drink bier. Wil je niks drink bier. Weet je niet wat je wil drink bier. Wil je leugens verkopen zorg voor genoeg bier. Wil je je tijd kwijt aan genoeg bier, dat kan. Zorg voor genoeg bier. Wil je voetbal zorg voor genoeg bier. Wil je iets door een ander laten doen zorg voor genoeg bier. Wil je niet waar je weten waar je geld aan uitgeeft zorg voor genoeg bier. Wil je teleurstellingen zorg voor bier. Zijn je vrienden van de Amstel? Drukte nodig maak een plek met bier. Wil je een rustig hoofd en een onrustig lijf drink genoeg bier. Wil je niet uit de toon vallen drink dan mee. Wil je informeel zorg voor bier. Wil je samenhang maken zorg dan voor een plek met bier. Wil je een kring geef dan een rondje. Wil je nergens over praten en nergens naar luisteren zorg voor genoeg bier. Wil je laten zien wie je echt bent drink dan genoeg bier. Wil je klote dingen zeggen over anderen drink dan genoeg bier. Wil je iets op een feestje doen lijken zorg voor genoeg bier. Wil je een domme lelijke plek verstoppen zorg voor bier. Wil je je niet thuis voelen ga naar een plek waar ze bier schenken en dan voel je je niet thuis. Wil je iets bewaren wat niet meer is zorg voor genoeg bier. Heb je veel kapot te maken drink heel veel bier. Heb je het niet naar je zin neem nog een bier. Heb je het dan nog niet naar de zin neem nog een bier. Wil je een ander geef de ander genoeg bier. Wil je je eigen weerstand breken zorg voor bier. Wil je laten zien hoe sterk je bent neem dan genoeg bier. Wil je niets goeds doen voor een ander begin een bierbrouwerij. Wil je aan verslaving geld verdien belast het bier. Wil je iets vieren zorg voor bier. Sta je met lege handen haal bier. Wil je je verdriet vergeten drink dan bier. Wil je een stad vol bier zorg voor een universiteit. Het vat is nog niet leeg…. Wil je je ongemakkelijk voelen ga naar een plek waar ze alleen water schenken.

I wanted to share the flavors I like the most and definitely recommend anyone to try. The closer it is to the top the more I like it. The ones toward the bottom is one I don't like.

These are all from the Lipton brand.

1) Lemon ginseng green tea – it doesn't taste herbal at all, smells good, and doesn't taste like anything to me.

2) Purple acai blueberry green tea – doesn't taste completely fruity which I like, smells good, tastes good.

3) Cranberry pomegranate green tea – smells and tastes sour (makes me feel it's burning the fat) and it smells good. I don't mind the taste. It reminds me of biting into a grapefruit.

4) Orange passionfruit jasmine green tea – smells and tastes good. It's #4 only because I've had this many times in the past.

5) Magnificent matcha green tea mint – smells and tastes herbal. I hate herbal teas. If I'm sick then I don't mind it. For everyday herbal teas are not my thing. The smell makes me nauseous. If you drink it cold it's more tolerable and the scent is not that strong.

All of these were fairly cheap. Almost $3 per box with 20 bags in them. It'll last a while.

Just wanted to do a review on this since there's not many people talking about her products. Before I bought this product I knew it was mostly going to be vitamin C because that's what helps you build your immunity. I'm only taking this vitamin during the winter and it is working great! Everyone is getting sick and I'm still healthy.

Another thing I like about this product and what justified the $45 tag, for me at least, is that this product has a blend of probiotics in it! Probiotics are already expensive costing around $20 for not even 30 capsules. The ones you find at any retail store aren't that great. I had a pharmacist look at the Gut Instinct supplement from HUM and was told that's better than Cultrelle or any that they sell.

The key is to find probiotics that have more than just 2 or 3 cultures of bacteria. They try to sell you a high count of cultures but look at the names of the bacteria. Not all do the same thing!

