# Blog Archive

Viewing page 1 from archive of January 2014

# When Two Packages Fight for a Name

## Pillow, the [un]friendly fork of PIL.

Many of us have had the "pleasure" of working with a pair of forked projects. Normally, this is an exercise in patience and reading code with extreme precision, but sometimes it is a whole other level of frustration.

In particular, I have spent a lot of time banging my head on FFmpeg and Libav, both of which generally provide identically named shared libraries which provide identically named exports, but are slowly diverging and offer slightly different functionality. Perhaps I am a complete n00b, but I have found it anything but easy to anticipate which one I will get when I install or later call upon anything prefixed with "ffmpeg" or "av", let alone develop code against them.

Because of that, I was very concerned when I started taking a serious look at Pillow, the self-dubbed "friendly" fork of PIL. On the surface, I am in love with the project and its call to action. However, I am afraid of the project's assumption of the "PIL" namespace, and how that will inevitably break other code in interesting ways.

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# Dictionary Building for Word-Search

## Mining Wikipedia for a "geek" lexicon.

One of the local pubs styles itself after geek/nerd culture (e.g. sci-fi, fantasy, and board games). The back of the coasters feature a word-search. It reports to contain 45 "geek words and phrases":

Writing code to solve a word-search isn't particularly tricky (if you remember to use a prefix trie) as long as you have a list of words to find, but in this case we are given no such clues.

But, since we are tremendously lazy, how can we solve this with code anyways?

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# Autocompleting Python Modules

## Simplifying the search for modules to execute from a shell.

The last few times I overhauled an execution environment I required people to execute the bulk of their tools via python -m package.module instead of python package/module.py (to enable the development environment).

The downside is that you lose shell autocompletion, which can be a big deal if you have dozens of tools that you only occasionally use.

This addition to your ~/.bashrc fixes that.

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# @classproperty

## Is this an amazing, or terrible idea?

Lets define a classproperty in Python such that it works as a property on both a class, and an instance:

class classproperty(object):

def __init__(self, func):
self.func = func

def __get__(self, obj, cls):
return self.func(cls, obj)


It can be used thusly:

class Example(object):

@classproperty
def prop(cls, obj):
return obj or cls

x = Example()
assert x.prop is x
assert Example.prop is Example


Is this a good idea, or a bad idea?

(Hint: I don't know.)

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After a concerted effort, I broke my longest streak on @GitHub. Finally, I can slack off again. http://twitter.com/mikeboers/status/402187403072270336/photo/1

@mikeboers on . Visit on Twitter.

@mikeboers on . Visit on Twitter.

# Linear RAW Conversions

## The first step when using photos in your computer graphics.

Real world photography is a fantastic and easy source of data in computer graphics and visual effects, be it for textures, backgrounds, or light maps. There is one complication that is very easy to overlook, and tricky to get right: linearity.

In real world light transport (and the simulated version of it in our various renderers) the math of light operates in a linear manner. That is, light source A with intensity 1 and light source B with intensity 1 will combine to intensity 2 (in whatever units those numbers are).

However, image capture and display devices do not work in a linear space. This is mostly historical, and maintained for backward compatibility for the content that has been produced in the past, but we must still deal with it to this day. In order to be immediately useful for 99% of cases, non-RAW image formats (as produced by your camera or the RAW converter) have the inverse curve already baked into the image so that they appear similar to the real world when viewed on a display.

It is this curve that must not be applied in order for our photography to be representative of the world (as far as the math is concerned).

I won't get into what "gamma" means, or scene-referred vs. display-referred imagery, so for an in-depth look at linear workflows see Sony Pictures Imageworks' 2012 SIGGRAPH course nodes (PDF) and this FXGuide article.

So how do we get linear output from our DSLR?

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Recently, someone broke into Adobe's network, stealing source code and part of their password database. It later turned out to affect at least 38 million people.

I always try to investigate to see if I am personally impacted by these leaks. Usually, that means submitting a carefully hashed password to some online service built to inform you if you were part of the leak. This time, however, the entire file was readily, and easily availible (by which I mean my Twitter feed included a link to it, several times).

So... why not take a peek?

\$ grep mikeboers cred


While not surprising, I am still dissapointed to be included.

Digging just a little bit deeper, there are some very troubling things in this file.