There will be a Galcon Tournament at PyCon on Saturday night from 8:00pm – 11:00pm in Ballroom II.

Galcon is an awesome high-paced multi-player galactic action-strategy game. You send swarms of ships from planet to planet to take over the galaxy.

Feel free to come even if you don’t have a Galcon license – they will be provided 🙂 It’ll be a great time to hang out and play one of the top 10 indie games of 2007 – built with python and pygame, of course!

Hope to see you there! If anyone wants to talk game development or Galcon or whatever, just look for the guy wearing a Galcon t-shirt 🙂

P.S. Just to be on the safe side, try to download and install Galcon well before the tourney so we don’t swamp the conference network.

I’m going to pycon next week, yah!  I’m planning on sprinting on PyGame on Flash.  However, if someone wants to sprint on tinypy, just find me and let’s talk!  There are loads of cool things that could be done:

• JIT
• improved bytecode generation
• LLVM or luavm backend
• add your favorite module
• that module could be pygame 🙂
• speed improvement
• general code review
• bug fixes / tests
• documentation
• ???

Hope to see you at pycon!  I’ll be wearing Galcon t-shirts all week, so I shouldn’t be too hard to find.  🙂

Its been a long two months getting this project to the 1.0 state. Here it is:

tinypy1.zip | tinypy.tgz | svn://www.imitationpickles.org/tinypy/tags/1.0.0

$ python build.py
$ ./tinypy-sdl julia.py *
$ ./tinypy your-program-goes-here.py

The win32.zip includes the tinypy.exe and tinypy-sdl.exe binaries, so you can skip the building process.

Features include the ability to parse and compile to bytecode a pretty decent subset of python code. Its got a pretty simple API, incremental garbage collection, and a handful of builtin functions. The vm supports strings, dicts, lists, numbers, functions, methods, and custom data types. tinypy even has exotic features like list comprehensions, variable and named function arguments, inheritance, and exceptions with tracebacks. All this in just 64k** of code!!

I also had some fun this past weekend testing tinypy “in the field” making an OpenGL tetris knock-off. My apologies to Alexey Pajitnov for my misguided contribution of tinypy to the open source stack. win32.zip | svn://www.imitationpickles.org/ld105/trunk

I hope you enjoy checking out tinypy – I’ve had a pretty wild ride building it.

*julia.py included is a low-res “realtime” jula fractal demo. I felt like rendering a mandelbrot for this article.

**See README.txt for my definition of 64k. It’s close enough.

Updates – I’ve got it all fitting in 64k*. It’s amazing how many functions that don’t do anything you can come across if you look around long enough. Not to mention how many little things you can trim out that don’t actually do anything. I have no idea where all this cruft comes from, but having a nice suite of tests sure is helpful for re-working stuff. I also cut out a bunch of stupid features nobody would ever use**. I was able to reduce the number of native types from 9 to 7.

One of the challenges I faced was trying to fix up the incremental garbage collection. My initial implementation was rather inefficient and caused some odd problems with how I wanted to code things. I was using a dict to store all the “white” items, which caused loads of dict hash lookups.

So in my mind I crafted a grand vision on how to accomplish this goal. I would adjust all objects (sans numbers) to contain a pointer to some data which would have some header data for the GC to do some bookkeeping in. Great! However, when I implemented this, I found that a number of problems presented themselves: I had to perform a malloc for each and every string that I used, which killed performance, actually making things 2-3x slower. I also noticed that the weird struct I defined was maybe a bit less standards compliant. This attempt was a wash.

So I re-crafted my grand vision. This time I would do the same thing. Brilliant aren’t I? Anyway, the results were basically the same. Who’d’ve thunk? It was slower again, this time I was quite confused by it, since I had worked around some of the string issues. I also found that the API for creating new strings wasn’t quite as “clean” as my original simple one. This caused some issues in the exception handling mechanism. I had to toss this try as well.

