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I did a quick research into documentation and did not find any evidence that suggests argparse is supported before 2.6. We have development network as well as servers that use Python 2.5.1 to do a lot of things. I had an idea to upgrade it, but didn't realise that there is a change request process that needs to be gone through. I am wondering if I can have an alternative method to use something similar to argparse.
I know optparse is the other option, but it is also deprecated in 2.7.x versions. Does anyone know anything else?
argparse is included with Python from version 2.7 onwards.
You can install it from PyPI for earlier versions of Python, Python 2.3 and up is supported.
Based on discussions that I've seen on the Python bug issue site, optparse is not really deprecated. Don't expect further development, but it isn't going to disappear any time soon.
All of argparse is contained in one file, argparse.py. So you could grab that from almost anywhere, and put it on your load path. A possible exception is a recent Python3 version that has a gratuitous (IMO) 'nested-with' statement.
It's possible that there are other incompatibilities with Python 2.5, but it wouldn't be hard to test a 2.7 argparse.py in the 2.5 environment.
There is also a unittesting Lib/test/test_argparse.py file. Though that is more likely to be incompatible, since it is using some newer unittest functionality.
I'm making a ST3 plugin on my OSX dev-environment, but according to the unofficial docs:
Sublime Text ships with a trimmed down standard library. The Tkinter, multiprocessing and sqlite3 modules are among the missing ones.
Even if it's not bundled with ST3, is there a way I can still import multiprocessing (docs)? Is there a way I can import it as a "standalone" module inside my plugin dir?
Assuming you intend this program for wide distribution, it's probably unreasonable to expect users to install Python 3 in a standard location in order to use your work. However, depending on Python's redistribution license, you may be able to get away with just bundling multiprocessing with your plugin. If your main my_awesome_plugin.py file is in the root of your plugin directory, put the full multiprocessing directory in as a subdirectory and you should be able to import multiprocessing as mp just fine. Fortunately it's pure Python, so you don't have to worry about platform-specific distributions.
EDIT
OK, my bad. After a little more exploring around the ...lib/python3.3/ hierarchy, it turns out there is a compiled _multiprocessing.so library in there to supplement the pure Python version. So, this will be a little more difficult than just dropping in the multiprocessing directory. I still think it might be doable, as you could theoretically include the compiled library for the three different ST3 platforms, then put in some logic to determine what OS the user is running. However, I'm not as up to date on the Python internals as I would need to be to properly answer this question, so I'll defer to someone else on exactly how that could work.
Is there a standard way to make sure a python script will be interpreted by python2 and not python3? On my distro, I can use #!/usr/bin/env python2 as the shebang, but it seems not all distros ship "python2". I could explicitly call a specific version (eg. 2.6) of python, but that would rule out people who don't have that version.
It seems to me that this is going to be increasingly a problem when distros will start putting python3 as the default python interpreter.
http://docs.python.org/library/sys.html#sys.version_info
using the sys module you can determine the version of python that is running and raise an exception or exit or whatever you like.
UPDATE:
You could use this to call the appropriate interpreter. For example, set up a small script that does the checking for you, and use it in the shbang. It would check the python version running, and if not what you want, looks for one you want. Then it would run the script in that version of python (or fail if nothing good was found).
This is a bit of a messy issue during what will be a very long transition time period. Unfortunately, there is no fool-proof, cross-platform way to guarantee which Python version is being invoked, other than to have the Python script itself check once started. Many, if not most, distributions that ship Python 3 are ensuring the generic python command is aliased by default to the most recent Python 2 version while python3 is aliased to the most recent Python 3. Those distributions that don't should be encouraged to do so. But there is no guarantee that a user won't override that. I think the best practice available for the foreseeable future is to for packagers, distributors, and users to assume python refers to Python 2 and, where necessary, build a run-time check into the script.
Using sys.version_info you can do a simple value test against it. For example if you only want to support version 2.6 or lower:
import sys
if sys.version_info > (2,6):
sys.exit("Sorry, only we only support up to Python 2.6!")
Not quite the same situation, but the company I work for has an app that can run Python scripts (among its many features). After numerous support issues involving Python installations on various platforms, we decided to just install our own Python interpreter with the app. That way we know exactly where it is installed and what version it is. This approach may be too heavyweight for your needs (the Python package is only about 10% of our app's bits) but it definitely works.
Depends on how you're distributing it, I guess.
If you're using a normal setup.py file to manage your distribution, have it bomb out if the user is trying to install it in Python 3.
Once it's installed, the shebang of the console script created by (say) setuptools will likely be linked to the specific interpreter used to install it.
If you're doing something weird for your installation, you can in whatever installation script you're using look for python interpreters and store a choice. You might first check whether whatever is called "python" is a 2.x. If not, check for "python2.7", "python2.6", etc to see what's available.
