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What is Python used for and what is it designed for?
Python is a dynamic, strongly typed, object oriented, multipurpose programming language, designed to be quick (to learn, to use, and to understand), and to enforce a clean and uniform syntax.
Python is dynamically typed: it means that you don't declare a type (e.g. 'integer') for a variable name, and then assign something of that type (and only that type). Instead, you have variable names, and you bind them to entities whose type stays with the entity itself. a = 5 makes the variable name a to refer to the integer 5. Later, a = "hello" makes the variable name a to refer to a string containing "hello". Static typed languages would have you declare int a and then a = 5, but assigning a = "hello" would have been a compile time error. On one hand, this makes everything more unpredictable (you don't know what a refers to). On the other hand, it makes very easy to achieve some results a static typed languages makes very difficult.
Python is strongly typed. It means that if a = "5" (the string whose value is '5') will remain a string, and never coerced to a number if the context requires so. Every type conversion in python must be done explicitly. This is different from, for example, Perl or Javascript, where you have weak typing, and can write things like "hello" + 5 to get "hello5".
Python is object oriented, with class-based inheritance. Everything is an object (including classes, functions, modules, etc), in the sense that they can be passed around as arguments, have methods and attributes, and so on.
Python is multipurpose: it is not specialised to a specific target of users (like R for statistics, or PHP for web programming). It is extended through modules and libraries, that hook very easily into the C programming language.
Python enforces correct indentation of the code by making the indentation part of the syntax. There are no control braces in Python. Blocks of code are identified by the level of indentation. Although a big turn off for many programmers not used to this, it is precious as it gives a very uniform style and results in code that is visually pleasant to read.
The code is compiled into byte code and then executed in a virtual machine. This means that precompiled code is portable between platforms.
Python can be used for any programming task, from GUI programming to web programming with everything else in between. It's quite efficient, as much of its activity is done at the C level. Python is just a layer on top of C. There are libraries for everything you can think of: game programming and openGL, GUI interfaces, web frameworks, semantic web, scientific computing...
Why should you learn Python Programming Language?
Python offers a stepping stone into the world of programming. Even though Python Programming Language has been around for 25 years, it is still rising in popularity.
Some of the biggest advantage of Python are it's
Easy to Read & Easy to Learn
Very productive or small as well as big projects
Big libraries for many things
What is Python Programming Language used for?
As a general purpose programming language, Python can be used for multiple things. Python can be easily used for small, large, online and offline projects. The best options for utilizing Python are web development, simple scripting and data analysis. Below are a few examples of what Python will let you do:
Web Development:
You can use Python to create web applications on many levels of complexity. There are many excellent Python web frameworks including, Pyramid, Django and Flask, to name a few.
Data Analysis:
Python is the leading language of choice for many data scientists. Python has grown in popularity, within this field, due to its excellent libraries including; NumPy and Pandas and its superb libraries for data visualisation like Matplotlib and Seaborn.
Machine Learning:
What if you could predict customer satisfaction or analyse what factors will affect household pricing or to predict stocks over the next few days, based on previous years data? There are many wonderful libraries implementing machine learning algorithms such as Scikit-Learn, NLTK and TensorFlow.
Computer Vision:
You can do many interesting things such as Face detection, Color detection while using Opencv and Python.
Internet Of Things With Raspberry Pi:
Raspberry Pi is a very tiny and affordable computer which was developed for education and has gained enormous popularity among hobbyists with do-it-yourself hardware and automation. You can even build a robot and automate your entire home. Raspberry Pi can be used as the brain for your robot in order to perform various actions and/or react to the environment. The coding on a Raspberry Pi can be performed using Python. The Possibilities are endless!
Game Development:
Create a video game using module Pygame. Basically, you use Python to write the logic of the game. PyGame applications can run on Android devices.
Web Scraping:
If you need to grab data from a website but the site does not have an API to expose data, use Python to scraping data.
Writing Scripts:
If you're doing something manually and want to automate repetitive stuff, such as emails, it's not difficult to automate once you know the basics of this language.
