Hi, did ya miss me? I’m blogging from O’Hare today, it’s going to be a busy week for me with lots of air travel. That won’t stop me from polluting the Internet with yet another blog post though, don’t you worry!
One of the things that we sometimes encounter is a binary file created by some C program writing a
struct straight to disk. If we want to get any of that data we will need to parse this file, and read that struct. It’s a little tricky, and you kinda have to know a little bit about either the system on which he program was run, or the intentional decisions made by the program about how the file was written. The most important thing you need to know is the endianness of the binary data. Continue reading Gist of the Day: C Structs from Binary Files Using Perl
I’ve been doing a lot of stuff lately with data structures and algorithms. This is one that seemed remarkably complicated to me – and still kinda does – when I started. It’s not as trivial as a binary tree mainly because there are far fewer rules. There’s a whole lot of stuff you can do with graphs, and this is by no means an advanced or complicated usage of them. This is as simple a task you can do with a graph.
The task at hand is to find all possible paths between two vertices. Continue reading Gist of the Day: Find All Paths for an Undirected Graph
Before you begin the well-deserved flaming, please understand that I do not intend on submitting this to CPAN. This is purely an academic exercise to demonstrate the algorithm (poorly), and to help me practice some stuff. I understand that this isn’t terribly efficient, and I am quite confident that one could do this much faster (and probably has many times over). I wrote this for fun, and for boredom, and I’m posting it because I thought it was cool and because I promised you I’d post stuff.
This algorithm is pretty simple. The premise is that you take a key value of some sort, you hash it using any algorithm, and then you take the mod of that hash value by the capacity of your hash table, and that gives you an index! It’s pretty simple, and even in the implementation I have here I believe it’s not a terrible look-up time.
The basic idea is this:
$array_index = hashval($key) % $array_capacity
Continue reading Gist of the Day: Re-Inventing Hashes… In Perl.
I feel really bad for leaving you all high and dry yesterday… really bad… okay, you’re right, I don’t really feel all that bad.
I have a doosey for you all today though, no doubt about it! One of the most common trends in computers these days is multi-processing. Multiple cores means one program can do more work by spawning extra threads or child processes. I’ve already done a bit of stuff with threading, so here’s a bunch of stuff with forking (tee-hee). Continue reading Gist of the Day: Process Control with fork(), exec(), and kill()
I biked a bunch tonight, and worked a bit late, and then watched Torchwood on Netflix… so, sorry for slacking.
Here’s the Gist of the Day, it’s just a simple Tree in Python with comparison. Very very simple, but I’m trying to get a better understanding of Python. I’m hoping next to implement something graph-related tomorrow. Continue reading Gist of the Day: Simple Tree in Python
Today I took on a rather ambitious Gist, and as a result the write-up is going to be rather minimal (I still have three miles that aren’t going to run themselves).
The Gist today is just a variation on the Python script I did before to load a CSV file into a MongoDB collection, but now it’s multi-threaded. Continue reading Gist of the Day: Threading in Python with All the Trimmings
Sometimes we have a simple task to do and we over-think it. Such was the case when someone asked me an interview question one time. They said, write me a quick function to prove that a provided integer ends in the number four. Instantly, without really thinking about it, bit operations popped into my head. Continue reading Gist of the Day: Ends in Four
In my post on
Inline::C a few days ago I mentioned The Rules of Optimization Club, and then I ranted a little bit about how if you cannot measure a performance problem then you don’t have a performance problem. That’s not to say that you’re incorrect in asserting that you have a performance problem, it is only to say that you cannot identify any particular part of the problem as a performance problem until you have measured it.
There a great number of ways to measure performance problems, profiling probably being the most useful in situations involving large applications where you want to test performance under real-life situations. For profiling, I would recommend you look at
Devel::NYTProf. This profiler is exceptionally feature-rich and has a boatload of useful functionality. All that said, here I’m only going to talk about bench-marking small pieces of code. Continue reading Gist of the Day: Analyzing Performance with Benchmark.pm