As I understand different distros will be in different locations in your drive. Here are some suggestions that come to mind -
You could use UNIX alias to create shortcuts pointing to the different distros. Eg: alias py2="/usr/bin/python2.X". So when you run your script you could use py2 xx.py
Or other way could be to modify your PYTHON_PATH environment variable.
Or if I am not wrong there is a provision in sys module to get the current python version number. You could get that & deal appropriately.
This should do it...
You can use the autotools to pick a Python 2 interpreter. Here is how to do that. Guaranteeing a correct shebang may be tricky to do elegantly; here is one way to do that. It may be easier to simply have a light Bash wrapper script, wrapper.sh.in that looks something like:
#!/bin/bash
PYTHON2="#PYTHON#" #That first link enables this autotool variable
"$PYTHON2" "$#" #Call the desired Python 2 script with its arguments
Call wrapper.sh (after a ./configure) like:
./wrapper.sh my_python2_script.py --an_option an_argument
I believe this will do what you want, namely test for a non-specific version of Python less than 3.x (as long as it doesn't contain a from __future__ import print_function statement).
try:
py3 = eval('print')
except SyntaxError:
py3 = False
if py3: exit('requires Python 2')
...
It works by testing to see if print is a built-in function as opposed to a statement, as it is in Python3. When it's not a function, the eval() function will raise an exception, meaning the code is running on a pre-Python 3.0 interpreter with the caveat mentioned above.
I'm a .NET developer who knows very little about Python, but want to give it a test drive for a small project I'm working on.
What tools and packages should I install on my machine? I'm looking for a common, somewhat comprehensive, development environment.
I'll likely run Ubuntu 9.10, but I'm flexible. If Windows is a better option, that's fine too.
Edit: To clarify, I'm not looking for the bare minimum to get a Python program to run. I wouldn't expect a newbie .NET dev to use notepad and a compiler. I'd recommend Visual Studio, NUnit, SQL Server, etc.
Your system already has Python on it. Use the text editor or IDE of your choice; I like vim.
I can't tell you what third-party modules you need without knowing what kind of development you will be doing. Use apt as much as you can to get the libraries.
To speak to your edit:
This isn't minimalistic, like handing a .NET newbie notepad and a compiler: a decent text editor and the stdlib are all you really need to start out. You will likely need third-party libraries to develop whatever kind of applications you are writing, but I cannot think of any third-party modules all Python programmers will really need or want.
Unlke the .NET/Windows programming world, there is no one set of dev tools that stands above all others. Different people use different editors a whole lot. In Python, a module namespace is fully within a single file and project organization is based on the filesystem, so people do not lean on their IDEs as hard. Different projects use different version control software, which has been booming with new faces recently. Most of these are better than TFS and all are 1000 times better than SourceSafe.
When I want an interactive session, I use the vanilla Python interpreter. Various more fancy interpreters exist: bpython, ipython, IDLE. bpython is the least fancy of these and is supposed to be good about not doing weird stuff. ipython and IDLE can lead to strange bugs where code that works in them doens't work in normal Python and vice-versa; I've seen this first hand with IDLE.
For some of the tools you asked about and some others
In .NET you would use NUnit. In Python, use the stdlib unittest module. There are various third-party extensions and test runners, but unittest should suit you okay.
If you really want to look into something beyond this, get unittest2, a backport of the 2.7 version of unittest. It has incorporated all the best things from the third-party tools and is really neat.
In .NET you would use SQL Server. In Python, you may use PostgreSQL, MySQL, sqlite, or some other database. Python specifies a unified API for databases and porting from one to another typically goes pretty smoothly. sqlite is in the stdlib.
There are various Object Relational Models to make using databases more abstracted. SQLAlchemy is the most notable of these.
If you are doing network programming, get Twisted.
If you are doing numerical math, get numpy and scipy.
If you are doing web development, choose a framework. There are about 200000: Pylons, zope, Django, CherryPy, werkzeug...I won't bother starting an argument by recommending one. Most of these will happily work with various servers with a quick setting.
If you want to do GUI development, there are quite a few Python bindings. The stdlib ships with Tk bindings I would not bother with. There are wx bindings (wxpython), GTK+ bindings (pygtk), and two sets of Qt bindings. If you want to do native Windows GUI development, get IronPython and do it in .NET. There are win32 bindings, but they'll make you want to pull your hair out trying to use them directly.