Browser Automation:
Perform some neat things such as opening a browser and posting a Facebook status, you can do it with Selenium with Python.
GUI Development:
Build a GUI application (desktop app) using Python modules Tkinter, PyQt to support it.
Rapid Prototyping:
Python has libraries for just about everything. Use it to quickly built a (lower-performance, often less powerful) prototype. Python is also great for validating ideas or products for established companies and start-ups alike.
Python can be used in so many different projects. If you're a programmer looking for a new language, you want one that is growing in popularity. As a newcomer to programming, Python is the perfect choice for learning quickly and easily.
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The standard way to test VHDL code logic is to write a test bench in VHDL and utilize a simulator like ModelSim; which, I have done numerous times.
I have heard that instead of writing test benches in VHDL, engineers are now using Python to test there VHDL code.
Questions:
How is this done?
Is this done by writing a test bench in Python and then compiling this Python file or linking into Modelsim?
Is this done in Python using a module like myHDL and then linking/importing your VHDL file into Python? Is so, how is the timing diagram generated?
When writing a test bench in Python can you use standard Python coding/modules or just a module like myHDL?
For example if I want to test a TCP/IP stack in VHDL, can I use the socket module in Python to do this (i.e. import socket)?
Is there a reference, paper, or tutorial that shows how to do this? I've checked the Xilinx, Altera, and Modelsim websites but could not find anything.
The only thing I find online about using Python for FPGA are a few packages: with myHDL being the most referenced.
Why Python is good for this
Python is an efficient language for writing reference models in or to process and verify output files of your testbench. Many things take much less time to program in Python than in a VHDL testbench.
One key feature of Python that makes it so suitable is the automatic usage of big integers. If your VHDL uses >64 bit widths, it can be tedious to interface with that in other languages. Also when verifying arithmetic functionality, e.g. Python's Decimal package is a convenient tool to build high-precision references.
How can this be done?
This is an example that does not rely on any other software tools.
A straightforward practical way to interface Python is via input and output files. You can read and write files in your VHDL testbench as it is running in your simulator. Usually each line in the file represents a transaction.
Depending on your needs, you can either have the VHDL testbench compare your design outputs to a reference, or read the output file read back into a Python program. If using files takes too long, at least in Linux it's easy to set up a pipe with mkfifo that you can use as if it were a file, and you can then have your Python program and simulator read from and write to in sync.
Using standard Python modules
With the method I described, you'll have to find a way to separate whatever that module is doing into a stream of data or raw transactions. Unfortunately for your example of a TCP/IP stack, I see no straightforward way to do this and it would probably require significant clarification to discuss further.
More information
Several useful things are linked to in the comments above, especially the link posted by user1155120: https://electronics.stackexchange.com/questions/106784/can-you-interface-a-modelsim-testbench-with-an-external-stimuli
Maybe it is better to design whole design in some other language like SystemC/myHdl/HWToolkit test it and then only export it to your target language.
In order to simulate HDL and drive it from regular python code you have to use framework like cocotb/PyCoRAM and others. Still it gets complicated really fast.
One of the best approaches I have found is to use simulator + agents with queues/abstract memory and in code work only with this queues and not simulator or model itself. It makes writing of testbenches/verification simple.
In python-hw word only HWToolkit currently uses this approach:
tx_rx_test.py
You could write IO from python to text files and use your traditional File-IO VHDL methods to stimulate the DUT.
But, you are better off performing verification in a native environment using a language that was developed to perform functional verification. Using Systemverilog and the Modelsim superset packaged as "Questa Prime" (if you have access to it) is much better.
Assuming you want your python file(s) to be a part of your real-time simulation in terms of transfer functions and/or stimulus generation, they will need to be converted to shared-object files. everything else is post-processing, and is not simulator dependent. e.g. writing output files for later comparison. Non-native simulations, using shared object files, require access via VPI/VLI/FLI/PLI/DPI (depending on what language/tool you are using) which then introduces the overhead of passing the kernel back and forth across the interface. i.e. stop sim, work external, run sim, stop sim, etc.
