Why is Python a favourite among people working in animation industry? - python

What is that needs to be coded in Python instead of C/C++ etc? I know its advantages etc. I want to know why exactly makes Python The language for people in this industry?

I work in this industry, and here's what I've observed:
It's a nice, tidy language that's not hard to pick up. You don't have to be a language guru to use it.
It embeds nicely in C/C++ applications.
It has data types, so numeric operations can be done without type shimmering.
Speaking of numeric operations, NumPy!
Network effect -- everybody else uses it, so we get a virtuous cycle of interoperable scripting.

Perhaps that's because it's a scripting language for Blender?

A few other points I've not seen in the existing answers:
it's free
it's fast [enough]
it runs on every platform I know of (AIX, HPUX, Linux, Mac OS X, Windows..)
quick to learn
large, powerful libraries
numeric
graphical
etc
simple, consistent syntax
the existing user-base is large
because it's easy-to-learn, you don't have to be a "programmer" to use it

Because Python is what Basic should have been ;)
Its a language designed from the beginning to be used by non-programmers, but with the power to be truly used as a general purpose programming language.

Aside from the fact that it's already in use, the main advantage is that it's quick to use. Java, C, and friends almost all require tedious coding that merely restates what you already know. Python is designed to be quick to write, quick to modify, and as general as possible.
As an example, functions in java require you to declare the type of each of the input variables. In python, as long as you pass input variables that work with the function, it's valid. This makes your code extremely flexible. You don't waste time declaring variables as one type or another, you just use them.
Some people will tell you that java produces code that is "more correct", but in animation and graphics, producing code that works in as short a time as possible is usually the goal.

My guess is that it is the tool for the job because it is easy to prototype extra features.

I used python for molecular animation using PyMol. Many molecular visualization programs have their own scripting languages. PyMol's scripting language is python, a real programming language. So, if your task requires calculations of any kind, text parsing or calling the net, you are welcome. Before I assume that in "conventional" animation the situation is similar.

Related

Benefits of accessing the Abstract Syntaxt Tree (AST) . How does Julia exploit it?

I have read that Julia has access to the AST of the code it runs. What exactly does this mean? Is it that the runtime can access it, that code itself can access it, or both?
Building on this:
Is this a key difference of Julia with respect to other dynamic languages, specifically Python?
What are the practical benefits of being able to access the AST?
What would be a good example of something that you can't easily do in Python, but that you can do in Julia, because of this?
What distinguishes Julia from languages like Python is that Julia allows you to intercept code before it is evaluated. Macros are just functions, written in Julia, which let you access that code and manipulate it before it runs. Furthermore, rather than treating code as a string (like "f(x)"), it's provided as a Julian object (like Expr(:call, :f, :x)).
There are plenty of things this allows which just aren't possible in Python. The main ones are:
You can do more work at compile time, increasing performance
Two good examples of this are regexes and printf. Both of these take a format specification of some kind and interpret it in some way. Now, these can fairly straightforwardly be implemented as functions, which might look like this:
match(Regex(".*"), str)
printf("%d", num)
The problem with this is that these specifications must be re-interpreted every time the statement is run. Every time the interpreter goes over this block, the regex must be re-compiled into a state machine, and the format must be run through a mini-interpreter. On the other hand, if we implement these as macros:
match(r".*", str)
#printf("%d", num)
Then the r and #printf macros will intercept the code at compile time, and run their respective interpreters then. The regex turns into a fast state machine, and the #printf statement turns into a simple println(num). At run time the minimum of work is done, so the code is blazing fast. Now, other languages are able to provide fast regexes, for example, by providing special syntax for it – but the fact that they're not special-cased in Julia means that developers can use the same techniques in their own code.
You can make mini-compilers for, well, pretty much anything
Languages with macros tend to have more capable embedded DSLs, because you can change the semantics of the language at will. For example, the algebraic modelling language, JuMP.jl. Clojure also has some neat examples of this too, like its embedded logic programming language. Mathematica.jl even embeds Mathematica's semantics in Julia, so that you can write really natural symbolic expressions like #Integrate(log(x), {x,0,2}). You can fake this to a point in Python (SymPy does a good job), but not as cleanly or as efficiently.
If that doesn't convince you, consider that someone managed to implement an interactive Julia debugger in pure Julia using macros. Try that in Python.
Edit: Another great example of something that's difficult in other languages is Cartestian.jl, which lets you write generic algorithms across arrays of any number of dimensions.
I am not familiar with Julia and only first heard of it with your question, but this sounded an awfully lot like Lisp (and indeed Julia seems to be a new grandchild/dialect of Lisp from what I'm reading) and it's powerful macros. The ability to access the AST at run/compile time brings a whole new dimension to the programmers code: metaprogramming.
See http://docs.julialang.org/en/latest/manual/metaprogramming/ and especially http://docs.julialang.org/en/latest/manual/metaprogramming/#macros for some of the practical uses. Basically you can 'inject/modify' code in places where it would be impossible for python/R to do the same.
Example: loop unrolling without any copy & paste, which takes a compile time argument to easily vary how much you want to unroll the loop.
Here's an excellent resource on Julia metaprogramming: https://en.wikibooks.org/wiki/Introducing_Julia/Metaprogramming

