How do I set up a Python development environment on Linux?

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.

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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