Systemverilog (IEEE-1800) was developed for IC designers, by IC designers to address the issue of functional verification. while I am all for re-use in terms of .so files from system engineering simulations, if you are writing the testbench (which you shouldn't write your own TB, but that is another discussion), you would be better off using SV given all the built-in functions for constraining stimulus generation, functional coverage and reporting via UCDB.
you should have a reference manual in your Modelsim install to describe using the Programming Interface. you can learn more here : https://verificationacademy.com/ but, it is highly SV-centric... Unfortunately, VHDL is not a verification language, even with the additions they have made to be more like SV, it is, still, better categorized as a modeling language.
Check out PyVHDL. It integrates Python and VHDL with an Eclipse GUI with editing, simulation and VCD generation & display.
GUI Image: https://i.stack.imgur.com/BvQWN.jpg
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I have been working with PHP for about 7 months now, been in Object oriented for half year, and I find it quite easy.
Python's syntax isn't that hard, aswell.
I've been getting intersted in learning python, I started learning java 3 days ago, and got a bit boring (Since I used to work with websites all the time, I am not really interested in software programming).
A few questions about Python:
Python is not only used for webs, but also used for computer softwares. Is that correct?
Python is usually only used on huge systems such as Twitter, Google, and more, but is faster and more stable than PHP?
Is there a full tutorial, on how to set-up Python on XAMPP? I've never installed such things, just Xampp and MySQL. EDIT: How to start making websites with Python, I mean how do I install it?
In PHP, you simple make <? ?> tags or <?php ?>, do you do that in Python? if not, is that correct that you have to include HTML in python, the same way you do in a echo in PHP? echo "<span>hey</span>"?
That's all I wanted to know.
Thank you! I hope you can answer these questions for me.
Python is not only used for webs, but also used for computer softwares. Is that correct?
Definitely true. I have seen Python used for most types of computer software where you would also expect to find Java, C#, C, Matlab and so on.
Python is usually only used on huge systems such as Twitter, Google, and more, but is faster and more stable than PHP?
We use Python for some very large scale, 24x7 systems for a billions-of-dollars industry. But Python is also my language of choice when doing some quick-and-dirty evening hack for some hobby project.
I would not say that it is faster and/or more stable than PHP (I simply don't know), but for me, it makes me focus more on writing high quality code than any other dynamic language I've used. I think every language has a reason why it exists, and almost no language is better in all cases. For me, Python is the language of choice for web projects (unless I have to use Java for some external reason).
Is there a full tutorial, on how to set-up Python on XAMPP? I've never installed such things, just Xampp and MySQL.
I have no experience with XAMPP, but it seems a bit redundant in the Python world. I strongly recommend you to check out Django for web applications. In most production applications, I tie Django with NginX or lighty using FastCGI or the like. It is efficient and quick to set up.
In PHP, you simple make tags or , do you do that in Python? if not, is that correct that you have to include HTML in python, the same way you do in a echo in PHP? echo "hey"?
If you do check out Django, check out its template engine. It is really powerful while still simple (at least compared to ASP.Net which is the only major web template engine I've used before).
This is one of my favorite beginner guides, because it gets you started so quickly
Yes.
This is a subjective question. Following best practices, using efficient data structures, and using efficient algorithms will impact performance far more than any language differences. See this question for more details on "benchmarks," which again, do not really prove anything.
I would suggest this tutorial, it has you use mod_wsgi instead of executing Python scripts with CGI. You do not have to use the Django framework.
Most Python web frameworks will separate views and logic. Some templating engines will still allow you to use logic in templates. See this list for more information on templating engines.
Yes. Python can be used in a similar manner to PHP using Django and other such web frameworks, and it of course inherently can be used for any computing task, being turing complete and whatnot.
Python usually does most things faster than PHP, but stability and performance are affected more by the developer's skill than by the language choice.
I wouldn't know.
Yes, I believe that's how Django works, and other web frameworks ought to work the same. I'm not sure about inline code, because I think that's considered poor practice - you tend to make calls to external Python code, I believe. You typically do not write HTML in your Python code, although there might be libraries which build HTML from inside Python. (I wouldn't know, since I haven't done any web programming with Python.)