Python and functional language interop

My current primary programming language is python. There are lots of things I like about it, but I also like functional languages. Not enough to do an entire program in them, but definitely for certain functionality, that fits the functional mould well.
Of course .NET is amazing in this regard, having both ironpython and F#. But considering the ironpython support for the scientific python ecosystem is still dodgy last time I checked, .NET is not much of an option for me. I am a bit shocked at the apparent lack of tools to facilitate interop between cpython and say, Haskell. They are both mature languages with large communities, that seem like such a nice match to me.
Is there something about their architecture that makes them ill-compatible that im missing, or is this just something awesome that is still waiting to happen?
To clarify; there are some half-baked projects out there, but I am thinking of something that parallels the awesomeness of Weave, pycuda, or boost. Something that automates all the plumbing inherent in interop with just a few annotations.
Another approach is to use unix pipes, and just write a Haskell program, and also write a Python program, and have them communicate over text. Haskell and Python even share the same syntax for lists, so it's really easy to pipe data from one to the other.
Referring to:
Is there something about their architecture that makes them
ill-compatible that im missing, or is this just something awesome that
is still waiting to happen?
I think it is about the people doing these languages:
There are not much people who want to do Haskell and Python at the same time.
to make use of both languages (liek Haskell and Python) at the same time you either could go via the C-Interface or create a protocol both languages speak.
Both are fairly advanced, limiting the number of people who could do it. Sure there would be also tradeoffs which make it difficult to use the full power of both languages.
I am using Python and although I know some Haskell, I do not program it. I am a bit stuck in object-orientation, telling me that some day a problem will decide for me that it can better be solved in Haskell than python. That problem did not yet occur because my first thought is: I know how to do it in Python. I think other 'experts' face that problem, too.
You start thinking in a language. I think that Haskell has a totally different way of thinking with its functional style, no side-effects. To get into this thinking I need to forget or not use my Python knowledge. Switching between these two ways of thinking requires some strength.
Wrapping it up: because that two languages are not so close they stay apart. It is hard to do both and there are not many or easy ways to practice doing both.
I think that any answer to this question would be remiss without considering the inertia of object-oriented and imperative languages relative to functional ones. Consider the following situation, beginning with the fact that functional languages are not taught at nearly the frequency that object-oriented or imperative languages are at the secondary, university, or graduate level. As User mentions, there is significant momentum involved as a programmer concerning one's choice of language. For example, during the course of a typical CS degree at a four year University, one may learn a handful of languages and more than likely, not one of them is a functional language. This typical graduate will then proceed to work in industry, where, after programming for 40+ hours per week for one's job, it is very difficult to then take time to, not only learn an entirely new language, but to learn a language that operates completely differently from the one's one already knows. On top of all of this, there is the drawback that functional languages are not nearly as useful in industry as object-oriented or imperative one's are. One can see that given this current state, it is understandable that the interoperability between Python and Haskell is not what some programmers would like it to be.
If you were to use Haskell to Python bindings, what would you do in each language?
If you consider binding C and Python, for example, you use C when you need the speed boost, or when you need to push bits around, and you are using Python when want to be expressive and concise. It's common that you have a pair of languages, one for most of the logic, and one that you can drop down to for speed, at the cost of clarity. The more of a gap between the languages, the more you can gain from switching.
If we were to bind Haskell and Python, it is less clear what you'd get out of it. I wouldn't drop from Python into Haskell just for speed, since Haskell, while fast, isn't as fast as C. But if I was using Haskell, when would I use Python? Python isn't more expressive than Haskell, not like comparing C and Python.
I think that most of the time, it's easier to just import functools, and program functionally in Python, instead of having to convert objects into some Haskell representation, do some work, and then convert it back.
Though, if you really wanted it, Cython would make it easy to write functions that Haskell's FFI can use.

