REST defines a way to design an API
with which you can consume its ressources using HTTP methods (GET, POST, etc) over URLs.
Interacting with such an API basically comes down to sending HTTP requests.
In this article, we’ll see which python modules are available to solve this problem, and which one you should use.
We’ll test all modules with this simple test case: we would like to create a new Github repository
using their RESTful API.
Tesseract is an open-source Optical Character Recognition engine, historically developped by HP and Google,
allowing you to extract text information out of images.
One of the great features of tesseract is the possibility of training it on a new language, a new set of characters,
or even on a particular font.
The training procedure is fully described here.
This prodecure is quite long and tedious. That’s why I’ve written a standalone Python wrapper that can take care of the
training process for you, in the case where you want to train tesseract on a new font, or characters.
This demo is intended for Unix/Linux users.
In this article, we are going to see a couple use-case examples of some of the Python built-in functions.
These functions can prove themselves extremely useful, and I think every Python coder should learn how to use them: they’re fast and well thought.
For each function, I will provide two snippets: one without any built-in function, and the equivalent “pythonic” snippet.
In this article, we are going to see how to scrape information from a website, in particular, from all pages with a common URL pattern. We will see how to do that with Scrapy, a very powerful, and yet simple, scraping and web-crawling framework.
I recently got introduced to virtualenv: a “tool to create isolated Python evironments”. It allows to have a fine grain control on the dependencies of each of your python project, and separate each project environment from the others.
I always forget how to precisely use ImageMagick, the documentation being so vast and operators being so numerous.
This time I wanted to blur an image, testing different blurring radiuses. This is how to do it.
My laptop can be hot sometimes, especially when I run great python calculations while I watch a movie, tweet with Hotot, chat with a couple of friends and send a couple of emails. (Hotot has nothing to do with this article, but I just think it’s a great twitter client).
I’m a social guy. Really. I love staying in touch with friends from college and high school, know what they’re up to. I really easily connect with people and love meeting new faces. I’m the typical Facebook user.
I recently joined the Strongsteam project for a 6 month internship. Our main goal is to provide some “artificial intelligence and
data mining APIs to let you pull interesting information out of images, video and audio.”
We will be doing a presentation at Pycon 2012, the 9th of March, during the Startup Row weekend.
One of the reason of the awesomness of Linux is the infinite number of nice tools you can install. It thus gives you this “feel like at home” fuzzy feeling.
Every time I use a friend’s computer, I can’t help but thinking “Man, it feels strange” : we’re using the same distro, but both our laptops provide different experiences.
I hereby present the tools that make me feel at home.
The idea of this post is to show you that if you want to implement a web-service, Python could be the way to go. The simplicity of the language syntaxis combined with some good micro-framework results into a powerful combination.
In this post, we’ll see how the program proposed in my previous post can be optimized in term of execution time. The code can be found the project GitHub repository. For those who haven’t read the first article but are interested in code optimization, i’d then advise you to read it first, to understand the causes of the problem.
If you always wanted to write texts in the way of Monty Python, I have what you need !
In this post, I am going to show you mathematical techniques to analyse a text, in order to randomly generate look-alike texts.