In order to reduce the chance of effecting/hosing the system install of python, I typically install virtualenv on the ubuntu python install. I then create a virtualenv in my home directory so that subsequent packages I install via pip or easy_install do not effect the system installation. And I add the bin from that virtualenv to my path via .bashrc
$ sudo apt-get install python-virtualenv
$ virtualenv --no-site-packages ~/local
$ PATH=~/local/bin:$PATH #<----- add this to .bashrc to make it permanent
$ easy_install virtualenv #<--- so that project environments are based off your local environment rather than the system, probably not necessary
Install your favorite editor, I like emacs + rope, but editors are a personal preference and there are plenty of choices.
When I start a new project/idea I create a new virtual environment for that project, so that I don't effect dependencies anywhere else. Since I would hate for some of my projects to break due to an upgrade of a library both that project and the new one depends on.
~/projects $ virtualenv --no-site-packages my_new_project.env
~/projects/my_new_project.env $ source bin/activate
(my_new_project.env)~/projects/my_new_project.env $ easy_install paste ipython #whatever else I think I need
(my_new_project.env)~/projects/my_new_project.env $ emacs ./ & # start hacking
When creating a new package...in order to have something that will be easy_installable/pippable use paster create
(my_new_project.env)~/projects/my_new_project.env$ paster create new_package
(my_new_project.env)~/projects/my_new_project.env/new_package$ python setup.py develop new_package
That's the common stuff as far as I can think of it. Everything else would be editor/version control tool specific
Since I'm accustomed to Eclipse, I find Eclipse + PyDev convenient for Python. For quick computations, Idle is great.
I've used Python on Windows and on Ubuntu, and Linux is much cleaner.
If you launch a terminal and type python you'll get an interpreter, where you can start trying stuff.
Just in case you haven't seen it, check out the book Dive Into Python, is free on-line.
http://www.diveintopython.org/
Follow the examples in the book using the interpreter.
For storing your work you could use any editor; Vim or EMACS could be the most powerful, but also the most difficult to learn at first. If you want a more "traditional" IDE, you could try WingIDE.
http://www.wingware.com/
After you start to get more comfortable with python you should try an enhanced interpreter; try ipython.
http://ipython.scipy.org/moin/
When you start to develop a more serious project you'll need to get additional modules. Here you have two options; 1) Use your distribution tools to install additional modules; or 2) Download the modules you need directly from their sites and install them manually. You'll be responsible to upgrade them of course.
You'll have to decide for yourself which way to go. Personally I prefer to download and install additional modules manually.
Python (duh), setuptools or pip, virtualenv, and an editor. I suggest geany, but that's just me. And of course, any other Python modules you'll need.
Getting to Python from .NET world
Jumping into the Linux world from a .NET / WIndows background can be a bit disconcerting (but I do encourage you to keep trying Linux)
But I would suggest to anyone coming from Windows, to stick with Windows for a little while. goto www.Activestate.com and download their Python package - it includes the full win32com extentions by Mark Hammond and it also includes a complete, fast IDE "pythonwin"
I have done real professional development with just this setup alone on a windows box - one 14MB .msi and off you go !
Now to use Python on the DLR (Dynamic common language runtime) you need to download IronPython. THis is a seperate interpreter, that was also originally written by Mark Hammond at Microsoft and is at ironpython.org.
With this you can run code like (from wikipedia) ::
import clr
clr.AddReference("System.Windows.Forms")
from System.Windows.Forms import MessageBox
MessageBox.Show("Hello World")
Now you can access any .NET code from python.
If you're just starting out with Python, I'd actually argue against bringing in the complexity of virtualenv (which I think can be pretty overwhelming), at least until you've got a firm grasp of Python basics (especially regarding library/dependency management).
If you're using Ubuntu and the Gnome desktop environment, gedit is the default (gui) text editor, and has great support for Python built in. So my recommendation is to start with the pre-installed Python and gedit (which is pretty extensible on its own).
You don't need much. Python comes with "Batteries Included."
Visual Studio == IDLE. You already have it. If you want more IDE-like environment, install Komodo Edit.
NUnit == unittest. You already have it in the standard library.
SQL Server == sqlite. You already have it in the standard library.
Stop wasting time getting everything ready. It's already there in the basic Python installation.
Get to work.
Linux, BTW, is primarily a development environment. It was designed and built by developers for developers. Windows is an end-user environment which has to be supplemented for development.
Linux was originally focused on developers. All the tools you need are either already there or are part of simple yum or RPM installs.
You would probably like to give NetBeans Python IDE a shot. You can choose to use either Windows/Linux.
Database: sqlite (inbuilt). You might want SQLAlchemy though.
GUI: tcl is inbuilt, but wxPython or pyQt are recommended.
IDE: I use idle (inbuilt) on windows, TextMate on Mac, but you might like PyDev. I've also heard good things about ulipad.
Numerics: numpy.
Fast inline code: lots of options. I like boost weave (part of scipy), but you could look into ctypes (to use dlls), Cython, etc.