coding language customization

I've always wondered this since I started to code: is there any way to customize deep portions of a language to your taste.
For example, I code mainly in Python would like to use the | or : characters to denote the boundary of a Set. I use sets frequently and hate typing set(some_list) or explicitly set([a,b,b,c,d]). I've been using s() by setting s = set, but this wouldn't work if I was working on code others would have to read.
Perhaps a "translator" text-editor add-on which would save 2 copies of your code, one with your own syntax and one with the standard syntax would be sufficient. Is there such a thing? (especially for python)
Clarity and readability is a very important trait in production code. Remember that far more effort is generally expended into reading existing code than is spent writing new code. Maintenance is a serious consideration.
With that in mind, doing something like s = set and using s() instead of set() adds no functional benefit and is detrimental to readability while only offering the savings of a couple keystrokes. I think you recognize that on some level, but part of you isn't willing to accept the additional keystrokes in the name of readability.
I urge you to consider something like a macro instead so you feel better about pressing only a single key while still producing the same code. Something like a Logitech G15/G110/G19 keyboard even allows you to do this independent of the editor you're using so you don't need a software add-on. A few mice would allow you to do something similar as well (oh how I love my Razer Naga). Of course, a basic macro feature in software would work as well, but you're probably pressing a key combination to do it and just typing set( is probably faster anyway.
It is possible indeed to customise your language as you like. Some languages provide powerful metaprogramming features (unfortunately, Python is not one of them). Take a look at Lisp macros, or Nemerle, or Converge (the latter is the closest to Python). Some languages, like Katahdin, would even allow you to modify the very syntax easily.
But this sort of power should not be used for petty language modifications - it would hinder the readability and won't add any significant benefits. It's much better to use metaprogramming for implementing the embedded Domain Specific Languages, preferably with distinctive syntax, so it would be obvious for a reader when you're using the core language constructs and when it is a eDSL code.
Of course, if you're designing your own language from scratch or implementing an existing language, you can also use metaprogramming and syntax alteration tricks for the core language functionality as well, it is a much more flexible approach than having a huge, bloated core language from the very beginning.

