If you ever accidentally delete /usr/bin/emerge (happened to me when I ran emerge -aC dev-lang/python-exec), don't panic. That file is just a wrapper for /usr/lib/python-exec/python2.7/emerge. So you can fix your system by temporarily using /usr/lib/python-exec/python2.7/emerge.
Yes, it's that simple. This is also a useful way to execute pylint and pyflakes on python3 files while still having your system's default python be python2. Simply run /usr/lib/python-exec/python3.3/pyflakes (substituting whichever version of python you use instead of 3.3) and you're set. Yes, it was actually designed to work that way.
In case you want more to read, read this. In case you're more interested in playing than reading, click here.
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I just bought a beautiful new bicycle. I've been riding my previous bike for nearly a decade. It's seen some tough time and I've tried to replace it more than once but it has been the only one to survive. Perhaps it's sunny disposition has turned potential thieves hearts or perhaps its resale value (less than scrap) has never attracted them. Of course wheels, brakes, and seats have been stolen from my old bike, mostly while parked outside Kinokuniya overnight which have made the bicycle fairly expensive to keep running while I lived in the International district in Seattle. I spent a small fortune on tubes when I accidentally put presta tubes in a rim sized for schrader. Anyway, the bicycle was on the heavy side (35 lbs, 77 kg), the shocks never really worked properly besides lightening the blow from some road features, and the bottom bracket is making a terrible noise despite replacing it. If I didn't buy a new bike I suspect that it would outlast me, but since I am prepared to the point of paranoia to prevent theft of this new bicycle, I am going to recycle the old bicycle. Perhaps someone can make odds or ends of the pieces or maybe the bottom bracket problem is not as bad as it seemed. This bicycle proves that cheap bicycles can survive a long time, but also that they are as expensive as expensive bicycles when you factor in maintenance and theft. The obvious benefit of a new bicycle is weight. This bicycle is 28 lbs (62 kg), a savings of 7 lbs (15 kg). Along with the bicycle I bought clipless pedals and shoes to go with them. While this adds a few pounds (since I'll have to carry shoes) it makes up for that in spades by delivering effective power to the pedal. There is some some dispute about the value of clipless pedals but certainly practically every serious cyclist can't be wrong (and yet still we test).
So what bicycle, what mods, and what changes will I plan to make? I bought the Black Kona Dew, which is a hybrid, has no suspension, v brakes, and stock everything. I added Shimano PD-M520 clipless pedals and I plan to switch out the quick release for allen and add a nice bike computer to track my progress. I'm going to add a front light when I start riding in the dark. For now I'll just jerry-rig a flashlight if I find myself out too late or too early. No other modifications? I plan to add a few dozen grams of paint so that is isn't just black. That's right, I'm going to make it three colors. One of my favorite bicycle colors was a purple/green pearlescent but I don't want my bike to stand out as much as that. Instead, I will be trying to make it a little less flat. I'm normally fine with matte black but there's something about a black bicycle. You can track the bicycle's progress here: Bike index link. Unless something bad happens, the page should just be a brief description of the bike with maybe a photo.
Cycling is for many people a recreation but for me it is a mode of transportation from one place to another. This bicycle isn't supposed to get me in shape, but I suppose it will. This bicycle isn't supposed to be a fast mode of transport in case of emergency, but it can be that. This bicycle isn't supposed to make it so I can spend time with friends away from civilization because getting away from civilization without a car isn't something a person can do very easily. Not just here, anywhere. The furthest from civilization you can get without a car anywhere is how far you can ride minus your current depth in civilization, so a place like Seattle which is very deep in civilization might not be possible to reach nature. For example, riding from Seattle Ferry Terminal to Falls View Campground in Olympic National Forest is a 42.6 mile ride with a huge elevation change. Though it would probably take 10 hours, it would be possible for me in my current shape. Without the elevation change, this was cake for 16-year-old me, riding 80 miles per day for 4 days in a row on a well-tuned mountain bike (yes, with shocks) was not a big problem.
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This blog post is a quick video with some backup data for my Small Wide World project.
Welcome to a quick update for Small Wide World. Progress on this project is moving rapidly so I just like to let you know what's going on and how awesome it is. The first improvement you've probably noticed on the website is better looking graphs all over it. That's a good sign that things are improving but that's just showing you the interesting improvements that can be made with a little bit of code. Today I wrote this code I'm going to show you. Here you see a two-node graph with a and b. It's the simplest you can get. You can see that we've added a new node onto a here. So now we have a three node network. And then you see it's the same network c-a-b and we've connected that via a to d. You can see that even though it looks different, we still have c-a-b and d and we've just connected e to a. This is a self-organizing network. It's actually very fast, it uses very few operations so it's going to become the default algorithm for the web, Python, C, and all versions. They will use this algorithm to make the initial pattern. It doesn't work perfectly for all types of graphs, but it works especially well for these types of graphs: graphs which aren't cyclic and are using lots of branches. See that we add g to b. See the angle between g-b-a, g-b-f, and a-b-f are all the same and the length of all the bonds are the same. This is a very easy technique that shows a graph effectively. This makes it so that you can understand the graph more quickly — or at least that is the idea. We've added h, we've added i, we've added j, and k. Then you see we've added l to d, so in order to make a-d-i, i-d-l, and l-d-a equal angles we turned d-i-k sideways. This is just another one rotated because we've added m to a here. You can see n added, we're getting close to where nodes start to overlap with each other. That's one limitation of this algorithm, but I can pretty confidently say that solving that is a job for a more expensive algorithm, for example global optimization. Once this algorithm has finished you can run a global optimization algorithm on it and it will have better success than just a random graph. You can see that k, h, and c are a little crowded, so an optimization algorithm would push these away from each other because k and h are too close to one another. We're almost to the point where it's going to fail. And here we see that it fails with c-h overlapping p-q and c-s overlapping i-k. In order to fix that, an optimization algorithm would only have to move p and q down and i and k up. How much computation does that require? Local minimization algorithms would probably be able to do this in a few million operations (less than a second but far more than this algorithm takes), but if they couldn't properly solve the collision, you'd have to use a global optimization algorithm like basin-hopping or Monte-Carlo Metropolis to finish the job. This could take seconds or even minutes. Small Wide World currently implements basin-hopping using SciPy which I will be testing thoroughly against graphs like these.
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