I'd also like to recommend you take the Python course at Codeacademy. It'll take you through the syntax, data structures, and neat features of Python; it's a step-by-step, interactive learning approach. It's basic, but a nice start which gives you feedback on your progress.
Python is used for large software projects yes. That is because you can easily link it to C and C++ but also because it is easy to do abstraction in Onject Oriented Style and because it has "Batteries included": e.g. a large STL.
By it self Python is not always the fastest, but because you can link it to C and C++ you gain performance. See comparison between PHP and Python and Java.
You should not start mixing Python and HTML. Instead you should learn a Python Webframework like Django. It will also save you the need to set up LAMP for the beginning, since Django has a built in HTTP server.
For getting starting with Python: http://learnpythonthehardway.org/
You should also get to know IPYTHON and python's packages. The former will help you inspecting objects and getting help quickly. The later is more then the Batteries included ...
1) Python is a general purpose language, like Java, C++, perl, ruby, etc.
2) Python is a general purpose language and can be applied to any problem. php is optimized for web programming, so it might be faster than python.
3) The first thing you want to do is just install the latest version of python on your system, and start messing around with writing short programs. You want to do that before you get involved in a more complicated setting, like web programming, where there are a lot of moving parts.
4) Python doesn't use script tags like php. Not to worry, many people consider mixing code and html to be bad practice.
I suggest you start with some simple cgi scripts. And then you can explore the many web frameworks for python. A web framework is usually a complex system, which you use to program your website. Read this overview of python and the web:
http://docs.python.org/2/howto/webservers.html
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I wanted to know
Python is suited for what kind of applications?
I am new to Python world but I know it's a scripting language like Perl but I was not sure about the kind of applications which one would build using Python and would certainly appreciate if someone can provide some useful information.
It's hard to think of kinds of general applications where Python would be unsuitable, but there are several kinds where, like just about all higher-level languages akin to it, it might be considered a peculiar and probably inferior choice.
In "hard real time" applications, all dynamic memory allocation and freeing, and especially garbage collection, are quite understandably frowned upon; this rules out almost all modern languages (including Python, but also Java, C#, etc, etc), since almost all of them rely on dynamic memory handling and garbage collection of some kind or other.
If you're programming for an "embedded device" which you expect to be produced and sold in huge numbers, every bit of ROM may add measurably to the overall costs, so you want a language focused on squeezing the application down to the last possible bit -- any language that relies on a rich supporting runtime environment or operating system (including Python, and, again, also Java, C#, etc, etc) would no doubt force you to spend extra on many more bits of ROM (consider threaded-interpretive languages like good old Forth: they can make a substantial application's code be measurably more compact than straightforward machine code would!).
There many be other niches that share similar constraints (mostly focused on MEMORY: focus on using as few bits as possible and/or strictly confining execution within precisely predefined limits -- no dynamism, no allocation, no garbage collection, etc, etc), and basically the case would once again incline in similar ways (for example, there are server applications, intended to run on myriads of servers, which can save many megabytes per server if coded in C++ [especially if without "allegedly-smart" pointers;-)] rather than Java, Python, C#, and so on).
Of course there are excellent reasons most modern languages (Python, Java, C#, etc) choose to do dynamic memory allocation, garbage collection, and so forth, despite the importance of application niches where those techniques are a negative aspect: essentially, if you can possibly afford such nice memory handling, writing applications becomes MUCH, MUCH easier, and a whole class of problems and bugs connected with the need to carefully manage memory if you lack such support can go away -- programmer productivity really soars... IF garbage collection and the like can be afforded at all, that is. For example, if an application was going to run on a few hundreds or thousands of servers, I probably wouldn't bother coding it in C++ with manual memory management in order to save memory; it's only at tens and hundreds of thousands of servers, that the economics of all those extra megabytes really kicks in.