Scripting language for trading strategy development

I'm currently working on a component of a trading product that will allow a quant or strategy developer to write their own custom strategies. I obviously can't have them write these strategies in natively compiled languages (or even a language that compiles to a bytecode to run on a vm) since their dev/test cycles have to be on the order of minutes.
I've looked at lua, python, ruby so far and really enjoyed all of them so far, but still found them a little "low level" for my target users. Would I need to somehow write my own parser + interpreter to support a language with a minimum of support for looping, simple arithmatic, logical expression evaluation, or is there another recommendation any of you may have? Thanks in advance.
Mark-Jason Dominus, the author of Perl's Text::Template module, has some insights that might be relevant:
When people make a template module
like this one, they almost always
start by inventing a special syntax
for substitutions. For example, they
build it so that a string like %%VAR%%
is replaced with the value of $VAR.
Then they realize the need extra
formatting, so they put in some
special syntax for formatting. Then
they need a loop, so they invent a
loop syntax. Pretty soon they have a
new little template language.
This approach has two problems: First,
their little language is crippled. If
you need to do something the author
hasn't thought of, you lose. Second:
Who wants to learn another language?
If you write your own mini-language, you could end up in the same predicament -- maintaining a grammar and a parser for a tool that's crippled by design.
If a real programming language seems a bit too low-level, the solution may not be to abandon the language but instead to provide your end users with higher-level utility functions, so that they can operate with familiar concepts without getting bogged down in the weeds of the underlying language.
That allows beginning users to operate at a high level; however, you and any end users with a knack for it -- your super-users -- can still leverage the full power of Ruby or Python or whatever.
It sounds like you might need to create some sort of Domain Specific Language (DSL) for your users that could be built loosely on top of the target language. Ruby, Python and Lua all have their various quirks regarding syntax, and to a degree some of these can be massaged with clever function definitions.
An example of a fairly robust DSL is Cucumber which implements a an interesting strategy of converting user-specified verbiage to actual executable code through a series of regular expressions applied to the input data.
Another candidate might be JavaScript, or some kind of DSL to JavaScript bridge, as that would allow the strategy to run either client-side or server-side. That might help scale your application since client machines often have surplus computing power compared to a heavily loaded server.
Custom-made modules are going to be needed, no matter what you choose, that define your firm's high level constructs.
Here are some of the needs I envision -- you may have some of these covered already: a way to get current positions, current and historical quotes, previous performance data, etc... into the application. Define/backtest/send various kinds of orders (limit/market/stop, what exchange, triggers) or parameters of options, etc... You probably are going to need multiple sandboxes for testing as well as the real thing.
Quants want to be able to do matrix operations, stochastic calculus, PDEs.
If you wanted to do it in python, loading NumPy would be a start.
You could also start with a proprietary system designed to do mathematical financial research such as something built on top of Mathematica or Matlab.
I've been working on a Python Algorithmic Trading Library (actually for backtesting, not for real trading). You may want to take a look at it: http://gbeced.github.com/pyalgotrade/
Check out http://www.tadeveloper.com for a backtesting framework using MATLAB as a scripting language. MATLAB has the advantage that it is very powerful but you do not need to be a programmer to use it.
This might be a bit simplistic, but a lot of quant users are used to working with Excel & VBA macros. Would something like VBSCript be usable, as they may have some experience in this area.
Existing languages are "a little "low level" for my target users."
Yet, all you need is "a minimum of support for looping, simple arithmatic, logical expression evaluation"
I don't get the problem. You only want a few features. What's wrong with the list of languages you provided? They actually offer those features?
What's the disconnect? Feel free to update your question to expand on what the problem is.
I would use Common Lisp, which supports rapid development (you have a running image and can compile/recompile individual functions) and tailoring the language to your domain. You would provide functions and macros as building blocks to express strategies, and the whole language would be available to the user for combining these.
Is something along the lines of Processing the complexity level that you're shooting for? Processing is a good example of taking a full-blown language (Java) and reducing/simplifying the available syntax into only a subset applicable to the problem domain (problem domain = visualization in the case of Processing).
Here's a little side-by-side comparison from the Processing docs.
Java:
g.setColor(Color.black)
fillRect(0, 0, size.width, size.height);
Processing:
background(0);
As others have suggested, you may be able to simply write enough high-level functions such that most of the complexity is hidden from the user but you still retain the ability to do more low-level things when necessary. The Wiring language for Arduino follows this strategy of using a thin layer of high-level functions on top of C in order to make it more accessible to non-programmers and hobbyists.
Define the language first -- if possible, use the pseudo-language called EBN, it's very simple (see the Wikipedia entry).
Then once you have that, pick the language. Almost certainly you will want to use a DSL. Ruby and Lua are both really good at that, IMO.
Once you start working on it, you may find that you go back to your definition and tweak it. But that's the right order to do things, I think.
I have been in the same boat building and trading with my own software. Java is not great because you want something higher level like you say. I have had a lot of success using the eclipse project xtext. http://www.eclipse.org/Xtext It does all the plumbing of building parsers etc. for you and using eclipse you can quickly generate code with functional editors. I suggest looking into this as you consider other options as well. This combined with the eclipse modeling framework is very powerful for quickly building DSL's which sounds like you need. - Duncan

Python vs. Ruby for metaprogramming [closed]

