2016-01-18
Infection is a sandbox contagion simulator I recently started working on. It
is an entertaining game that anyone with a basic understanding of JavaScript
should be able to hack.
A simple set of rules and values govern how an infection spreads in a square
board of 400 tiles. In the future, different challenges should be made
available.
It is hosted at GitHub and
released under the MIT license.
You can find an online version of the project
here.
2016-01-10
Even though this feature is not new at all, very few seem to use
generators as much as they should. Generators may help one write
programs that require less memory to run when compared to their list
comprehension analogous.
Let me use a trivial example to demonstrate the difference. Real-world
examples may involve more complicated number crunching but will have
a very similar structure and also present the same improvements.
Problem: determine the sum of the first ten thousand perfect squares
Solution using list comprehension
sum([n ** n for n in range(10 ** 4)])
Solution using a generator
sum((n ** n for n in range(10 ** 4)))
In this case, refactoring is very simple, but usually you would have
the list comprehension result assigned to a variable and used later on.
It’s up to the developer to spot scenarios where a list comprehension
may be replaced by a generator.
The list, in its entirety, takes 79.28 MiB on my machine, whilst the
bigger value produced by the generator takes only 17.33 KiB. As you
would expect, the results are identical.
Determining the size of a list in memory
If you don’t know about it yet, there is a nice tool called pympler that
allows you to measure the memory size of collections. See the snippet
below.
from pympler.asizeof import asizeof
print(asizeof(list_of_perfect_squares)) # 84 134 440 -> 79.28 MiB
2016-01-05
This is an announcement of a Java image manipulation library I created.
It is released under BSD 2-Clause and can be found here. The main reason for
creating it was that there was not an open source Directional Cubic Convolution
Interpolation implementation out there in Java.
According to Wikipedia,
An article
from 2013 compared the four algorithms above, and found that DCCI had the
best scores in PSNR and SSIM on a series of test images.
There is also a dedicated page for this library here.
A Maven artifact is on its way. If you have any suggestions or requests, send
me an email or create a new issue.
2016-01-02
It may happen that you have a remote to which you have push rights but will
never want to push. If you are afraid of pushing your changes to it by accident
or just want to play it safe, this command may be of assistance:
git remote set-url upstream --push disallowed
This makes the push url of the upstream
remote (use whatever name your remote
has) an invalid address that will prevent accidental pushes.
2015-11-26
This post is a collection of highlights from this fantastic
article about what
every computer science major should know by Matt Might.
Portfolio over Resume
A resume says nothing of a programmer’s ability.
Every computer science major should build a portfolio.
Communication
Modern computer scientists must practice persuasively and clearly
communicating their ideas to non-programmers.
Unix
Given the prevalence of Unix systems, computer scientists today should be
fluent in basic Unix.
Programming Languages
While it is important to teach languages relevant to employers, it is equally
important that students learn how to teach themselves new languages.
The best way to learn how to learn programming languages is to learn multiple
programming languages and programming paradigms.
Mathematics
Computer scientists must be fluent in formal mathematical notation, and in
reasoning rigorously about the basic discrete structures: sets, tuples,
sequences, functions and power sets.
User Experience
Programmers too often write software for other programmers, or worse, for
themselves.
User interface design (or more broadly, user experience design) might be the
most underappreciated aspect of computer science.
Databases
It’s useful to understand the fundamental data structures and algorithms that
power a database engine, since programmers often enough reimplement a database
system within a larger software system.
There is more
There is much more than this on the original post. It is also supposedly an
alive post, so you should definitely check it out from time to time. There is
also some really nice stuff about which languages the author thinks provide a
reasonable mixture of paradigms and practical applications that I did not quote
because it is fairly long.