Note that, despite the common misconception that "interpreted languages" (ones with a rich underlying runtime or VM, like Java, C#, Python, etc) "are slow", in fact for most CPU-intensive applications (such as scientific computation), Python is perfectly suitable, as long as the "rich supporting runtime environment" (e.g. numpy) is factored in. So, that is not really a factor -- though memory consumption and garbage collection CAN be, in some niches.
http://www.python.org/about/apps/
http://wiki.python.org/moin/Applications
Recap:
Web Applications ( Django, Pylons )
Games ( Eve Online - MMORPG )
Software Development ( Trac for Project Management )
Object Databases ( ZODB / Durus )
Network Programming ( Bittorent )
Mobile applications
And far more...
You say:
I am new to Python world but I know it's an scripting language.
I think the distinction between "scripting languages" and "programming languages" is quite arbitrary. Nearly every language developed in the last 10-20 years has some kind of runtime support, usually in the form of a bytecode interpreter or virtual machine. Python is no different: it gets compiled to bytecode and the bytecode is executed by the Python runtime. The point is, I would say there are very few things you can do in Java, C#, Ruby, etc., that you couldn't do in Python.
That said, however, different languages have different strengths. So there are certainly some kinds of programs that would be better suited to being written in Python. It really depends on what you want the programming language to do for you, and what you want to do yourself. The right answer depends on what kinds of problems you're interested in solving.
I know its a bit late, but if it helps.
Civilization IV
OpenStack
Bazaar
Mercurial
Blender 3D
TwistedMatrix
Trac
Allura (source project for SourceForge.net)
BitTorrent(<5.3)
Gwibber
Ubuntu Software Center
YUM
OpenERP
journyx
Please note that I have avoided the entire race of web-frame works, IDEs (Eric Python IDE, Ninja-ide, PIDA -ide,Wing IDE,Stani's Python Editor and tools ( Pygame, PyGTK, wxPython, mod python, IPython) and webservices ( youtube.com, reddit.com, quora.com, dropbox.com)
Well, the short answer is, since you mentioned Perl, anything you could build in Perl you could build in Python. You can build anything in any language, and if the language has easy C bindings, you could even do it efficiently.
Now, this being the case, the question becomes somewhat philosophical. Python has as a key tenet "There should only be one way to do it". Perl is exactly the opposite. The key tenet of Perl is "There Is More Than One Way To Do It" (TIMTOWTDI) or ( Tim Toady, to his frineds ;) ) How do you like to do things? One clear and shining path, agreed upon by most? Or perhaps you value the almost infinite number of solution paths that any task has in Perl?
So, assuming that your task is I/O bound ( like most things ) rather than CPU bound ( real time programming or games , or nipple crinkling number crunching ) then Python would be suitable. Whether its philosophy suits you is the key question.
Most of the 3d packages these days, such as Maya, SoftImage, Houdini, RealFlow, Blender, etc. all use Python as an embedded scripting and plugin language.
It's computer programming language, and as such any computer program could theoretically could be built with it. See here for an example
Bittorrent was built on Python.
http://en.wikipedia.org/wiki/List_of_Python_software
follow the link and You will see a lot of things. Actually I am also willing to learn Python thats why I have been searching such answers like you and i got this link. Good luck buddy.
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I'm downloading Python 3.1.1 and that comes with the IDLE correct?
I'm also downloading QT for Windows which I'm told is a good GUI framework to work with Python.
What projects should I try to make in order to grasp some of the goodies Python brings to the table?
Thanks a bunch SO.
I highly recommend
http://www.diveintopython3.net
It assumes you already understand programming, and walks you through examples that demonstrate the unique abilities of Python.
Do the next project you intended to program with your prefered language with Python.
If you are new to python, why not start with some simpler command line projects? I know you said you are not new to development, but maybe you should spend some time with the core python stuff before tacking on a GUI framework. Just a suggestion.
Also, I would point out that Python 3+ code looks a bit different than a lot of the python 2.x code samples you will see around the internet. I have found Python 3 to be not the best in terms of backward compatibility. You might want to start out with a 2.x version of Python to get the most out of the plethora of Python tutorials on the internet, then move to Python 3 if you need it.
Write a simple Text Editor.