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I'm currently primarily a D programmer and am looking to add another language to my toolbox, preferably one that supports the metaprogramming hacks that just can't be done in a statically compiled language like D.
I've read up on Lisp a little and I would love to find a language that allows some of the cool stuff that Lisp does, but without the strange syntax, etc. of Lisp. I don't want to start a language flame war, and I'm sure both Ruby and Python have their tradeoffs, so I'll list what's important to me personally. Please tell me whether Ruby, Python, or some other language would be best for me.
Important:
Good metaprogramming. Ability to create classes, methods, functions, etc. at runtime. Preferably, minimal distinction between code and data, Lisp style.
Nice, clean, sane syntax and consistent, intuitive semantics. Basically a well thought-out, fun to use, modern language.
Multiple paradigms. No one paradigm is right for every project, or even every small subproblem within a project.
An interesting language that actually affects the way one thinks about programming.
Somewhat important:
Performance. It would be nice if performance was decent, but when performance is a real priority, I'll use D instead.
Well-documented.
Not important:
Community size, library availability, etc. None of these are characteristics of the language itself, and all can change very quickly.
Job availability. I am not a full-time, professional programmer. I am a grad student and programming is tangentially relevant to my research.
Any features that are primarily designed with very large projects worked on by a million code monkeys in mind.
I've read up on Lisp a little and I would love to find a language that allows some of the cool stuff that Lisp does, but without the strange syntax, etc. of Lisp.
Wouldn't we all.
minimal distinction between code and data, Lisp style
Sadly, the minimal distinction between code and data and "strange" syntax are consequences of each other.
If you want easy-to-read syntax, you have Python. However, the code is not represented in any of the commonly-used built-in data structures. It fails—as most languages do—in item #1 of your 'important' list. That makes it difficult to provide useful help.
You can't have it all. Remember, you aren't the first to have this thought. If something like your ideal language existed, we'd all be using it. Since the real world falls short of your ideals, you'll have to re-prioritize your wish list. The "important" section has to be rearranged to identify what's really important to you.
Honestly, as far as metaprogramming facilities go, Ruby and Python are a lot more similar than some of their adherent like to admit. This review of both language offers a pretty good comparison/review:
http://regebro.wordpress.com/2009/07/12/python-vs-ruby/
So, just pick one based on some criteria. Maybe you like Rails and want to study that code. Maybe SciPy is your thing. Look at the ecosystem of libraries, community, etc, and pick one. You certainly won't lose out on some metaprogramming nirvana based on your choice of either.
Disclaimer: I only dabble in either language, but I have at least written small working programs (not just quick scripts, for which I use Perl, bash or GNU make) in both.
Ruby can be really nice for the "multiple paradigms" point 3, because it works hard to make it easy to create domain-specific languages. For example, browse online and look at a couple of bits of Ruby on Rails code, and a couple of bits of Rake code. They're both Ruby, and you can see the similarities, but they don't look like what you'd normally think of as the same language.
Python seems to me to be a bit more predictable (possibly correlated to 'clean' and 'sane' point 2), but I don't really know whether that's because of the language itself or just that it's typically used by people with different values. I have never attempted deep magic in Python. I would certainly say that both languages are well thought out.
Both score well in 1 and 4. [Edit: actually 1 is pretty arguable - there is "eval" in both, as common in interpreted languages, but they're hardly conceptually pure. You can define closures, assign methods to objects, and whatnot. Not sure whether this goes as far as you want.]
Personally I find Ruby more fun, but in part that's because it's easier to get distracted thinking of cool ways to do things. I've actually used Python more. Sometimes you don't want cool, you want to get on with it so it's done before bedtime...
Neither of them is difficult to get into, so you could just decide to do your next minor task in one, and the one after that in the other. Or pick up an introductory book on each from the library, skim-read them both and see what grabs you.
There's not really a huge difference between python and ruby at least at an ideological level. For the most part, they're just different flavors of the same thing. Thus, I would recommend seeing which one matches your programming style more.
Have you considered Smalltalk? It offers a very simple, clear and extensible syntax with reflectivity and introspection capabilities and a fully integrated development environment that takes advantage of those capabilities. Have a look at some of the work being done in Squeak Smalltalk for instance. A lot of researchers using Squeak hang out on the Squeak mailing list and #squeak on freenode, so you can get help on complex issues very easily.
Other indicators of its current relevance: it runs on any platform you'd care to name (including the iPhone); Gilad Bracha is basing his Newspeak work on Squeak; the V8 team cut their teeth on Smalltalk VMs; and Dan Ingalls and Randal Schwartz have recently returned to Smalltalk work after years in the wilderness.