I bought this earlier this month and have been trying it out. It's definitely a staple for me! Before I heard of Dr.Jess my physician told me my thyroid is enlarged. They wanted me to do further testing and I didn't want to at the time. Plus I would have to pay about $200 because my insurance didn't cover it. Another doctor did tell me they felt my thyroid was enlarged.

I don't take medications unless I really have to. Before this year I never took vitamins. After using the Thyroid Master for a few weeks now, I decided to skip one night. I was exhausted and didn't feel like taking it. Didn't think anything of it. When I woke up I felt drained even though I got 8 hours of sleep! I tried to go back to sleep and couldn't.

That's how I know this vitamin is doing something for me. It's pretty expensive but if you bought everything and blend it yourself, it would cost the same. It's definitely worth a try! If you end up loving it you can get her subscription service. Dr.Jess also sells cosmetics!

Drjess.com

Tag her in your photos of her products. She'll repost it into her instagram story!

I've tried this vitamin once and it's enough for me to not try it again. It's suppose to make your stomach look flat by getting rid of bloating. It did the exact opposite for me! It made me starving and I tried to not eat everything. I felt disgusting and fatter than when I started my diet.

Hum seems like a cute brand. Right now I can't be part of their subscription service. Financially it's not doable for me now. Cancelling their monthly plan was easy and painless. For those who want to buy something from them, as long as you choose the monthly plan, you can cancel at any time! You have to cancel before they ship out your next box.

M. Night Shyamalans Karriere in Hollywood als holperig zu bezeichnen wäre wohl etwas untertrieben. Ein Tal zwischen zwei Bergen trifft es da schon besser, stellt man sich die Reaktionen auf sein Gesamtwerk einmal als Lorenz-Kurve vor. Nichtsdestotrotz haben Filme wie The Sixth Sense, Signs und allen voran Unbreakable bei mir für immer einen sicheren Platz im Herzen. Letzterer ist immer noch mein Lieblings Superheldenfilm ohne Comicvorlage. Umso erfreuter war ich, als sich Split überraschend als Nachfolger outete, nachdem sich Shyamalans Ruf zuvor mit The Visit gerade wieder erholt hatte. Dass er es jetzt trotz des Auf und Abs in seiner Karriere nach 19 Jahren geschafft hat, mit Glass nicht nur einen Abschluss der Trilogie vorzulegen, sondern auch noch einen, dessen Rechte an den beiden Vorgängern bei zwei verschiedenen Produktionsfirmen liegen, weshalb sich Universal und Disney nun die Rechte an Glass teilen, ist nicht etwa trivial, sondern durchaus ein kleines Lizenz-Wunder von Hollywood.

Noch viel schöner ist es natürlich, dass mich Glass durchweg sehr gut unterhielt und die Reihe für mich schlüssig, befriedigend und natürlich nicht ohne mindestens zwei Shyamalan Trademark Twists beendet hat. Das übernatürliche Talent James McAvoys bei der erneuten Darstellung der 20 Persönlichkeiten aus Split steht hier neben Bruce Willis und Samuel L. Jacksons routiniertem Schauspiel deutlich im Vordergrund. Aber auch die teilweise nach 19 Jahren wiederkehrenden Nebendarsteller, die omnipräsenten Schemata aus der Welt der Comics und ein ausgereiztes Spiel mit Farben trägt zum runden Gesamtbild des Films bei.

Die zwei Stunden und zehn Minuten Filmlänge wirkte auf mich zwar nicht ermüdend, hätte aber zu Gunsten des Pacings gerne um 20 Minuten gekürzt werden dürfen. Einen Directors Cut des angeblich dreieinhalb Stunden langen Original-Schnitts würde ich mir aus reinem Interesse heraus allerdings trotzdem gerne anschauen. So richtig genug habe ich von der Welt nämlich noch nicht. Und das, obwohl wir seit Jahren mit Superheldenfilmen nur so beschmissen werden. Aber wer weiß. Vielleicht kommt ja in fünfzehn Jahren noch ein vierter Teil. Ob M. Night Shyamalans Lorenz-Kurve dann einen weiteren Berg oder einen weiteren Graben aufweist bleibt abzuwarten.

