Lower the Barrier for Scratching Open Source Itches!

Ok, this is an idea I've had for some time now, I think it's time to put it out there and see what a large audience thinks. I'm a bit ignorant about how distributions are set up, maybe it's just impractical for some reason I'm unaware of.

I think there should be an easy way for users of a distro to jump right into development. This stuff is done for free, we need all the help we can get. It would help to eliminate any barriers to entry we can. My proposal is that it should be integrated into the package manager.

Here is the process I envision: I, the user with coding skills, have an itch with Program X. I issue one command, let's say "sudo apt-get --collab programx". Here's what it does:

• It automatically creates a fork of the project on my account on Github (or equivalent)
• It pulls, via Git (or equivalent), the very version of Program X that I am running currently. Now, this is important because I don't want to worry about different behavior in the program, I don't want to deal with a newer version of the program requiring different versions of libraries. I want the same thing I just ran, with the same bug, and I want the source code that generates it.

• The build environment is all set up. I don't want to hunt for build dependencies, compiler options, etc. Enough said. "apt-get -b" Seems to do most of what I described thus far, minus the crutial Git part.

• I fix my problem. I make my changes, commit, and push. It shows up on upstream's Github fork queue (or equivalent). They decide whether to accept it.

Github has already done a great part of this, compared to a few years ago, by lowering the barrier to entry with the fork queue. Install via source already exists in apt. Would it be a huge task to coordinate the two?

I think that I would probably have scratched a few itches by now if it were this straightforward. Instead, I have to look up the specific build setup for the project (on the project's site, not Ubuntu's site), figure out build dependencies, etc. Or, I can do apt-get -b, but then it's not ready to commit my changes back (afaik).

The limit of my patience, and free time, is reached much earlier in the process as things currently stand. Remember, this is for people who are perhaps a few levels less involved than the sort of user who would run the bleeding edge Ubuntu Beta. This is a regular user with some coding skills, who might be able to fix a problem or two if the setup were handed to them. They have a different mentality. This is about getting a new class of developers involved.

Again, I'm ignorant about the details of package management and open source project management, so I'm probably leaving holes in this idea that I don't know about. I'm just a developer with an idea. The question is, can these holes be ironed out, or does this have a fundamental problem because of package management, as it stands today?

Or does this already exist and I just never heard of it? (in which case, it should just be promoted more!)

I found the perfect project to dive into Haskell

I've had a recurring project in my life, a modular software synth. See here to get an idea of what I'm doing. The difference being that with software synths, you're not limited to how many components you have and how they're configured. I somehow thought I came to this revelation on my own years ago, but there's plenty of this sort of thing out there, such as SuperCollider, which sounds like it's fairly popular.

I've been trying to get into Haskell, but have been struggling to get myself out of my Python comfort zone. A friend of mine actually told me about SuperCollider recently, and I realized that my own synth would be the perfect project to get me started on Haskell, and one day last week I got inspired to get started. I found a simple example to start with of a sine wave being played through Pulse Audio and I went from there. Here's my repo

Unfortunately, you need PulseAudio to run this. I'm working on either getting Alsa output or file generation working soon.

When I was making this a few times before, I made it in C++, the latest instance being several years ago. Amazingly enough, despite still being a novice in the language, I found that doing this in Haskell is easier. The infinite lazy lists work perfectly as signals. Before I considered each component to be an object that had a value, and input signals. And I had to have a global "tick" that conveyed info between items. (And I thought that was really neat at the time.) Now I just have components be functions that "output" (return) infinite lists, and take infinite lists as inputs. It all sortof just sorts itself out.

Speed is sacrificed to be sure, at least so far, but real-time synths have been made for Haskell, so I bet I can profile it and optimize it significantly.

Also you will notice that everything is hard coded! I sortof like it that way, it's amusing, particularly when it starts making beat sequences (which is a point I got to in my old version), but I'll probably make an interface at some point. Or maybe not, Haskell is a nice interface.