Best of luck with your search - let us know what you decide in the end.
Lisp satisfies all your criteria, including performance, and it is the only language that doesn't have (strange) syntax. If you eschew it on such an astoundingly ill-informed/wrong-headed basis and consequently miss out on the experience of using e.g. Emacs+SLIME+CL, you'll be doing yourself a great disservice.
Your 4 "important" points lead to Ruby exactly, while the 2 "somewhat important" points ruled by Python. So be it.
You are describing Ruby.
Good metaprogramming. Ability to create classes, methods, functions,
etc. at runtime. Preferably, minimal
distinction between code and data,
Lisp style.
It's very easy to extend and modify existing primitives at runtime. In ruby everything is an object, strings, integers, even functions.
You can also construct shortcuts for syntactic sugar, for example with class_eval.
Nice, clean, sane syntax and consistent, intuitive semantics.
Basically a well thought-out, fun to
use, modern language.
Ruby follows the principle of less surprise, and when comparing Ruby code vs the equivalent in other language many people consider it more "beautiful".
Multiple paradigms. No one paradigm is right for every project,
or even every small subproblem within
a project.
You can follow imperative, object oriented, functional and reflective.
An interesting language that actually affects the way one thinks
about programming.
That's very subjective, but from my point of view the ability to use many paradigms at the same time allows for very interesting ideas.
I've tried Python and it doesn't fit your important points.
Compare code examples that do the same thing (join with a newline non-empty descriptions of items from a myList list) in different languages (languages are arranged in reverse-alphabetic order):
Ruby:
myList.collect { |f| f.description }.select { |d| d != "" }.join("\n")
Or
myList.map(&:description).reject(&:empty?).join("\n")
Python:
descriptions = (f.description() for f in mylist)
"\n".join(filter(len, descriptions))
Or
"\n".join(f.description() for f in mylist if f.description())
Perl:
join "\n", grep { $_ } map { $_->description } #myList;
Or
join "\n", grep /./, map { $_->description } #myList;
Javascript:
myList.map(function(e) e.description())
.filter(function(e) e).join("\n")
Io:
myList collect(description) select(!="") join("\n")
Here's an Io guide.
Ruby would be better than Lisp in terms of being "mainstream" (whatever that really means, but one realistic concern is how easy it would be to find answers to your questions on Lisp programming if you were to go with that.) In any case, I found Ruby very easy to pick up. In the same amount of time that I had spent first learning Python (or other languages for that matter), I was soon writing better code much more efficiently than I ever had before. That's just one person's opinion, though; take it with a grain of salt, I guess. I know much more about Ruby at this point than I do Python or Lisp, but you should know that I was a Python person for quite a while before I switched.
Lisp is definitely quite cool and worth looking into; as you said, the size of community, etc. can change quite quickly. That being said, the size itself isn't as important as the quality of the community. For example, the #ruby-lang channel is still filled with some incredibly smart people. Lisp seems to attract some really smart people too. I can't speak much about the Python community as I don't have a lot of firsthand experience, but it seems to be "too big" sometimes. (I remember people being quite rude on their IRC channel, and from what I've heard from friends that are really into Python, that seems to be the rule rather than the exception.)
Anyway, some resources that you might find useful are:
1) The Pragmatic Programmers Ruby Metaprogramming series (http://www.pragprog.com/screencasts/v-dtrubyom/the-ruby-object-model-and-metaprogramming) -- not free, but the later episodes are quite intriguing. (The code is free, if you want to download it and see what you'd be learning about.)
2) On Lisp by Paul Graham (http://www.paulgraham.com/onlisp.html). It's a little old, but it's a classic (and downloadable for free).
#Jason I respectively disagree. There are differences that make Ruby superior to Python for metaprogramming - both philosophical and pragmatic. For starters, Ruby gets inheritance right with Single Inheritance and Mixins. And when it comes to metaprogramming you simply need to understand that it's all about the self. The canonical difference here is that in Ruby you have access to the self object at runtime - in Python you do not!
Unlike Python, in Ruby there is no separate compile or runtime phase. In Ruby, every line of code is executed against a particular self object. In Ruby every class inherits from both object and a hidden metaclass. This makes for some interesting dynamics:
class Ninja
def rank
puts "Orange Clan"
end
self.name #=> "Ninja"
end
Using self.name accesses the Ninja classes' metaclass name method to return the class name of Ninja. Does metaprogramming flower so beautiful in Python? I sincerely doubt it!
I am using Python for many projects and I think Python does provide all the features you asked for.
important:
Metaprogramming: Python supports metaclasses and runtime class/method generation etc
Syntax: Well thats somehow subjective. I like Pythons syntax for its simplicity, but some People complain that Python is whitespace-sensitive.
Paradigms: Python supports procedural, object-oriented and basic functional programming.
I think Python has a very practical oriented style, it was very inspiring for me.
Somewhat important:
