Can I use my working Python code as Jython? Are there any differencies?
The point is that I have code in Python, but I want to divide the code into, at least, 2 parallel running processes to improve speed of my program. This can be done using Python because of Global Interpreter Lock. So my idea is to get whole code and compile it using Jython compiler.
Is it possible? If yes, are there any disadvantages?
Most of my code works fine on both Python and Jython. I often use databases (Oracle, PostgreSQL and Informix), so I have different "connector" for Jython (which uses JDBC) and for Python (various libraries). There are some little bugs in Jython 2.5.3 I use like parsing date with %f, but most of libraries I use just work with Jython.
You question is very general. I don't think we can help you without more details like libraries you use (databases, scientific, games, network, text processing etc).
I've built a fairly complicated application with PyQt4 and Python, but it is a pain to send to people (and once I do, they have no idea how to run it). Then there are dependencies to wrestle. Ugh.
Anyways, I just learned about Jython, and since virtually everybody has Java installed, it seems like a perfect solution to my problem of distribution of Python scripts. Has anybody actually developed a functional piece of software with Jython, and if it even exists, one with Jambi bindings?
I'm just asking so that I don't go digging for something which doesn't work.
Thanks!
If you did move this application to Jython, you would have to convert the GUI from QT to Jambi.
Jython is the Python language implemented in Java to run on the Java virtual machine. Because it runs on the JVM, Jython apps can use any Java libraries, such as SWING or Jambi.
It is possible that the differences between PyQT and Jambi are very small, but fundamentally, you would not be using QT directly. Instead you would be using Jambi. And if you use any non-standard Python modules you will still have to resolve packaging issues.
If your application uses other Python modules which are implemented in C, then you would also need to replace those with Java libraries. Jython is great at running a lot of pure Python code unchanged, but Jython runs in a Java environment and there are differences in the way some fundamental objects, such as strings, are implemented. Jython uses Java internals, Java's garbage collector, and so on.
There is more info available via this SO question: Migrating from CPython to Jython
I just downloaded the original Python interpreter from Python's site. I just want to learn this language but to start with, I want to write Windows-based standalone applications that are powered by any RDBMS. I want to bundle it like any typical Windows setup.
I searched old posts on SO and found guys suggesting wxPython and py2exe. Apart from that few suggested IronPython since it is powered by .NET.
I want to know whether IronPython is a pure variant of Python or a modified variant. Secondly, what is the actual use of Python? Is it for PHP like thing or like C# (you can either program Windows-based app. or Web.).
IronPython isn't a variant of Python, it is Python. It's an implementation of the Python language based on the .NET framework. So, yes, it is pure Python.
IronPython is caught up to CPython (the implementation you're probably used to) 2.6, so some of the features/changes seen in Python 2.7 or 3.x will not be present in IronPython. Also, the standard library is a bit different (but what you lose is replaced by all that .NET has to offer).
The primary application of IronPython is to script .NET applications written in C# etc., but it can also be used as a standalone. IronPython can also be used to write web applications using the SilverLight framework.
If you need access to .NET features, use IronPython. If you're just trying to make a Windows executable, use py2exe.
Update
For writing basic RDBMS apps, just use CPython (original Python), it's more extensible and faster. Then, you can use a number of tools to make it stand alone on a Windows PC. For now, though, just worry about learning Python (those skills will mostly carry over to IronPython if you choose to switch) and writing your application.
IronPython is an independent Python implementation written in C# as opposed to the original implementation, often referred to as CPython due to it being written in (no surprise) C.
Python is multi-purpose - you can use it to write web apps (often using a framework such as Django or Pylons), GUI apps (as you've mentioned), command-line tools and as a scripting language embedded inside an app written in another language (for instance, the 3D modelling tool Blender can be scripted using Python).
what does "Pure Python" mean? If you're talking about implemented in Python in the same sense that a module may be pure python, then no, and no Python implementation is. If you mean "Compatible with cPython" then yes, code written to cPython will work in IronPython, with a few caveats. The one that's likely to matter most is that the libraries are different, for instance code depending on ctypes or Tkinter won't work. Another difference is that IronPython lags behind cPython by a bit. the very latest version of this writing is 2.6.1, with an Alpha version supporting a few of the 2.7 language features available too.
What do you really need? If you want to learn to program with python, and also want to produce code for windows, you can use IronPython for that, but you can also use cPython and py2exe; both will work equally well for this with only differences in the libraries.
IronPython is an implementation of Python using C#. It's just like the implementation of Python using Java by Jython. You might want to note that IronPython and Jython will always lag behind a little bit in development. However, you do get the benefit of having some libraries that's not available in the standard Python libraries. In IronPython, you will be able to get access to some of the .NET stuff, like System.Drawings and such, though by using these non-standard libraries, it will be harder to port your code to other platforms. For example, you will have to install mono to run apps written in IronPython on Linux (On windows you will need the .NET Framework)
If I write a python script, anyone can simply point an editor to it and read it. But for programming written in C, one would have to use decompilers and hex tables and such. Why is that? I mean I simply can't open up the Safari web browser and look at its code.