Here's why I'm writing now of all times though. On top of being functional with the lazy infinite lists and such, Haskell also has a type system from Nazi Germany. This is actually an advantage, though. I have some trouble remembering all the unit conversions involved in the oscillators, when I'm dealing with cycles, seconds, and samples. So today, I made a type framework that provided functions that did the conversions properly. When I was writing out an improved version of my oscillator function, I used these types.

It took me a long time to figure out exactly how I wanted it all to work, and how to make it work. I would start on an expression, and then realize that I was adding different units, and Haskell wouldn't let me do it. Or sometimes the compiler told me so. But eventually I got through it. This is the monstrosity that resulted.

And the kicker: I used this to make a new version of the square wave oscillator, and it sounded exactly the same as the old one, the first time I ran it.

Testing Multiple Login Sessions Simultaneously

One annoyance in developing websites is that you sometimes have to log in and out all the time to test interaction between multiple users.

Have you ever visited or administered a website (say, www.example.com) which lets you visit "www.example.com" or "www2.example.com", etc, and doesn't forward to "example.com"? Did you ever try logging in at one subdomain, and then switch to another? You'll be logged out, it's a different login session. If you needed to test something remotely with multiple users logging in at once, that's a nice trick to use.

Now let's do the same thing locally (*nix systems only afaik, sorry):

In /etc/hosts you should see:

127.0.0.1 localhost

Add the following:

127.0.0.1 localhost2
127.0.0.1 localhost3
127.0.0.1 localhost4

And so on for however many you need. Now each one will access your site with a different session, so you can log in as a different user for each.

Cryptonomicon: A Lesson for my Hyper-Logical Friends

I'm currently reading Cryptonomicon by Neil Stephenson. I'm not very acquainted with literature at large, so forgive me if I'm being ignorant here, but it seems that this book is unique or among very few that are in wide release and yet somewhat esoteric. That is to say, anybody can appreciate it, but I think it speaks specifically to computer programmers and mathematicians, and may not be 100% understood by those who are unfamiliar with certain mathematical and engineering concepts, and who don't share that mentality. Then again, the purpose could be to provide some insight to outsiders who may want to understand the hyper-logical nerd mentality. Tom Wolfe seems to do a similar thing, for instance, with the investment bankers in Bonfire of the Vanities.

Though I think Neil Stephenson must have a closer personal connection with this mentality. It's a great book for a nerd because it's literature we can really relate to. It's told from the perspective of those of us who try to make logical sense of everything, see patterns all around us, and are confused by strange things like social niceties.

All in all I think it teaches an important lesson to nerds and non-nerds alike. I only just now crossed the 1/3 way mark (it's like 1100 pages), but I just came across some particular dialog which I think is particularly insightful. In this scene, Randy Waterhouse pulls Eberhard Föhr aside during a business meeting, and explains to him why, for their own legal protection, information has been withheld from them by one of their business partners, Avi. Ebehard, being of this nerd mindset, is frustrated that his business partners are not behaving logically. Randy, being of the same mindset but somewhat more enlightened, explains to Ebehard the realities of dealing with illogical people, but he does so in logical terms that Ebehard can relate to. This conversation is amusing like a lot of things in this book, because it demonstrates how us analytical types like to deconstruct everything.

Rather than risk inviting Neil Stephenson's lawyers (I have no idea how likely a scenario this is be but I don't care to do the research right now) I'll just invite you to read this page via Google Books.

I appreciate a couple things about this passage. Firstly, I appreciate that Randy's character is sort of an enlightened techie, who we should aspire to, who respects the qualities of other sorts of people, even if he doesn't understand their mentality. Business people clueless about technology, idealistic designers with a vision, techies who can't design a usable interface to save their life, we should all accept our own limitations of understanding, respect the others, and occasionally yield our own ideals for the sake of other ones. (ex: if "doing it right" means taking twice as long, and failing in the market, what use is your ideally laid out code if nobody's going to use it?)

