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According to Jackie Stewart, a three-time world champion F1 driver, having an understanding of how a car works made him a better pilot.

“You don’t have to be an engineer to be a racing driver, but you do have to have Mechanical Sympathy

Martin Thompson (the designer of the LMAX Disruptor) applied the concept of mechanical sympathy to programming. In a nutshell, understanding the underlying hardware should make us a better developer when it comes to designing algorithms, data structures, etc.

In this post, we will dig into the processor and see how understanding some of its concepts can help…

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A couple of months ago, I wrote a post about Go and CPU Caches:

Then, I wanted to extend the scope of this post. Following this idea, I had the chance to give a talk to GopherCon Turkey 2020. The topic is the following: Mechanical Sympathy in Go.

I tried to cover the following topics:

  • CPU architecture introduction
  • Locality of reference principles: temporal vs spatial locality, predictability, striding
  • Data-oriented design: introduction, slice of structs vs struct of slices, etc.
  • Pitfalls due to a bad utilization of CPU caches: cache associativity, critical stride
  • Concurrency: false sharing

Here is the video of my talk:

The beginning of the talk was unfortunately ousted. Yet, you can find the slides here for the missing introduction:

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  • Find the only element that appears once
In an unsorted array of integers, every element appears twice except for one element that appears only once. Return this element.Example:Input: a=[1, 4, 2, 4, 1, 3, 2]
Output: 3


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With the rise of distributed architectures, consistent hashing became mainstream. But what is it exactly and how is it different from a standard hashing algorithm? What are the exact motivations behind it?

First, we will describe the main concepts. Then, we will dig into existing algorithms to understand the challenges associated with consistent hashing.

Main Concepts


Hashing is the process to map data of arbitrary size to fixed-size values. Each existing algorithm has its own specification:

  • MD5 produces 128-bit hash values.
  • SHA-1 produces 160-bit hash values.
  • etc.

Hashing has many applications in computer science. For example, one of these applications is called…

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  • ReactiveX is an API for asynchronous programming based on the observer pattern.
  • RxGo is the official Go implementation of ReactiveX (a cousin of RxJS, RxJava, etc.).
  • There are +50 new operators and multiple new features (hot vs cold observable, connectable observable, backpressure, etc.)
  • Yes, Go has already great concurrency primitives and yes, there is still no generics. Nonetheless, RxGo may still be worth a look.


In ReactiveX, the two main concepts are the Observer and the Observable. An Observable is a bounded or unbounded stream of data. An Observer subscribes to an Observable. Then, it reacts to whatever item the…

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I wanted to let you know that I just released Algo Deck. It is a free & open-source collection of +200 algorithmic cards.

Each card is a synthesized way to describe a concept. For example:

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This is not an analogy for the sync package quality :)

Let’s take a look at the Go package in charge to provide synchronization primitives: sync.


sync.Mutex is probably the most widely used primitive of the sync package. It allows a mutual exclusion on a shared resource (no simultaneous access):

It must be pointed out that a sync.Mutex cannot be copied (just like all the other primitives of sync package). If a structure has a sync field, it must be passed by pointer.


sync.RWMutex is a reader/writer mutex. It provides the same methods that we have just seen with Lock() and Unlock() (as both structures implement sync.Locker interface). …

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Testing is fun

A small trick I wanted to share.

Sometimes, you need to make sure your Go tests are executed sequentially. I did not mention unit tests as one would argue that if unit tests cannot be executed in parallel, these are not unit tests.

Anyway, the first option is to run your tests using go test -p 1.

The second option is the following:

In every test, we have to call defer seq()(). The locking is the first statement executed whereas the unlocking is the last one. This option guarantees that TestFoo and TestBar are executed sequentially regardless of the test option used.

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This post is a summary of my 2-day experience at GopherCon UK 2019. I did not attend the first day (workshops only).

Disclaimer: In this post, I am expressing my opinions about some talks. Under no circumstances, I am making a value judgment on the speakers.

Finding Dependable Go Packages

The conference started with a keynote from @JQiu25 who’s working at Google in the Go team.

She described the 3-step process when it comes to working with an external open-source library:

  • Discovery: Searching and finding a solution for a given problem (via Google, Twitter or whatever).
  • Evaluation: Evaluating a solution.
  • Maintenance: Contributing back to…

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We are developing on two different Go projects using modules:

  • A module
  • Another module that depends on the first one

Let’s say we made some changes to and we would like to test the impacts on before committing them.

Without Go modules, it was pretty straightforward as our changes were done in GOPATH so they were automatically reflected.

With Go modules, the trick is to replace our import by the physical location of the project:

Here, /path/to/local/bar is the actual location of the bar project containing the local changes.

We can also use the following command:

go mod edit -replace


Teiva Harsanyi

Software Engineer, Go, Rust, Java | 改善

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