Gee, it's my turn to throw some gloom light on iptables! There are hundreds or even thousands of articles on the topic out there, including introductory ones. I'm not going to put either formal and boring definitions here nor long lists of useful commands. I would rather try to use layman's terms and scribbling as much as possible to give you some insights about the domain before going to all these tables, rules, targets, and policies. By the way, the first time I faced this tool I was pretty much confused by the terminology too!

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Well, I don't see any practical applications of the approach I'm going to describe... However, I do think that messing about with things like this is the only way to gain extra knowledge of any system internals. We are going to speak Docker and Linux here. What if we want to take a base Docker image, I mean really base, just an image made with a single line Dockerfile like FROM debian:latest, and convert it to something launchable on a real or virtual machine? In other words, can we create a disk image having exactly the same Linux userland a running container has and then boot from it? For this we would start with dumping container's root file system, luckily it's as simple as just running docker export, however, to finally accomplish the task a bunch of additional steps is needed...

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In the previous article, we learned how to implement a simple but workable event loop. However, programs which are supposed to be run by the event loop are full of callbacks. This is the usual problem of event-loop-driven environments. When business logic becomes reasonably complicated, callbacks make program's code hardly readable and painfully maintainable. And the callback hell begins! There is plenty of ways to deal with the artificial complexity arose due to callbacks, but the most impressive one is to make the code great flat again. And by flat, I mean callback-less and synchronous-like. Usually, it's done by introducing async/await syntactic feature. But every high-level abstraction is built on top of some basic and fundamental ideas. Let's check the async/await sugar out and see what exactly happens under the hood.

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There is plenty of articles out there about the event loop. However, as a software engineer, I prefer to read code, not text. And there is no better way of learning a new concept than implementing it yourself. So, let's try to grasp the idea of the event loop by coding a new and shiny one.

NB: In the article, we will try to describe the idea of the event loop in general, not a specific implementation of the event loop in Node.js or Python, or some other language/library.

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One day you were hired by a startup to build yet another web site service. The problem sounded similar to numerous back-ends you had been doing before. So, you decided to move with python to be conservative enough and pick flask to be lightweight but yet powerful enough. Nobody was fired for buying IBM starting things in python, wise man's choice.

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In contrast to protobuf2 there is no way in protobuf3 to mark some fields as optional and some other fields as required. Instead, any field might be omitted leading this field to be set to its default zero-value. I believe there were many good reasons for such a design decision. However, while this behavior might be superior to the proto2's explicit distinction between required and optional fields, it also has some unfortunate implications.

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Writable streams are an abstraction for a destination to which data is written... And this time it's a concise abstraction! Compared to vague readable streams (multiple operation modes behind single abstraction) writable streams implement only one mode and hence expose only one essential method write(chunk). Nevertheless, the idea of writable streams is not trivial and it's due to one nice feature it provides - backpressure. Let's try to wrap our mind around writable stream abstraction.

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Readable stream is an abstraction for some data source. Which could be hard to grasp and even harder to use...

Everybody knows that readable streams support two modes of operating (flowing and paused) and piping to writable streams. It's not that easy to understand the purposes of these mechanisms and behavioral differences though. Since one readable stream abstraction stands for multiple usage modes its public interface (i.e. the set of methods and events) is a bit inconsistent. Usage of readable streams might be totally confusing without the understanding of the underlying ideas. In this article, we will make an attempt to justify the abstraction of readable streams trying to implement our own file reader. Also, we will have a look at some nicer ways to consume readable streams.

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Do you want to run an executable file from your program? Or execute a shell command programmatically? Or maybe just parallelize your code? Have you read a lot of information regarding execve() functions family and fork() but still have a mess in your head? Then this article is for you.

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