#Film

Hi. Most would classify me as a white male. This means a variety of things, depending on who you are and your background. We categorize things to make sense of them. This is how our human brain works. By the way, that's my favorite classification for myself— human. Haven't we seen enough science fiction to understand that the only way to defeat the aliens is to come together under the banner of humans? Of course, the assumption there is that the aliens need defeating. Instead, maybe we need to change the banner to sentient beings? The Temptations and Edwin Starr had it right back in 1969 and 1970, “War. What is it good for? Absolutely Nothing.”

The Daily Dot article, “Mastodon is crumbling” asks you to choose sides over at Mastodon. Perhaps that is a strong statement. Maybe I should say Ana Valens presents two sides to readers. Furthermore, in the article Eugen Rochko is seen putting users on opposing sides. Here we have two perspectives from two different people. Their categorization of the users is unique to their own context. Indeed, if I were to go further in implying Valens viewpoint is influenced by her status as a LGBTQ reporter or Eugen is affected by his whiteness, I am making assumptions. Even if either of them were to concede to my implications or explain their perspective in quoted detail it doesn't matter. Myself, and you, dear reader, will form our own opinions about them. Using our own lenses, our context, we will make our own judgments. You've most likely formed an opinion of me before finishing the title above. If not, you may have after the second sentence when I declared that I am a white male. My privilege in a world that favors white men means I cannot begin to speak to your feelings or experiences. You're right, but it's not entirely because of my skin color. We're individuals. I will never be able to feel what you've felt as you lived your life. Yes, I'm glossing over the fact that the world favors my hairy white ass. My struggle in this life is different than yours, but that doesn't make it less painful.

The floor I'm dancing around on is this— pain. My pain may be self-inflicted while yours is societal. Pain, it sucks. It really sucks, a lot. In general, we both have pain. I wish we could come together in this common understanding, rather than categorizing by sexual preference, color, or preference for upgrades to an open source project like Mastodon.

Perhaps we need to stop comparing Mastodon to Twitter. Again, our experiences on Twitter were different. The interesting thing about Mastodon is that we can make our own communities and still connect with those who we interact with and respect within different communities. Instead of spending time pointing fingers, choosing sides and building fences around our communities we can remember that each of us experiences pain. Politics isn't the answer, compassion is.

The internet is often praised for speed, instant communication. We use things people said online to crucify them. We talk of futures we fear or delight in, but it is all in the past. The internet is far from instant. People change every moment. We have to stop condemning each other. I'm not against debate, but remember we're all suffering and the below each side of an argument is someone suffering.

Where I am there's a snow storm about to happen this weekend. In my area I'm suppose to see some snow tonight. Either way my energy is so good right now I don't even care! Nursing school starts in 3 days for me and I couldn't be happier. I'm beyond excited and ready for this. The best decision I made is choosing to get myself a career for 2019-2020!

Putting all that good energy out there.

Whenever I have an out of town music gig, I go through a checklist of items to confirm are packed and ready to go before leaving. Nearly all are the standard items (horn, mouthpiece, music and/or tablet to read music, gig clothes, street clothes, phone/tablet charger) but I've begun including a few items that are not normally thought of.

Since I have moved away from a smartphone in the last month, I'll bring my Kindle along for when I have time to kill. And since I have a food sensitivity, I always bring activated charcoal, both on my person and in my toiletry bag. I really never know what food I am going to be provided or have the option of so for me, it's better to be safe than sorry (and for those unfamiliar, it's a wonderful home remedy for nearly any stomach ailment). And speaking of food, for multiple days away, I've been bringing along a box or two of Clif bars. Not only are they safe for me to eat, they work as great snacks or part of a meal.

It's always good to be overly prepared when away from home.

This is a test

Since some days i think to create a blog to publish some stories. It would be more like a mix between 4-koma and plain text story. It's the draft concept anyway.

What do you think of it, anon ?