Note: The author disavows a deep expertise in this subject. Some assertions may be incorrect.
Python actually is compiled into bytecode, which is what gets run by the python interpreter. Whenever you use a Python module, Python will generate a .pyc file with a name corresponding to the module. This is the equivalent of the .o file that's generated when you compile a C file.
So if you want something to disassemble, the .pyc file would be it :)
The process that Python goes through when compiling a module is pretty similar to what gcc or another C compiler does with C source code. The major difference is that it happens transparently as part of execution of the file. It's also optional: when running a non-module, i.e. an end-user script, Python will just interpret the code rather than compiling it first.
So really your question is "Why are python programs distributed as source rather than as compiled modules?" Or, put another way, "Why are C applications distributed as compiled binaries rather than as source code?"
It used to be very common for C applications to be distributed as source code. This was back before operating systems and their various subentities (i.e. linux distributions) became more established. Some distros, for example gentoo, still distribute apps as source code. Apps which are a bit more cutting edge or obscure are still distributed as source code for all platforms they target.
The reason for this is compatibility, and dependencies. The reason you can run the precompiled binary Safari on a Mac, or Firefox on Ubuntu Linux, is because it's been specifically built for that operating system, architecture (e.g. x86_64), and set of libraries.
Unfortunately, compilation of a large app is pretty slow, and needs to be redone at least partially every time the app is updated. Thus the motivation for binary distributions.
So why not create a binary distribution of Python? For one thing, as Aaron mentions, modules would need to be recompiled for each new version of the Python bytecode. But this would be similar to rebuilding a C app to link with a newer version of a dynamic library — Python modules are analogous in this sense to C libraries.
The real reason is that Python compilation is very much quicker than C compilation. This is in part, I think, because of the dynamic nature of the language, and also because it's not as thorough of a compilation. This has its tradeoffs: in particular, Python apps run much more slowly than do their C counterparts, because Python has to interpret the compiled bytecode into instructions for the processor, whereas the C app already contains such instructions.
That all being said, there is a program called py2exe that will take a Python module and distribution and build a precompiled windows executable, including in it the logic of the module and its dependencies, including Python itself. I guess the point of this is to avoid having to coerce people into installing Python on their Windows system just to run your app. Under linux, or I think even OS/X, Python is usually already installed, so precompilation is not really necessary. Linux systems also have super-dandy package managers that will transparently install dependencies such as Python if they are not already installed.
Python is a script language, runs in a virtual machine through an interpeter.
C is a compiled language, the code compiled to binary code which the computer can run without all that extra stuff Python needs.
This is sorta a big topic. You should look into your local friendly Computer Science curriculum, you'll find a lot of great stuff on this subject there.
The short answer is the Python is an "interpreted" language, which means that it requires a machine language program (the python interpreter) to run the python program, adding a layer of indirection. C or C++ are different. They are compiled directly to machine code, which runs directly on your processor.
There is a lot of additional voodoo to be learned here, however. Technically Python is compiled to a bytecode, and modern interpreters do more and more "Just in Time" compilation, so the boundaries between compiled and interpreted code are getting fuzzier all the time.
In several comments you asked: "Is it then possible to compile python to an executable binary file and then simply distribute that?"
From a theoretical viewpoint, there's no question the answer is yes -- a Python program could be compiled to, and distributed as, fully compiled machine code.
From a practical viewpoint, it's open to a lot more question. There are a few things like Unladen Swallow, Psyco, Shed Skin, and PyPy that you might want to know about though.
Unladen Swallow is primarily an attempt at making Python run faster, but part of the plan to do so involves using LLVM for its back-end. LLVM can (among other things) produce native machine code output. The last couple of releases of Unladen Swallow have used LLVM for native code generation, but 1) the most recent update on the web site is from late 2009, and 2) the release notes for that version say: "The Unladen Swallow team does not recommend wide adoption of the 2009Q3 release."
Psyco works as a plug-in for Python that basically does JIT compilation, so even though it can speed up execution (quite a lot in some cases), it doesn't produce a machine-code executable you can distribute. In short, while it's sort of similar to what you want, it's not intended to do exactly what you've asked for.
Shed Skin Python-to-C++ produces C++ as its output, and you then compile the C++ and (potentially) distribute the result of that. Shedskin is currently at version 0.5 -- i.e., nobody's claiming that it's a finished, released product. On the other hand, development is ongoing, and each release does seem to include pretty substantial improvements.
PyPy is a Python implementation written in Python. Their intent is to allow code production to be "plugged in" without affecting the rest of the implementation -- but while they currently support 4 different code generation models, I don't believe any of them results in producing native machine code that runs directly on the hardware.
Bottom line: work has been done and is being done with the intent of doing what you asked about, but at least to my knowledge there's not really anything I could reasonably recommend as a finished product that you can really depend on to do the job right now. The primary emphasis is really on execution speed, not producing standalone executables.