Web server: too many options. Django (plus Apache) is the biggest.
Unit testing: inbuilt.
Pyparsing, just because.
BeautifulSoup (or another good HTML parser).
hg, git, or some other nice VC.
Trac, or another bug system.
Oh, and StackOverflow if you have any questions.
Pycharm Community is worth to try.
I bought a low-end MacBook about a month ago and am finally getting around to configuring it for Python. I've done most of my Python work in Windows up until now, and am finding the choices for OS X a little daunting. It looks like there are at least five options to use for Python development:
"Stock" Apple Python
MacPython
Fink
MacPorts
roll-your-own-from-source
I'm still primarily developing for 2.5, so the stock Python is fine from a functionality standpoint. What I want to know is: why should I choose one over the other?
Update:
To clarify, I am looking for a discussion of the various options, not links to the documentation. I've marked this as a Community Wiki question, as I don't feel there is a "correct" answer. Thanks to everyone who has already commented for their insight.
One advantage I see in using the "stock" Python that's included with Mac OS X is that it makes deployment to other Macs a piece of cake. I don't know what your deployment scenario is, but for me this is important. My code has to run on any number of Macs at work, and I try to minimize the amount of work it takes to run my code on all of those systems.
I would highly recommend using MacPorts with Porticus for managing your Python installation. It takes a while to build everything, but the advantage is that whatever you build yourself will be built against the same libraries, so you won't have to futz around with statically linked shared objects, etc. if you want your Python stuff to work with Apache, PostgreSQL, etc.
If you choose to go this way, remember to install the python_select port and use it to make your system use the Python installed from MacPorts.
As an added bonus, MacPorts has packages for most main-stream Python eggs, so if you should be able to have MacPorts keep you up-to-date with the latest versions of all that stuff :)
Here's some helpful info to get you started. http://www.python.org/download/mac/
Depends what you are using python for. If you are using MacOS funitionality and things like PyObjC you are probably best of with MacPython or the python provided by Apple.
I use Python on my Mac mostly for development of server side applications which later will run on FreeBSD & Linux boxes. For that I have used fink python for a few years and ever since MacPorts python. With mac ports it is simple to add required c modules (like database driver etc). It's also easy to keep two python Versions (2.5 & 2.6 in my case) around.
I used "compile your own" python to test pre-3.0 python but generally I find managing dependencies to c modules painfull if done by hand.
Thanks to easy_install installing pure python modules is fast and easy for all the options mentioned above.
I was never very much an IDE person. For development I use command line subversion installed by MacPorts, Textmate and occasionaly Expandrive do directly access files on servers. I personally are very dependent on Bicyclerepairman for Textmade to handle my refactoring needs.
Others seem to be very happy with Eclipse & Pydev.
How about EPD from Enthought? Yes, it's large but it is a framework build and includes things like wxPython, vtk, numpy, scipy, and ipython built-in.
I recommend using Python Virtual environments, especially if you use a Timecapsule because Timecapsule will back everything up, except modules you added to Python!
Based on the number of bugs and omissions people have been encountering in Leopard python (just here on SO!), I couldn't recommend that version. e.g., see:
Why do I get wrong results for hmac in Python but not Perl?
Problems on select module on Python 2.5
I would choose MacPorts.
It does not eliminate your existing python supplied by Apple since it installs by default in /opt/local/bin (plays nice with it) and plus it is easy to download and install additional python modules (even binary modules that you need to compile!). I use Porticus GUI to maintain my MacPorts installed list of packages, including python.
In my windows environment I use Eclipse and PyDev, which works quite well together, even if it's a bit sparse. Apparently the exact same environment is available for the Mac as well, so I suggest downloading Eclipse and using the internal update software function to update PyDev with the URL http://pydev.sourceforge.net/updates/. To look further into PyDev, look here.
Apple's supplied python is quite old – my tiger install has 2.3.5. This may not be a problem for you, but you would be missing out on a lot. Also, there is a risk that Apple will update it. I'm not sure if moving from 2.3.5 to (say) 2.4 would cause code to break, but I guess it's possible. This happened to perl people recently: http://developers.slashdot.org/article.pl?sid=09/02/18/1435227
Macpython is a framework build (as is Apple's, I believe). To be honest, I'm not sure exactly what that means, but it's a prerequisite for some modules, in particular wxPython. If you get python from macports or fink, you will not be able to run wxPython (unless you run it through X11).
And guess what was forgotten by every answer here ... ActivePython.
No compilation required, even for third-party modules such as numpy, lxml, pyqt and thousands of others.
I recommend python (any python?) plus the ipython shell. My most recent experience with MacPython was MacPython 2.5, and I found IDLE frustrating to use as an editor. It's not very featureful, and its' very slow to scroll large quantities of output.