The other thing I like about this passage is, as I mentioned above, the logical way that it approaches illogical people. Some nerds have a tendency to refuse to approach the world in anything other than a logical manner. Normal People may try to explain to them that the world, particularly other individuals, aren't rational at all, and we should stop seeing things so logically. I include myself in this group of nerds, so honestly, this line of argument is ridiculous to me. The universe is logical. But, I think that sometimes we as nerds are just Doing It Wrong, and we can take a cue from Randy here.

What we need to do is to appreciate that the fact that people act irrationally, out of emotion, is just a condition of the world. Just as we accept that animals are irrational, or that the sun is hot. It's a datum. Further, accept that you yourself, the nerd, are also emotional, particularly when people don't act logically. This frustration with others' illogical behavior is based on an expectation for people to act contrary to their nature. You're ignoring a data point. You're mad at the sun for being hot. You're a non-techie who's mad at your computer for doing something other than exactly what you told it to. Now look who is being irrational? I'm going to agitate a little and propose that we are in fact being hypocritical here.

The main problem I think we sometimes have is the distinction between Logic and Logical Faculties. The expectation of perfection in Logic is not the same as expecting a human to have perfect Logical Faculties. The universe works by rational laws. People are part of the universe, so their workings are rationally explainable. But this is entirely distinct from their Logical Faculties being able to perfectly model the world around them. Furthermore, people's Logical Faculties being able to model the world around them is distinct from their ability to defend it from any of their Emotional Faculties getting in the way. We humans are but animals who happen to possess a limited amount of logical faculties.

Expecting people to act in a rational straightforward manner is like expecting a computer to compute beyond its capacity. A problem may be Logically solvable. There is a perfect Logical progression toward the answer. If we treated computers the same way we sometimes treat other humans, we would demand that we should be able to stick the problem into a computer and get an instant output. But again, Logical Faculties are in limited supply. Somehow we don't seem to have a problem accepting this in computers. In fact, we have entire sub-fields of computer science, taking RAM, HD, and time limitations as data, and creating a whole new set of Logical problems. Why not accept the same limitations and challenges in humans?

Perhaps it's that there is one fundamental difference between computers and humans, which is that our departure from being perfect logic solvers is not just in our processing capabilities, but also, as Randy pointed out in the passage linked above, in our interfaces. Human interfaces are more like neural networks than serial connections. To gain access to the Logical Faculties, one must enter a pattern that is accepted by the neural network. The patterns include such things as social niceties and innuendo. Some of us have simpler interfaces than others. (And as Randy described, some may even require other humans to act as intermediate interfaces. When I worked at Oracle, there was a guy who was fluent in both Engineer and Customer, and intermediated all conversation. I understand this is a common thing to have in a company.)

And you, the nerd, are a neural network, at your core, not a Turing machine. You operate in that domain. That means you have the natural ability, however impaired by years sitting in front of the computer, to interface with other neural networks, if you would just accept your nature. This is in fact the only way you can communicate with other humans, so you might as well accept it for what it is. You may try to approximate a Turing machine, but your neural network nature will still show on occasion. For instance, as I pointed out above, when you are frustrated about others not behaving like Turing machines.

allCombinations: leaveOut

leaveOut

Ok, on my previous post I brought up a small Python module I was inspired to throw together while writing tests. It's still sitting in a gist, though I'll probably move it to a real repo before too long:

https://gist.github.com/674715

So I admit, as I was posting it, it occurred to me that to a large extent this stuff could be replaced with a nested for loop. For instance, this:

for lst in allCombinations([1, 2, oneOf(3,4), oneOf(5,6)]):

can be pulled off with:

for x in (3, 4):
for y in (5, 6):
   lst = [1, 2, x, y]

Not a huge gain necessarily on my part. So as I was using it in my testing I realized I once again had engineered something for a tiny use that, neat as it is, could have been done much faster by brute force. But then, I realized another thing I could add that would make my code much more concise. I've added another keyword called "leaveOut". It lets you opt to not have the element show up at all. Here's an example:

allCombinations([1,2, oneOf(3, leaveOut), oneOf(4, leaveOut)])

This will return:

[ [1, 2, 3, 4], [1, 2, 3], [1, 2, 4], [1, 2] ]

And of course, the "leaveOut" case will omit dictionary entries and object data members as well.

