#Intro
Kotlin is a new programming language for the JVM. It produces Java bytecode, supports Android and generates JavaScript. The latest version of the language is Kotlin M5.3
Kotlin project website is at kotlin.jetbrains.org.
All the codes here can be copied and run on Kotlin online editor.
Let's get started.
| # to generate your dhparam.pem file, run in the terminal | |
| openssl dhparam -out /etc/nginx/ssl/dhparam.pem 2048 |
Copied from https://github.com/sindresorhus/guides/blob/master/how-not-to-rm-yourself.md
The rm command is inherently dangerous and should not be used directly. It can at worst let you accidentally remove everything. Here's how you can protect you from yourself.
The trash command-line tool will move stuff to the trash instead of permanently deleting it. You should not alias rm to trash as it will break external scripts relaying on the behavior of rm. Instead use it directly: trash image.jpg.
RDBMS-based job queues have been criticized recently for being unable to handle heavy loads. And they deserve it, to some extent, because the queries used to safely lock a job have been pretty hairy. SELECT FOR UPDATE followed by an UPDATE works fine at first, but then you add more workers, and each is trying to SELECT FOR UPDATE the same row (and maybe throwing NOWAIT in there, then catching the errors and retrying), and things slow down.
On top of that, they have to actually update the row to mark it as locked, so the rest of your workers are sitting there waiting while one of them propagates its lock to disk (and the disks of however many servers you're replicating to). QueueClassic got some mileage out of the novel idea of randomly picking a row near the front of the queue to lock, but I can't still seem to get more than an an extra few hundred jobs per second out of it under heavy load.
So, many developers have started going straight t
For this configuration you can use web server you like, i decided, because i work mostly with it to use nginx.
Generally, properly configured nginx can handle up to 400K to 500K requests per second (clustered), most what i saw is 50K to 80K (non-clustered) requests per second and 30% CPU load, course, this was 2 x Intel Xeon with HyperThreading enabled, but it can work without problem on slower machines.
You must understand that this config is used in testing environment and not in production so you will need to find a way to implement most of those features best possible for your servers.
| #!/bin/bash | |
| # This gist contains pre-commit hooks to prevent you from commiting bad code or to the wrong branch. | |
| # There are six variants that I have built: | |
| # - pre-commit: stops commits to master/main/develop branches. | |
| # - pre-commit-2: also includes a core.whitespace check. | |
| # - pre-commit-3: the core.whitespace check and an EOF-newline-check. | |
| # - pre-commit-4: only the core.whitespace check. | |
| # - pre-commit-5: elixir formatting check. | |
| # - pre-commit-6: prettier formatting check. | |
| # Set the desired version like this before proceeding: |
Example /etc/nginx/nginx.conf using FastCGI (e.g. to PHP-FPM) with FastCGI cache enabled. This will capture returned data and persist it to a disk based cache store for a configurable amount of time, great for robust full page caching.
Will need to create a directory to hold cache files, for the example given here that would be:
$ sudo mkdir -p /var/cache/nginxfastcgi
$ chown www-data: /var/cache/nginxfastcgi
(by @andrestaltz)
If you prefer to watch video tutorials with live-coding, then check out this series I recorded with the same contents as in this article: Egghead.io - Introduction to Reactive Programming.