That was one of the projects i started when i first learned python. It gets you used to the GUI framework, file IO, many types, OOP, lots... It's something that you can grow over time as your confidence builds and it's cross platform so it's handy.
If python is your first dynamic lanugage you might want to play with some of it's dynamic aspects.
For example, using the getattr and setattr methods on objects, you could write a class that provides a fluent way of accessing elements from an XML document. Rather calling methods on an object with parameters like 'xml.getnode("a").getnode("b")' you could dynamically lookup the nodes as attributes and allow 'xml.a.b' instead. I thought this was very cool having come from static languages.
Note that this won't neccessarily give you a great feel for python in general (although you'll pick up the language as you go) but it will give you a taste of what is possible in dynamic languages.
PythonChallenge
Code Golf
Google Code Jam
These are good ways to practice learning Python.
Might I also suggest that you consider using a different IDE.
If you are interested in GUI programming, I would suggest looking into wxPython, PyWin32, easyGUI, TkInter (which is bundled with the Python distribution)
Python Challenge This is fun and interesting to learn Python programming.
While it is a matter of personal preference, I certainly wouldn't want to play around with a GUI framework when starting out -- I would want to get a feel for the language first by playing around with smaller snippets, such as those suggested on Code Golf. While getting your code to fit into the smallest number of bytes perhaps isn't the best way to learn good design, I think it's a good way to learn parts of the language. Certainly, just doing the tasks without necessarily trying to compact them down excessively could be helpful.
A project I wish someone would write: a friendly GUI that wraps around the scanner library and the PDF library, and lets the user easily scan and file documents.
It would have a toolbar with big buttons: "scan letter", "scan brochure", "scan photo". These would respectively choose high-resolution black-and-white, medium-resolution color, and high-resolution color.
The user would plop down the document and hit one of those buttons. Python would wake up the scanner and have it scan, and then would use Python Image Library or something to auto-detect the size of the actual scanned document and auto-crop down to minimal size.
For "scan photo" you would get a JPEG. For the others, you would get a PDF. And it would have an option where you could scan several pages and then select the scanned pages, and say "group" and it would make a single PDF out of them.
Other useful toolbar buttons would be: "Copy Letter", "Copy Brochure", "Copy Photo". These would scan and then immediately print on an appropriate output device (or just on the default output device for your first version).
If you want to go crazy, you could add an OCR function to try to recover searchable text from the scanned images, and put that in the PDF as tags or something.
Someday I will write this if nobody else does...
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Right now I'm developing mostly in C/C++, but I wrote some small utilities in Python to automatize some tasks and I really love it as language (especially the productivity).
Except for the performances (a problem that could be sometimes solved thanks to the ease of interfacing Python with C modules), do you think it is proper for production use in the development of stand-alone complex applications (think for example to a word processor or a graphic tool)?
What IDE would you suggest? The IDLE provided with Python is not enough even for small projects in my opinion.
We've used IronPython to build our flagship spreadsheet application (40kloc production code - and it's Python, which IMO means loc per feature is low) at Resolver Systems, so I'd definitely say it's ready for production use of complex apps.
There are two ways in which this might not be a useful answer to you :-)
We're using IronPython, not the more usual CPython. This gives us the huge advantage of being able to use .NET class libraries. I may be setting myself up for flaming here, but I would say that I've never really seen a CPython application that looked "professional" - so having access to the WinForms widget set was a huge win for us. IronPython also gives us the advantage of being able to easily drop into C# if we need a performance boost. (Though to be honest we have never needed to do that. All of our performance problems to date have been because we chose dumb algorithms rather than because the language was slow.) Using C# from IP is much easier than writing a C Extension for CPython.
We're an Extreme Programming shop, so we write tests before we write code. I would not write production code in a dynamic language without writing the tests first; the lack of a compile step needs to be covered by something, and as other people have pointed out, refactoring without it can be tough. (Greg Hewgill's answer suggests he's had the same problem. On the other hand, I don't think I would write - or especially refactor - production code in any language these days without writing the tests first - but YMMV.)
Re: the IDE - we've been pretty much fine with each person using their favourite text editor; if you prefer something a bit more heavyweight then WingIDE is pretty well-regarded.
