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.
Related
I'm working in the VFX industry and we deal with different software packages that ship with their own Python interpreter. We are running on Linux and use modules to handle our environments to make sure that people are using the correct version of all applications depending on the project they are working on.
Since months, we are trying to setup an environment that supports multiple versions of Python. And what is blocking right now are additional Python libraries that we are using in our in-house tools, like sqlalchemy, psycopg2, openpyxl, zmq, etc.
So far, for each project, we have config file that defines the version of each package to be use including the additional Python modules. And to use the correct Python version of each Python module, we look up the main Python interpreter defined in that same modules definition file. This works as long as the major and minor versions of all Python interpreters do line up.
But now, I would like to start an application that ships with a Python 3.7 interpreter and another application with a Python 3.9 interpreter and so on. All applications do you use our in-house tools which need the additional Python modules. Of course, this fails when trying to import any additional module.
For now, the only solution that I see is to install the corresponding Python modules in the 'site-packages' of each application that comes with its own Python interpreter. That should work. But this means that we have to install for each application version all necessary Python modules (ideally, the same version of it to avoid compatibility issues) and when we decide to update one of them, this needs to be done again for all 3rd party applications.
That does not sound super-efficient to me.
Do you have similar experiences and what did you came up with to handle this? I know, that there are more advanced packages like rez to handle complex environment setups, but although I do not know the details of rez, I could imagine that the problems stays the same. I guess that it is not possible to globally populate PYTHONPATH with additional modules so that it works on multiple Python interpreter versions.
Another solution that I could imagine is to make sure that on startup of each application that needs additional Python modules, we do our own sys.path modification depending on the interpreter version. That would imply some coding but we could keep a global version handling without installing them everywhere.
Anyway, if you have any further hints, please let me know.
Greets,
Carlo
My friends usually ask me which Python IDE is easier to use, and I don't have an answer for them, because depending on their platform, package management could be a headache. Today I tried looking for a Python IDE with some kind of integrated package management system (e.g. PIP) that asks user if they like the IDE search online repositories for the missing package, and just install it--like the way their favorite TeX editor does.
So, do you know if such an IDE exists? If not, do you have any idea why?
Well, if you deal with Django development, I think you should definitely check out sourceLair which offers integration with pip. You just right click on your requirements.txt file, select install dependencies and you're done.
Currently, you cannot search for pip packages but I suppose this could be a future feature.
I think it mostly has to do with python packaging hate. Binary package management is very important to Windows users (of which Python has many, because they don't treat Windows as a second class platform), and building many C extensions with distutils on Windows often just doesn't work (try 'pip install numpy' on Windows, for instance). The state of "packaging" in python is confusing in general; I would say that's the primary reason nobody (that I know of) has gone thru the effort of integrating the existing tools into their IDEs.
As an aside, if you want something free and are familiar with eclipse, I recommend pydev.
After using C# for long time I finally decided to switch to Python.
The question I am facing for the moment has to do about auto-complete.
I guess I am spoiled by C# and especially from resharper and I was expecting something similar to exist for Python.
My editor of choice is emacs and after doing some research I found autocomplete.pl, yasnippet and rope although it is not clear to me if and how they can be installed in a cygwin based system which is what I use since all the related documentation appears to be linux specific...
The version of emacs I currently use is 23.2.1 which bundles the python mode that although useful is far behind from whatever research has to offer.
My question to python users has to do about how common is autocomplete vs manual typing (using M-/ where possible) ?
I am thinking about just memorizing python build-in functions like len, append, extend etc. and revert close to a pre-autocomplete editing mode. How different such an approach is from what other pythonistas are doing?
I found this post
My Emacs Python environment
to be the most useful and comprehensive list of instructions and references on how to setup a decent Python development environment in Emacs regardless of OS platform. It is still a bit of work to setup but at least it covers the popular packages and components generally recommended for Python in Emacs that provide auto-completion functionality.
I loosely used this post as a guide to do the setup on my Windows machine with Emacs 23.2.1 and Python 2.6.5. Although, I also have Cygwin installed in some cases instead of running the *nix shell commands mentioned in the post, I just download the packages via a web browser, unzip them with 7zip, and copy them to my Emacs' plugin directory.
Also, to install Pymacs, Rope, and Ropemacs, I used Python's EasyInstall package manager. To use it, I downloaded and installed the setuptools package using the Windows install version. Once installed, at the command line, cd to their respective download locations and run the command
easy_install .
instead of the shell commands shown in the post.
Generally, I saved any *.el files in my ~\.emacs.d\plugins (e.g. in %USERPROFILE%\Application Data\.emacs.d\) and then updated my .emacs file to reference them as documented in the post.
Despite all this, on occasion, I've used DreamPie since it does have overall better auto-completion out of the box than my Emacs setup.
I'm spoiled by Intellisense too. The PyDev extensions for Eclipse offer a pretty good auto-complete substitute.
I find that PyDev + Eclipse can meet most of my needs. There is also PyCharm from the Intellij team. PyCharm has the added advantage of smooth integration with git.
I've been using PyScripter, an IDE for Windows, for a while now, and have found it very good. It has autocompletion among many other features. It's written in Delphi -- not that there's anything wrong with that -- it just bothers me a bit, though...
Take a look at Spyderlib, support most of the features including code completion
IMO, by far the easiest way to take advantage of the python tools available for emacs is to take advantage of the defaults that are all set up at:
https://github.com/gabrielelanaro/emacs-for-python
I actually took the time to get pymacs and ropemacs and python-mode all working independently before finding that little gem, and now I rely on it entirely for all my python based customizations. If you are new, I would definitely start there.
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.
I've got a python project I've been making in terminal with vim etc.. I've read that XCode supports Python development at that it supports SVN (which I am using) but I can't find documentation on how to start a new XCode project from an existing code repository.
Other developers are working on the project not using XCode - They won't mind if I add a project file or something, but they will mind if I have to reorganise the whole thing.
I don't think it's worth using Xcode for a pure python project. Although the Xcode editor does syntax-highlight Python code, Xcode does not give you any other benefit for writing a pure-python app. On OS X, I would recommend TextMate as a text editor or Eclipse with PyDev as a more full-featured IDE.
I recommend against doing so. Creating groups (which look like folders) in Xcode doesn't actually create folders in the filesystem. This wreaks havoc on the module hierarchy.
Also, the SCM integration in Xcode is very clunky. After becoming accustomed to using Subversion with Eclipse, the Subversion support in Xcode is hopelessly primitive. It's almost easier to just do svn commands on the command line just so it's clear what's going on.
If you must use Xcode, use it to open individual py files. Use it as a slow, relatively featureless text editor.
If you must use Xcode for SCM, take a look at their guide to using Xcode with Subversion.
There are no special facilities for working with non-Cocoa Python projects with Xcode. Therefore, you probably just want to create a project with the "Empty Project" template (under "Other") and just drag in your source code.
For convenience, you may want to set up an executable in the project. You can do this by ctrl/right-clicking in the project source list and choosing "Add" > "New Custom Executable...". You can also add a target, although I'm not sure what this would buy you.
Also see:
http://lethain.com/entry/2008/aug/22/an-epic-introduction-to-pyobjc-and-cocoa/