At this point, having re-mangled the code twice and having poor results, I suspected something else might be wrong. My brain was turning into mush. Each time I had completely edited my “tp.h” with all my struct changes in one go. I decided to make a final attempt at reworking tinypy, this time *one* data type at a time. After each data type I added I was able to see if my changes caused any performance issues. I found that my function data type was the culprit. My hashing function (borrowed from lua) wasn’t getting enough entropy and was generating massive collision cases! A few tweaks later, this was resolved. I was able to also craft the string interface to be backwards compatible with the original string interface while also working with the new garbage collection. This “step by step” approach got me to my goal. All said and done, with a bit more tweaking, I was able to *double* the speed of tinypy 🙂

Lesson learned – even if it’s only 64k, it’s better to do changes step by step instead of in one big go. valgrind and callgrind are your friends. (Although I found that tinypy doesn’t entirely agree with callgrind … ideas anyone?)

To wrap up this excessively long post about me trying to get code to work — this weekend I’m hosting a Ludum Dare warmup compo. I’m going to give tinypy a run in the “real world”. Here’s to hoping! Next week I plan on releasing the 1.0 version of tinypy.

I’m also thinking about renaming some of my files. And although pylang, dumbparse, and dump2vm have a certain rustic charm, I wonder if I’d do better with names like goat, gorilla, and sausage. Or maybe more descriptive names like tokenator, parsalizer, and bytecodatron.

svn://www.imitationpickles.org/tinypy/trunk for the brave. If you want a zip or an exe, check back in a week. I’ll have all those and more (a game!) Note that I’ve split the SDL dependency out of the main tinypy code. tinypy-sdl.c lets you run my julia.py example. The bootstrapping process also has a final step of compiling with -O3, which I think might not work for everyone. It gives pretty good speed gains on my system, so if it works for you, great!

*python mk64k.py will do a bit of search-n-replace to cut it down to size. I’ve resisted doing anything really ghastly, the code is still indented and readable. See README.txt for more disgusting details on how I cheat to pretend this is 64k.

**Okay, I’ve used some of those features. But hey, this is a 64k implementation, I’ve got to trim the fat.

Yay – I got incremental garbage collection added into tinypy. It took a good deal of troubleshooting, but thanks to valgrind (and thanks to the people who pointed me to it) after some work I got all the memory leaks and crashes worked out. This is a nice step forward, since it enabled me to eliminate the libgc dependency.

tinypy is slightly larger than 64k, but I have vague hopes that will be remedied* at some point. In the meantime, I’m going to take a bit of a break from it. On Feb. 23rd, the Ludum Dare community is having a “warm-up” compo, and I shall give tinypy a real try at that point. After that I will probably put out the 1.0 release.

All that said, its been quite a learning experience for me. I learned how to tokenize, parse, generate byte code, build a virtual machine, and do garbage collection. I’m hoping this will make looking at the innards of other languages seem less intimidating in the future.

* if you’re a clever C / python coder and feel like taking a look at the tinypy code and give me ideas on how to compact the code a bit, I’d sure appreciate it. It’s 4k too big right now, and I’d really like to fix that. I’m cool with any suggestions though I won’t implement anything unless it leaves the code just as (if not more) readable. Please examine the README.txt to find out how I calculate the code size first.

svn://www.imitationpickles.org/tinypy/trunk or tinypy.zip for the brave. I’ve managed to compile it under mingw32 (Minimalist GCC for windows) as well as using GCC under MacOSX. Perhaps for the 1.0 release I’ll include binaries 🙂

For giggles I tried to write a garbage collector to replace libgc in tinypy. I tried doing a tri-color incremental collector. I couldn’t get it to work, so I ended up switching it to be more of a tri-color mark and sweep collector.

The result of my mark and sweep collector was a 40% reduction in speed. I’m guessing ol’ libgc was designed with a bit more cleverness than mine 😉 Anyway, for now I’ve moved my “tgc” development into a branch of tinypy svn://www.imitationpickles.org/tinypy/branches/tgc if you want to see it in action.

Stuff to read: Memory Management Reference and libgc.