You'll find mostly two answers to that – the religous one (Yes! Of course! It's the best language ever!) and the other religious one (you gotta be kidding me! Python? No... it's not mature enough). I will maybe skip the last religion (Python?! Use Ruby!). The truth, as always, is far from obvious.
Pros: it's easy, readable, batteries included, has lots of good libraries for pretty much everything. It's expressive and dynamic typing makes it more concise in many cases.
Cons: as a dynamic language, has way worse IDE support (proper syntax completion requires static typing, whether explicit in Java or inferred in SML), its object system is far from perfect (interfaces, anyone?) and it is easy to end up with messy code that has methods returning either int or boolean or object or some sort under unknown circumstances.
My take – I love Python for scripting, automation, tiny webapps and other simple well defined tasks. In my opinion it is by far the best dynamic language on the planet. That said, I would never use it any dynamically typed language to develop an application of substantial size.
Say – it would be fine to use it for Stack Overflow, which has three developers and I guess no more than 30k lines of code. For bigger things – first your development would be super fast, and then once team and codebase grow things are slowing down more than they would with Java or C#. You need to offset lack of compilation time checks by writing more unittests, refactorings get harder cause you never know what your refacoring broke until you run all tests or even the whole big app, etc.
Now – decide on how big your team is going to be and how big the app is supposed to be once it is done. If you have 5 or less people and the target size is roughly Stack Overflow, go ahead, write in Python. You will finish in no time and be happy with good codebase. But if you want to write second Google or Yahoo, you will be much better with C# or Java.
Side-note on C/C++ you have mentioned: if you are not writing performance critical software (say massive parallel raytracer that will run for three months rendering a film) or a very mission critical system (say Mars lander that will fly three years straight and has only one chance to land right or you lose $400mln) do not use it. For web apps, most desktop apps, most apps in general it is not a good choice. You will die debugging pointers and memory allocation in complex business logic.
In my opinion python is more than ready for developing complex applications. I see pythons strength more on the server side than writing graphical clients. But have a look at http://www.resolversystems.com/. They develop a whole spreadsheet in python using the .net ironpython port.
If you are familiar with eclipse have a look at pydev which provides auto-completion and debugging support for python with all the other eclipse goodies like svn support. The guy developing it has just been bought by aptana, so this will be solid choice for the future.
#Marcin
Cons: as a dynamic language, has way
worse IDE support (proper syntax
completion requires static typing,
whether explicit in Java or inferred
in SML),
You are right, that static analysis may not provide full syntax completion for dynamic languages, but I thing pydev gets the job done very well. Further more I have a different development style when programming python. I have always an ipython session open and with one F5 I do not only get the perfect completion from ipython, but object introspection and manipulation as well.
But if you want to write second Google
or Yahoo, you will be much better with
C# or Java.
Google just rewrote jaiku to work on top of App Engine, all in python. And as far as I know they use a lot of python inside google too.
I really like python, it's usually my language of choice these days for small (non-gui) stuff that I do on my own.
However, for some larger Python projects I've tackled, I'm finding that it's not quite the same as programming in say, C++. I was working on a language parser, and needed to represent an AST in Python. This is certainly within the scope of what Python can do, but I had a bit of trouble with some refactoring. I was changing the representation of my AST and changing methods and classes around a lot, and I found I missed the strong typing that would be available to me in a C++ solution. Python's duck typing was almost too flexible and I found myself adding a lot of assert code to try to check my types as the program ran. And then I couldn't really be sure that everything was properly typed unless I had 100% code coverage testing (which I didn't at the time).
Actually, that's another thing that I miss sometimes. It's possible to write syntactically correct code in Python that simply won't run. The compiler is incapable of telling you about it until it actually executes the code, so in infrequently-used code paths such as error handlers you can easily have unseen bugs lurking around. Even code that's as simple as printing an error message with a % format string can fail at runtime because of mismatched types.
I haven't used Python for any GUI stuff so I can't comment on that aspect.