Performance: Well its a scripting language. But writing C extensions for Python is a common optimization practice.
Documentation: I cannot complain. Its not that detailed as someone may know from Java, but its good enough.
As you are grad student you may want to read this paper claiming that Python is all a scientist needs.
Unfortunately I cannot compare Python to Ruby, since I never used that language.
Regards,
Dennis
Well, if you don't like the lisp syntax perhaps assembler is the way to go. :-)
It certainly has minimal distinction between code and data, is multi-paradigm (or maybe that is no-paradigm) and it's a mind expanding (if tedious) experience both in terms of the learning and the tricks you can do.
Io satisfies all of your "Important" points. I don't think there's a better language out there for doing crazy meta hackery.
one that supports the metaprogramming hacks that just can't be done in a statically compiled language
I would love to find a language that allows some of the cool stuff that Lisp does
Lisp can be compiled.
Did you try Rebol?
My answer would be neither. I know both languages, took a class on Ruby and been programming in python for several years. Lisp is good at metaprogramming due to the fact that its sole purpose is to transform lists, its own source code is just a list of tokens so metaprogramming is natural. The three languages I like best for this type of thing is Rebol, Forth and Factor. Rebol is a very strong dialecting language which takes code from its input stream, runs an expression against it and transforms it using rules written in the language. Very expressive and extremely good at dialecting. Factor and Forth are more or less completely divorced from syntax and you program them by defining and calling words. They are generally mostly written in their own language. You don't write applications in traditional sense, you extend the language by writing your own words to define your particular application. Factor can be especially nice as it has many features I have only seen in smalltalk for evaluating and working with source code. A really nice workspace, interactive documents, etc.
There isn't really a lot to separate Python and Ruby. I'd say the Python community is larger and more mature than the Ruby community, and that's really important for me. Ruby is a more flexible language, which has positive and negative repercussions. However, I'm sure there will be plenty of people to go into detail on both these languages, so I'll throw a third option into the ring. How about JavaScript?
JavaScript was originally designed to be Scheme for the web, and it's prototype-based, which is an advantage over Python and Ruby as far as multi-paradigm and metaprogramming is concerned. The syntax isn't as nice as the other two, but it is probably the most widely deployed language in existence, and performance is getting better every day.
If you like the lisp-style code-is-data concept, but don't like the Lispy syntax, maybe Prolog would be a good choice.
Whether that qualifies as a "fun to use, modern language", I'll leave to others to judge. ;-)
Ruby is my choice after exploring Python, Smalltalk, and Ruby.
What about OCaml ?
OCaml features: a static type system, type inference, parametric polymorphism, tail recursion, pattern matching, first class lexical closures, functors (parametric modules), exception handling, and incremental generational automatic garbage collection.
I think that it satisfies the following:
Important:
Nice, clean, sane syntax and consistent, intuitive semantics. Basically a well thought-out, fun to use, modern language.
Multiple paradigms. No one paradigm is right for every project, or even every small subproblem within a project.
An interesting language that actually affects the way one thinks about programming.
Somewhat important:
Performance. It would be nice if performance was decent, but when performance is a real priority, I'll use D instead.
Well-documented.
I've use Python a very bit, but much more Ruby. However I'd argue they both provide what you asked for.
If I see all your four points then you may at least check:
http://www.iolanguage.com/
And Mozart/Oz may be interesting for you also:
http://mozart.github.io/
Regards
Friedrich
For python-style syntax and lisp-like macros (macros that are real code) and good DSL see converge.
I'm not sure that Python would fulfill all things you desire (especially the point about the minimal distinction between code and data), but there is one argument in favour of python. There is a project out there which makes it easy for you to program extensions for python in D, so you can have the best of both worlds. http://pyd.dsource.org/celerid.html
if you love the rose, you have to learn to live with the thorns :)
I would recommend you go with Ruby.
When I first started to learn it, I found it really easy to pick up.
Do not to mix Ruby Programming Language with Ruby Implementations, thinking that POSIX threads are not possible in ruby.
You can simply compile with pthread support, and this was already possible at the time this thread was created, if you pardon the pun.
The answer to this question is simple. If you like lisp, you will probably prefer ruby. Or, whatever you like.
I suggest that you try out both languages and pick the one that appeals to you. Both Python and Ruby can do what you want.
Also read this thread.
Go with JS just check out AJS (Alternative JavaScript Syntax) at my github http://github.com/visionmedia it will give you some cleaner looking closures etc :D
Concerning your main-point (meta-programming):
Version 1.6 of Groovy has AST (Abstract Syntax Tree) programming built-in as a standard and integrated feature.
Ruby has RubyParser, but it's an add-on.

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