So.. hey, it’s done. Basically. tinypy is a 64k implementation of a subset of python. It can bootstrap itself into a single executable that can compile python files to bytecode and run them on a VM. Thanks to everyone who gave feedback thus far on this project. Double thanks to allefant who listened to me blab about it endlessly on irc for the last month 🙂

I found all the stuff people told me about for parsing was a huge help. This article http://javascript.crockford.com/tdop/tdop.html was what I ended basing it on. It’s almost like magic, but it makes for a really simple easy to follow parser. The VM is based on stuff I read about the lua VM.

So what’s next? I need to let it sit around for a week and then I’ll do a “release” I guess. I’ve gotta pick a license or something for it (probably MIT? I’m open for suggestions.) I’m also mulling over possible names. Maybe “tinypy” .. or “wedge” .. or “cupcake” .. or “garter”. Hmmn.

Anyway – I’m sure I’ll be tweaking it a bit over time, but I’m pretty happy to have it to this point now. I probably won’t do much with it until I try making a game with it. Right now it depends on libgc for garbage collection. If someone clever out there can implement a garbage collector for it that works in like 2-4k, that’d be better. My brain is pretty spent.

For the brave: svn://www.imitationpickles.org/tinypy/trunk or tinypy.zip. The following is only tested under linux, but I bet it would work in any bash environment. Maybe.

$ python boot.py

Will run the 3-phase testing + bootstrapping process. It will first use python to generate the .tpc files for the compiler. Second phase uses the VM to generate those same files. Third phase uses the bootstrapped tinypy executable to “re-bootstrap” tinypy to get the final version. The -nopos option strips out debug info from the .tpc files.

$ ./tinypy julia.py

Run the julia demo without dependence on *anything* but the tinypy executable.

$ ./tinypy your_own_code.py

Will do something! Probably print out a pretty traceback about how you tried to use a python feature / module that tinypy doesn’t support 🙂 “batteries not included”

I’ve been out of town for the last few days, so I haven’t done much to tinypy. However, I have realized that my current “dumbparse” module is pretty dumb. Two things are wrong with it:

• It’s slow. Noticeably so with 8k modules, etc.
• It’s dumb. It doesn’t give “useful” parsing errors.

I’ve read up a bit on LR, LL, top-down, and a whole bunch of kinds of parsers and it all sounds a bit magical to me. I’d be glad for some suggestions or ideas on where I could go from here. My requirements are:

• must be pretty compact (I want my parser to be < 12k in size)
• must not get exponentially slower on larger files (but it doesn’t have to be blindingly fast, just decent)
• must be able to notice where a syntax error is (indicated by token – I’ve got a good tokenizer already)
• must parse “basic” python and be written in that as well (see my current files for examples)

Thanks! svn://www.imitationpickles.org/tinypy/trunk – for the brave

Hey all you open source folks out there .. I’m looking for an electronic document / data / business intelligence tool. Something where I can set up a handful of forms, collect the data, search the data, and generate nice reports.

I’m open for any language, any platform, whatever (though, PHP and python are preferred). I’ve done some searching but so far most things seem too “heavyweight” I want something “lightweight” that I can actually get into and use without dedicating the rest of my life to figuring out someone’s junk.

Thanks!

Well, I got two of my favorite python features added in – list comprehensions [x*x for x in range(1,5)] and fancy arguments test(1,2,a=3,*c,**d).

Adding list comprehensions was painless, took only a few minutes. The arguments change was rather difficult because I had to add more rules to the parser, change how the bytecode was outputted, and rework all the internal calling stuff in the VM. Now every function takes a single argument of type ‘params’ which can contain all the details of a call.

I’ve also added in better error handling. Errors print out a backtrace of the function calls and lines of code. This is making debugging everything much easier.

I’m also finding that the more features I add, well, the slower things get. I’m also coming up against my 64k limit, so I’ve moved my tests out of the core code into a separate tests.py file to ensure that I don’t “trim down the tests” to give myself more space 🙂 The tests I’ve made have been invaluable in making it possible to do big changes fairly quickly.

Next on the agenda – either bootstrapping, or making a game with it 🙂

For the brave: svn://www.imitationpickles.org/tinypy/trunk ; python tests.py ; ./run_julia_o3 (not very fast)