BTW

I should also mention another use case I thought of, "leaveOut" aside, that might be a real pain to do without an aide such as allCombinations, which is dynamically created structures, with an arbitrary amount of variables:

allCombinations( [ oneOf(1, 2) ] * x )

I've just generated all possible lists of either 1 or 2, of an arbitrary length, which can be set at runtime. Or how about something a bit more fun:

allCombinations( [ oneOf( *range(y) + [leaveOut] ) for y in range(x) ] )

Taking all combinations of lists of length x, where each element can equal any integer from zero to its index, and then adding combinations where items are omitted. Not horribly useful, but complicated.

To do these in a standard way you'd need x for loops, which you can't do directly. (I bet you could do it with recursion).

Fixes

I'll also mentione that I fixed a couple general errors. oneOf on Data members had a big bug. And now if you don't have oneOf in your structure, allCombinations just returns a list containing only the original structure, instead of looping to death.

allcombinations - generating combinations of python structures

Alright, on a whim I decided to make another tricky thing in Python. This one is less of a hack, and is more likely to be useful.

So let's say you want to do something with all combinations of... something.

[5, 6, oneOf(7,8,9), oneOf(10, 11, "shazaam")]

So you want to turn this structure into all the possibilities represented within:

[
[5, 6, 7, 10],
[5, 6, 7, 11],
[5, 6, 7, "shazaam"],
[5, 6, 8, 10],
[5, 6, 8, 11],
[5, 6, 8, "shazaam"],
[5, 6, 9, 10],
[5, 6, 9, 11],
[5, 6, 9, "shazaam"],
]

Well with allcombinations, you can do just that:

from allcombinations import allCombinations

allCombinations( [5, 6, oneOf(7,8,9), oneOf(10, 11, 12)] )

Here it is. The gist includes more complicated example.

Features
The oneOf should be able to reside almost anywhere in your expression. It can be in a list (as seen here), in a dict, or even in the attribute of an object. It can also reside in a list within a dict within an object's attribute, etc, as long as it's nowhere within an unsupported container type.

Limitations:
This will only work if oneOf resides in a list, dict, or an object's attributes. It shouldn't work anywhere within a set, or any other structure I can't think of. If you try it in something unsupported, the oneOf object should just stick around in all your combinations.

I'm probably actually going to use this, particularly (again) for testing. Anyone else think they'd find it useful? Should I package it?

Testing (Django) views with pyquery

PyQuery is basically what it sounds like. Using jQuery syntax, you can query and even manipulate XML files. Obviously we don't (yet!) have Python in the browser, so it's not useful in the same domain, but it can help out in dealing with XML in general, in the same way as, say, lxml, but without having to learn about things like ElementTree for simple cases. It's particularly good for XHTML because jQuery (and thus PyQuery) uses CSS syntax for class= and id=. Which brings me to how I'm using it:

from django.test.client import Client
from pyquery import PyQuery
from django.test.testcases import TestCase

...

class TestSomeViews(TestCase):

   def testAView(self):

       client = Client()

       ...

       response = client.get("/someurl/")

       self.assertTrue("expected text" in PyQuery(response.content)("#someid").html() )

(If you're unfamiliar with testing Django views, see this.)

For some basic tests, you can just search the entire response html, and not have to worry about where it shows up. But suppose you're searching for a username in a particular part of your response. You're pretty likely to find that username elsewhere on the page, so you have to select out the part of the file you expect it. I think this is much easier than using a regex.

So what this bit of PyQuery does is find the tag with the id of "someid" (presumably there's only only one, being an id), and returns the html within that tag. (If you search for a class that returns multiple tags, it seems that a simple call to .html() will only return the contents of the first one. This very well may match jQuery's behavior, I'm admittedly not that familiar, but just a head's up.) For more details look at the PyQuery API.