Thread pools on the JVM should usually be divided into the following three categories:
- CPU-bound
- Blocking IO
- Non-blocking IO polling
Each of these categories has a different optimal configuration and usage pattern.
| #!/usr/bin/env bash | |
| # | |
| # Script that detects if Scala's SBT is installed and if | |
| # not then it automatically downloads and installs it at | |
| # a specified path. | |
| # | |
| # Author: Alexandru Nedelcu (https://alexn.org) | |
| # | |
| set -e |
| #!/usr/bin/env bash | |
| # | |
| # Script that detects if Scala's SBT is installed and if | |
| # not then it automatically downloads and installs it at | |
| # a specified path. | |
| # | |
| # Author: Alexandru Nedelcu (https://alexn.org) | |
| # | |
| set -e |
| Introduction | |
| ============ | |
| Industry statistics as a whole have failed to improve much since 1968, when software engineering and | |
| scientific management were introduced as means for resolving the "software crisis". Unfortunately | |
| abandoned projects, cost/time overruns, and bloated, buggy software still dominate the landscape. | |
| In spite of the efforts to mitigate this situation --like XP, agile, software craftsmanship or DDD-- the | |
| reality is that a usual software project stack involves an increasingly larger number of programming | |
| languages, DSLs, frameworks, systems, tools, techniques and processes, so it is a fact that the |
Zebu https://github.com/modernserf/zebu
Constraints - Crista Lopes tagide.com/blog/research/constraints
Little Languages - Jon Bentley staff.um.edu.mt/afra1/seminar/little-languages.pdf
Purpose-Built Languages - Mike Shapiro
The first post has been published: https://www.swyx.io/writing/cloud-distros
The second post has been adapted for Temporal: https://www.swyx.io/why-temporal/
these are bullet points of a blogpost on a topic i know very little about but i feel like there is something there that is happening as we speak
Lately I have been busy reading some new books on Domain Driven Design (DDD) and software architecture -- including a short yet eye-opening one in Python and a great one in F#. At the same time, it seems that more people in the Functional Programming world are looking at more formal approaches to modelling -- some examples here. This has brought some thought from the background of my brain about how we should model, organize, and architect software using the lessons we've learnt from functional programming.
Before moving on, let me be clear about this being just a dump of some thoughts, not always well-defined, definite
Fibers are an abstraction over sequential computation, similar to threads but at a higher level. There are two ways to think about this model: by example, and abstractly from first principles. We'll start with the example.
(credit here is very much due to Fabio Labella, who's incredible Scala World talk describes these ideas far better than I can)
Consider the following three functions
This is inspired by https://fasterthanli.me/blog/2020/a-half-hour-to-learn-rust/
the command zig run my_code.zig will compile and immediately run your Zig
program. Each of these cells contains a zig program that you can try to run
(some of them contain compile-time errors that you can comment out to play
with)