Python is considered (among Python programmers :) to be a great language for rapid prototyping. There's not a lot of extraneous syntax getting in the way of your thought processes, so most of the work you do tends to go into the code. (There's far less idioms required to be involved in writing good Python code than in writing good C++.)
Given this, most Python (CPython) programmers ascribe to the "premature optimization is the root of all evil" philosophy. By writing high-level (and significantly slower) Python code, one can optimize the bottlenecks out using C/C++ bindings when your application is nearing completion. At this point it becomes more clear what your processor-intensive algorithms are through proper profiling. This way, you write most of the code in a very readable and maintainable manner while allowing for speedups down the road. You'll see several Python library modules written in C for this very reason.
Most graphics libraries in Python (i.e. wxPython) are just Python wrappers around C++ libraries anyway, so you're pretty much writing to a C++ backend.
To address your IDE question, SPE (Stani's Python Editor) is a good IDE that I've used and Eclipse with PyDev gets the job done as well. Both are OSS, so they're free to try!
[Edit] #Marcin: Have you had experience writing > 30k LOC in Python? It's also funny that you should mention Google's scalability concerns, since they're Python's biggest supporters! Also a small organization called NASA also uses Python frequently ;) see "One coder and 17,000 Lines of Code Later".
Nothing to add to the other answers, besides that if you choose python you must use something like pylint which nobody mentioned so far.
One way to judge what python is used for is to look at what products use python at the moment. This wikipedia page has a long list including various web frameworks, content management systems, version control systems, desktop apps and IDEs.
As it says here - "Some of the largest projects that use Python are the Zope application server, YouTube, and the original BitTorrent client. Large organizations that make use of Python include Google, Yahoo!, CERN and NASA. ITA uses Python for some of its components."
So in short, yes, it is "proper for production use in the development of stand-alone complex applications". So are many other languages, with various pros and cons. Which is the best language for your particular use case is too subjective to answer, so I won't try, but often the answer will be "the one your developers know best".
Refactoring is inevitable on larger codebases and the lack of static typing makes this much harder in python than in statically typed languages.
And as far as I know they use a lot of python inside google too.
Well i'd hope so, the maker of python still works at google if i'm not mistaken?
As for the use of Python, i think it's a great language for stand-alone apps. It's heavily used in a lot of Linux programs, and there are a few nice widget sets out there to aid in the development of GUI's.
Python is a delight to use. I use it routinely and also write a lot of code for work in C#. There are two drawbacks to writing UI code in Python. one is that there is not a single ui framework that is accepted by the majority of the community. when you write in c# the .NET runtime and class libraries are all meant to work together. With Python every UI library has at's own semantics which are often at odds with the pythonic mindset in which you are trying to write your program. I am not blaming the library writers. I've tried several libraries (wxwidgets, PythonWin[Wrapper around MFC], Tkinter), When doing so I often felt that I was writing code in a language other than Python (despite the fact that it was python) because the libraries aren't exactly pythonic they are a port from another language be it c, c++, tk.
So for me I will write UI code in .NET (for me C#) because of the IDE & the consistency of the libraries. But when I can I will write business logic in python because it is more clear and more fun.
I know I'm probably stating the obvious, but don't forget that the quality of the development team and their familiarity with the technology will have a major impact on your ability to deliver.
If you have a strong team, then it's probably not an issue if they're familiar. But if you have people who are more 9 to 5'rs who aren't familiar with the technology, they will need more support and you'd need to make a call if the productivity gains are worth whatever the cost of that support is.
I had only one python experience, my trash-cli project.
I know that probably some or all problems depends of my inexperience with python.
I found frustrating these things:
the difficult of finding a good IDE for free
the limited support to automatic refactoring
Moreover:
the need of introduce two level of grouping packages and modules confuses me.
it seems to me that there is not a widely adopted code naming convention
it seems to me that there are some standard library APIs docs that are incomplete
the fact that some standard libraries are not fully object oriented annoys me
Although some python coders tell me that they does not have these problems, or they say these are not problems.
Try Django or Pylons, write a simple app with both of them and then decide which one suits you best. There are others (like Turbogears or Werkzeug) but those are the most used.