This post is not going to be long. It’s not going to have any examples, details, or anything of the sort. It will just teach you what Unicode is, how to use it, what an encoding is and what UTF-8 means (hint: it’s an encoding). If you sort-of, semi-understand what Unicode is, this should clarify everything.
Understanding Unicode is really simple. The first thing you need to know is that Unicode is a standard that is used for the representation and handling of most of the world’s writing systems.
Often I find that I need to include administration views in my site, such as statistics, management, etc etc. When these are more than just model CRUD views, a good idea is to extend the builtin Django admin site, as it’s the easiest to do.
While looking at the docs, however, I realised they were a bit cryptic and lacked good examples.
One of the most often requested features for historious is del.icio.us link importing, so I researched how it would be possible to add that feature.
Some of you might remember the great MongoDB saga, which ended with me migrating from MongoDB to SQLite after losing my data more often than not. After the Nth time I lost my data, I decided I had enough and decided to migrate to SQLite. I also decided not to use MongoDB for historious, as I had originally planned.
For a while now I’ve been working on my new, ultra-secret web app, and now it’s time for me to reveal it. It’s looking to address the following scenario:
Imagine that you read an article, and it’s mildly interesting. It’s not interesting enough to bother with bookmarking it (because you likely won’t read it again, and bookmarks tend to get too cluttered and linger unread), but you definitely think that the content is worth remembering.
A month later, you remember it and search for it, but with keywords such as, e.g.
As you may remember, some months ago I had decided to use MongoDB for my masters project, and had a few rather large problems with it.
These past few days I have been trying (unsuccessfully) to get Windows 7 to run in a virtual machine.
Shortly after my post about speeding up Python with Cython, I was contacted by Mark Dufour, creator of ShedSkin, a Python-to-C++ compiler, who wanted to try my code with his compiler. I had heard of ShedSkin before, but I chalked it up as something to try later, or something too hard to try (C++ is not my forte).
After Mark contacted me, I decided to give it a go on the code of the post, and, to my great, surprise, it performed a bit better than Cython with no changes to my code.
EDIT: To clarify, because people don’t seem to get it. I experienced silent data corruption, both on 1.3.3, a development version, and 1.4.0. 64-bit. Can you guys please accept that MongoDB ate my data now? Thanks.
For a bit of introduction, last year I enrolled in the Machine Learning course of the University College London, and it is now time for me to start my MSc project.
Introduction to SSL
So, say you want to buy a book on Amazon. You go on the website, pick the book you want, add it to your cart and proceed to check out. While checking out, Amazon asks you for your credit card information, you enter it and they tell you your item will be shipped soon.
You really really want to be sure that only Amazon got your data, though, because you trust them.