When approaching a programming challenge, there will always be multiple ways to implement a solution. Sometimes the differences will be trivial stylistic choices. Other times, they can be the reason one solution works at scale and another other cracks under pressure. To determine the most effective way to solve a problem, programmers analyze the complexity of the algorithms used.

Big O notation provides a shared language for describing the complexity of algorithms. It acts a shorthand summary that helps communicate in broad strokes the general degree of complexity of a process. This article will attempt to shed light on the core ideas behind Big O as well as a few of the most commonly referenced examples.

Complexity

Algorithms can be measured in terms of time complexity, or in terms of space complexity. Time complexity deals with the total execution time of a process given a particular set of inputs, with all other variable factors such as processing power being equal. Space complexity relates to the amount of disk space or physical memory required to execute a process.

A function may work very quickly, but still consume a large amount of computing resources, while another may utilize minimal memory but require many iterations that lead it to take a greater amount of time.

Worst Case Scenarios

array = [1,0,0,0,0,0,0,0,0]

Imagine you are writing a function that tries to find the position of the 1 in an array like the one above. One very simple solution would be to start at the beginning of the array and step through each item until you arrived at the desired 1.

def indexOfOne(array)
  array.each.with_index do |item,index|
    return index if item == 1
  end
end

In the example array, this would be extremely fast because the first step would yield a match. Imagine if the same strategy (algorithm) were applied to the following array.

array = [0,0,0,0,0,0,0,0,1]

Here, the same approach would take 9 steps because it wouldn’t encounter the 1 until the very end of the array. So is this a slow algorithm or a fast one?

In this case, only the second example matters. Big O notation only concerns the worst possible outcome of a process. What is the longest it could take? What is the maximum amount of memory or disk space it could require?

Inputs

Big O notation is all about scale. The above function may take a trivial amount of time to execute with a nine element array, but how well would it work if the array had thousands or even millions of elements? This is the scale of thinking that is required when designing applications that will serve large populations of users and deal with significant amounts of data. It is easy to picture how inefficient this algorithm would be when used to try to find string matches across millions of HTML documents, or to seek products in a massive ecommerce database.

The main factor here is inputs. The input in the first example was a short array of size nine. Big O describes how fast an algorithm’s running time or resource consumption will increase as its inputs increase.

Consider the following two functions:

Function A

def itemIncreaser(array)
  array.each |item| { return item + 1 }
end

Function B

def itemConverter(array)
  array.each |item| do
    item += 1
    item += 2
    item += 3
    return item
  end
end

As far as Big O notation is concerned, both functions are equally complex. How is this possible when they look so different? Remember, Big O is about inputs, so consider what happens at different scales with each function.

With an input array of 10 items, Function A would need to take one step per item, simply incrementing each by 1 and returning the result. Thus we could say that it will take 10 “steps” to work through 10 items. Function B is longer, and will require 3 steps per item, thus it would take 30 total steps for the same 10 item input.

Now, consider what happens when the same functions are given an input array of length 1,000. Unsurprisingly, Function A would take 1,000 steps, while Function B would take 3,000. The key point here is that although Function B requires 3 times as many steps as Function A, the rate of change is consistent across both functions. With any given inputs, at any scale, Function B will always take 3 times as many steps as Function A.

Notation

In terms of Big O, both Functions A and B would be described as having a runtime of O(N). The runtime describes, in abstract, how long an algorithm will take relative to its inputs. The O is simply a prefix indicating Big O notation, while the characters within the parenthesis describe the actual runtime.

Note that runtime is not exact – this isn’t designed to say that these functions will take precisely 200 milliseconds per input item or utilize 120KB of disk space. Instead, O(N) means that the runtime of the function will increase at a rate that is directly proportional to the number of inputs (N). An algorithm with an O(N) runtime will take steadily more time given more inputs.

While there are numerous different types of runtimes, knowing a handful of the most common will enable an engineer to quickly convey the general complexity (and ability to scale) of an algorithm.

”This function runs quickly in the test environment, but how well will it handle the full dataset in production?”

“It will scale predictably, it has an O(N) runtime.”