Yes, you can - it's called disassembling, and allows you to look at the code of Safari perfectly well. The thing is, C, among other languages, compiles to native code, i.e. code that your CPU can "understand" and execute.
More or less obviously, the level of abstraction present in the instruction set of your CPU is much smaller than that of a high level language like Python. The CPU instructions are not concerned with "downloading that URI", but more "check if that bit is set in a hardware register".
So, in conclusion, the level of complexity present in a native application is much higher when looking at the machine code, so many people simply can't make any sense of what is going on there, it's hard to get the big picture. With experience and time at your hands, it is possible though - people do it all the time, reversing applications and all.
you can't open up and read the code that actually runs for python either. Try
import dis
def foo():
for i in range(100):
print i
print dis.dis(foo)
That will show you the (human readable) bytcode of the foo program. equivalently, you can save the file and import it from the interactive python interpreter. This will create a .pyc file with the same basename as the script. open that with a hex editor and you are looking at the actually python bytecode.
The reason for the difference is that python changes up it's byte code between releases so that you would either need to distribute a different version of a binary only release for each version of python. This would be a pain.
With C, it's compiled to native code and so the byte code is much more stable making binary only releases possible.
because C code is complied to object (machine) code and python code is compiled into an intermediate byte code. I am not sure if you are even referring to the byte code of python - you must be referring to the source file itself which is directly executable (hiding the byte code from you!). C needs to be compiled and linked.
Python scripts are parsed and converted to binary only when they're run - i.e., they're text files and you can read them with an editor.
C code is compiled and linked to an executable binary file before they can be run. Normally, only this executable binary file is distributed - hence you need a decompiler. You can always view the source code, if you've access to it.
Not all C programs require decompilers. There's lots of C code distributed in source form. And some Python programs do require decompilers, if distributed as bytecode (.pyc files).
But, to the extent that your assumptions are valid, it's because C is a compiled language while Python is an interpreted language.
Python scripts are analogous to a man looking at a to-do list written in English (or language he understands). The man has to do all the work, every time that list of things has to be done.
If the man, instead of doing the steps on his own each time, creates and programs a robot which can carry out those steps again and again (and probably faster than him), that robot is analogous to the C program.
The man in the python case is called the "interpreter" and in the C case is called the "compiler", and the C robot is called the compiled program/executable.
When you look at the python program source, you see the to-do list. In case of the robot, you see the gears, motors and batteries, etc, which look very different from the to-do list. If you could get hold of the C "to-do" list, it looks somewhat like the python code, just in a different language.
G-WAN executes ANSI C scripts on the fly -making it just like Python scripts.
This can be server-side scripts (using G-WAN as a Web server) or any general-purpose C program and you can link any existing library.
Oh, and G-WAN C scripts are much faster than Python, PHP or Java...
I recently started learning Python. Not yet ventured into coding.
During one of my learning sessions, i came accross the term Jython.
I googled it & got some information.
I would like to know if anyone has implemented any real-world program using Jython.
Most of the time, Jython isn't used directly to write full read-world programs, but a lot of programs actually embed Jython to use it as a scripting language.
The official Jython website gives a list of projects, some written in Jython, others using Jython for scripting:
http://wiki.python.org/jython/JythonUsers
I am writing a full application in Jython at the moment, and would highly recommend it. Having all of the Java libraries at your disposal is very handy, and the Python syntax and language features actually make using some of them easier than it is in Java (I'm mostly talking about Swing here).
Check out the chapter on GUI Applications from the Jython book. It does a lot of comparisons like 'Look at all this Java code, and now look at it reduced to Python code of half the length!'.
The only caveats I've found are:
Jython development tends to run slightly behind Python, which can be annoying if you find a cool way of doing something in Python, only to discover it's not supported in the current Jython version.
Occasionally you might have hiccups with the interface between Python and Java (I have a couple of unsolved problems here and here, although there are always workarounds for this kind of thing).
Distribution is not as simple as it could be, although once you figure out how to do it, it's fairly painless. I recommend following the method here. It essentially consists of:
Exploding jython.jar and adding your own modules into it.
Writing and compiling a small Java class that creates a Python interpreter and loads up your Python modules.
Creating an executable .jar file consisting of the jython.jar modules, your own Python modules, and the Java class.
Jython really shines for dependency injection.
You know those pesky variables you have to give your program, like
file system paths
server names
ports
Jython provides a really nice way of injecting those variables by putting them in a script. It works equally well for injecting java dependencies, as well.
WebSphere and WebLogic use it as their default scripting engine for administrative purposes.
A lot of other Oracle products ship it as part of their "oracle_commons" module (Oracle Universal Installer, Oracle HTTP Server etc). It's mostly version 2.2 being deployed though, which is a bit old and clunky.
There is a list of application that uses jython at http://wiki.python.org/jython/JythonUsers