a tumblelog
Tue 10 Nov 2020

Eleven Years of Go

Today we celebrate the eleventh birthday of the Go open source release. The parties we had for Go turning 10 seem like a distant memory. It’s been a tough year, but we’ve kept Go development moving forward and accumulated quite a few highlights.

Source: Eleven Years of Go, an article by Russ Cox.

This is how I git

Every now and then I get questions on how to work with git in a smooth way when developing, bug-fixing or extending curl – or how I do it. After all, I work on open source full time which means I have very frequent interactions with git (and GitHub). Simply put, I work with git all day long. Ordinary days, I issue git commands several hundred times.

I have a very simple approach and way of working with git in curl. This is how it works.

Source: This is how I git, an article by Daniel Stenberg.

Optimizing your code is not the same as parallelizing your code

You’re processing a large amount of data with Python, the processing seems easily parallelizable—and it’s sloooooooow.

The obvious next step is switch to some sort of multiprocessing, or even start processing data on a cluster so you can use multiple machines. Obvious, but often wrong: switching straight to multiprocessing, and even more so to a cluster, can be a very expensive choice in the long run.

In this article you’ll learn why, as we:

  1. Consider two different goals for performance: faster results and reduced hardware costs.
  2. See how different approaches achieve those goals.
  3. Suggest a better order for many situations: performance optimization first, only then trying parallelization.

Source: Optimizing your code is not the same as parallelizing your code, an article by Itamar Turner-Trauring.