Example Runtimes

O ( 1 )

This describes a runtime that is static regardless of input size. Generally, algorithms of this type will lack any type of iteration.

def myFunction(array)
  doSomethingWith(array[0])
end

Regardless of what happens inside the function named doSomethingWith, this function will always take the same amount of time no matter how large the input array is because it only uses the first element of the array. When execution time is independent of inputs like this, the algorithm is said to have an O(1) runtime.

O ( N² )

This describes an algorithm that will take exponentially more time or space with greater inputs. The following is a very basic example.

results = []

def multiplier(array)
  array.each do |x|
    array.each do |y|
      results.push(x * y)
    end
  end
end

One quick indication of this type of runtime is nested loops. The function will generate four results if given an array of two digits. For example an input array of [3,5] would yield a results array of [9,15,15,25]. An input of three would yield nine results. An input of 100 would yield 10,000. Note how dramatically the amount of space required is rising with growing inputs.

This is a common pattern that can create significant problems at scale. When algorithms rely on nested loops, there is a great likelihood that they will fall into this category. Similarly, if the function above added another nested loop inside of the existing ones, it would be said to have a runtime of O(N³).

O ( 2ᴺ )

This runtime frequently relates to algorithms that use recursion. Recursion, in very simplified terms, can be thought of as a function calling itself. A simple illustration follows.

def doRecursion(input)
  return input if input <= 1
  return doRecursion(input - 2) + doRecursion(input - 1)
end

This function uses itself internally and is thus recursive. Each iteration will trigger two more calls to the function, and each of those will do the same. If the recursive function called itself three times, it would instead be marked as O(3ᴺ).

This is one of the most complex runtimes, as a moderate increase in input size can result in a massive increase in resulting execution time or memory space.

O ( log N )

This describes a function with a logarithmic runtime. Somewhat opposite to the previous runtime, these algorithms increase noticeably in execution time with the first few increases in input size, then level out with continually larger inputs. The most common example of this runtime is a process called a binary search.

A binary search is a method of finding an element in a sorted array. It steps through the array, dividing the array in half at a pivot point at each step, and determining if the desired element will be before or after the pivot point. The following steps illustrate how a binary search would be used to find the 5 in an array of fifteen numbers.

[0,1,3,3,4,5,8,12,15,15,18,21,23,26,30]
                   ^

The pivot point starts at the midpoint of the full array. Because 5 is less than 12, it must fall to the left of the pointer given that the array is sorted. Thus, the 12 and all elements to the right are discarded and a new pivot point is placed at the center of the remaining portion of the array.

[0,1,3,3,4,5,8,12                     ]
         ^

Because 5 is greater than 4, the 4 and all elements to the left are discarded and the pivot moves again to the new center of the array.

[          5,8,12                     ]
             ^

With one final repetition of this process the pivot will end up on the desired number, 5.

[          5                          ]
           ^

This binary search is an example of an O(log N) runtime. The input size can increase greatly without increasing the number of steps needed to find a result because the inputs are halved at each step. Doubling the length of the input to 30 elements would only add a single extra step in the previous example, because the first step would immediately cut the input array back in half to 15 elements.

Because of this relationship between input size and time/space requirements, logarithmic algorithms can be effective at scale where an O(N) or O(N²) algorithm would begin to become prohibitively expensive.

Further Resources

When dealing with small-scale projects Big O notation can seem like an esoteric concept that’s best reserved for engineering interviews. It is when scale becomes a factor that it suddenly becomes essential to be able to describe in a concise way how implementation decisions will impact the ability of a program to respond to increasing inputs. Here are a few more resources to continue developing a deeper understanding of Big O.

A beginner’s guide to Big O notation – A brief but clear summary of common runtimes, and one of the resources that I consulted while writing this article.

Big-O Algorithm Complexity Cheat Sheet – I highly recommend taking a look at this page to see its visual comparing the complexities of various runtimes.

Big O notation: definition and examples – Somewhat math-heavy but rich dive into Big O, complete with handy visuals.