In order of first appearance in The Morning Paper.
It's been often said that programming is part art, part science - that because lots of times there's no single, simple solution to a problem; or if there is, we might not know about it. There's also an infamous joke that if there are n developers in the room, then there are n+1 opinions on how things should be done. That being said, here are some guidelines that should prevent friction when submitting or reviewing code.
The code has to work. Unless you open a PR as a work in progress, the code should be built and tested on a device or emulator.
If you have touched the gradle build files and changed build setup, it's useful to test the whole build from scratch (clean build) and all of the types and flavours. If you have touched payments (logic or UI), you should test that it still works correctly, both in test and production builds. If you updated external libraries, test the pertaining features (e.g. if you
Concurrency is a domain I have wanted to explore for a long time because the locks and the race conditions have always intimidated me. I recall somebody suggesting concurrency patterns in golang because they said "you share the data and not the variables".
Amused by that, I searched for "concurrency in golang" and bumped into this awesome slide by Rob Pike: https://talks.golang.org/2012/waza.slide#1 which does a great job of explaining channels, concurrency patterns and a mini-architecture of load-balancer (also explains the above one-liner).
Let's dig in:
This guide has moved to a GitHub repository to enable collaboration and community input via pull-requests.
https://github.com/alexellis/k8s-on-raspbian
Alex
The following are examples of the four types rate limiters discussed in the accompanying blog post. In the examples below I've used pseudocode-like Ruby, so if you're unfamiliar with Ruby you should be able to easily translate this approach to other languages. Complete examples in Ruby are also provided later in this gist.
In most cases you'll want all these examples to be classes, but I've used simple functions here to keep the code samples brief.
This uses a basic token bucket algorithm and relies on the fact that Redis scripts execute atomically. No other operations can run between fetching the count and writing the new count.
I screwed up using git ("git checkout --" on the wrong file) and managed to delete the code I had just written... but it was still running in a process in a docker container. Here's how I got it back, using https://pypi.python.org/pypi/pyrasite/ and https://pypi.python.org/pypi/uncompyle6
apt-get update && apt-get install gdb
#!/usr/bin/perl | |
use warnings; | |
use strict; | |
my $bin=$ARGV[0]; | |
my @line = split /\s+/, `nm $bin |grep runtime.buildVersion`; | |
my $addr = hex($line[0]); | |
my $end = $addr + 16; |
FWIW: I (@rondy) am not the creator of the content shared here, which is an excerpt from Edmond Lau's book. I simply copied and pasted it from another location and saved it as a personal note, before it gained popularity on news.ycombinator.com. Unfortunately, I cannot recall the exact origin of the original source, nor was I able to find the author's name, so I am can't provide the appropriate credits.
- By Edmond Lau
- Highly Recommended 👍
- http://www.theeffectiveengineer.com/
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