Develop Reference

How to install matplotlib for particular version of Python?

I have installed scipy and numpy, and they are being used with my current, desired version of python 2.7.6 (I am running on OSX Mavericks and had to upgrade.) However, when I pip installed matplotlib, by default it referenced my previous python version, 2.7.5, thus making it troublesome to use (obviously.)
How do I change which version of python matplotlib uses so I can import and use the library?
Thanks.

The way I would solve this problem is like this, firstly one would need to go into your 2.7.6 directory, and under the Scripts folder you will find the pip executable. My suggestion is (because its difficult to debug this kind of people without having all the details) is this:
./pip install matplotlib
And see if this succeeds, otherwise, I suggest using pyenv to manage your python installations.

I suggest you use Macports for installing additional Python versions on OS X. Once Macports is installed, it's fairly easy to install Python 2.7.6. All you'd have to do is:
sudo port install python27
Now, you should be able to get all the libraries you need just as easily, using, too, Macports.
sudo port install py27-numpy
sudo port install py27-scipy
sudo port install py27-matplotlib
Macports should solve all the dependencies and, of course, link the packages to their correct Python versions, avoiding you a lot of headaches.
For a step by step guide on how to set up a nice, functional Python environment, visit: http://jakevdp.github.io/blog/2013/02/02/setting-up-a-mac-for-python-development/

What is best option from pip, pythontools or easy-install

I am looking for the best option to keep my Python upgraded and to install new packages. I know there was previous discussion like this: Why use pip over easy_install? but they often quite old.
The problem is: I have ubuntu 12.04 at home and Windows 7 at work, would like to keep both of them on the same (newest) version level.
In ubuntu I found that repository contains often old version so I use different procedures to install new packages. I also found that pip installs new version, but did not check other options. In windows I try to install from provided .exe files which sometimes is difficult, and to have ipython working I had to install pythontools. Over the internet I see a lot of opinion about the subject, and advocates to different tools.
Is there a way to keep to different computers (ubuntu/windows) upgraded on the same level and what is the best choice.
I am looking for a constructive opinions like: if you use ... then you don't have to add paths manually but you need to clean downloaded files, or this ... will work perfectly on linux but for the reason ... not on windows.
I would like to use it in ubuntu 12.04 and Windows 7

I'm not sure about Windows. I think people like pip because it does dependencies better than easy_install. But I don't know enough about that to say more. Using virtualenv is a great choice in that it keeps your projects versions. You can also to pip freeze > requirements.txt to get a list of packages you installed within virtual env. This file can then be used to download those versions in another virtualenv. virtualenv installs its own local pip

If someone has problem with installation basic packages under windows this http://viziblr.com/news/2012/4/21/step-by-step-installing-pandas-on-windows-7-from-pypi-with-e.html gives good help. It works well in windows, although does it does not resolve the issue.

What's the proper way to update Python packages when updating Python from 2.6 to 2.7?

I've installed A LOT of python packages for Python 2.6. Now I would like to upgrade Python to 2.7. Is there a proper or systematic way to update all the installed packages?
In my system, all the packages are installed at
/usr/lib64/python2.6/site-packages/ and
/usr/lib/python2.6/site-packages/
One obvious way is to install Python 2.7, download all the package sources or egg files, and re-install them one by one. However, Some useful packages like numpy and scipy are notorious for installation, especially when one needs to install from source. I expect I'll need to spend several hours to find the packages and solve the installation problems here and there.
Anyone has any suggestions on systematically update the installed packages?

First, you should not never ever ever ever install Python packages in in system library folder with easy_install using sudo on any operating system.
http://jamiecurle.co.uk/blog/installing-pip-virtualenv-and-virtualenvwrapper-on-os-x/#comment-573429347
The correct procedure would be make your installation procedure repeatable. There exist two commonly used solutions in Python world. These solutions automatically download correct versions of Python packages from http://pypi.python.org
PIP
pip and requirements.txt http://www.pip-installer.org/en/latest/requirements.html within virtualenv http://pypi.python.org/pypi/virtualenv
Buidout
Buildout, example from Plone CMS https://github.com/plone/Installers-UnifiedInstaller/blob/master/base_skeleton/versions.cfg
Buildout can also do configure, make, make install style installations for packages which need native libraries. For example there exist solution for libxml2 + lxml
http://pypi.python.org/pypi/z3c.recipe.staticlxml/
(Note: buildout does not need virtualenv as it does its own isolation from system Python)

What is the best way to install python 2 on OS X?

A colleague of mine wants to use my python 2 code on his OS X (10.6) machine. My code imports several built-in python packages, including Tkinter and shelve, and also uses third-party packages, including numpy, scipy, matplotlib, and ipython.
I've encountered a few problems with OS X's built-in python. (IDLE doesn't work, for example*). I suspect I should install a more recent version of python, and a different version of Tk.
My questions:
Will having two different versions of python/Tk on the same machine cause problems?
I would like to associate the terminal commands 'python', 'ipython', and 'easy_install' with the more recent version of python. How should I do this?
When I install third-party packages like numpy using a .dmg file, how do I control which version of python numpy installs into?
Is there a better way to do this?
If this process goes well, I'd consider adding OS X instructions to my code's documentation, so I'd like to boil down this process to the simplest, most general approach.
*EDIT: Also, this
EDIT: Thank you everyone for the useful answers. My colleague tried MacPorts, which seems to work well, but has a few speedbumps. First we had to install Xcode from the system install disk. This is not a fast or lightweight install (several GB). Luckily we still had the disk! Once Xcode was installed, MacPorts was easy to install. Python and the python subpackages we needed were also easy to install, but he told me this installation took several hours. Presumably this delay is due to compilation? He had an easy time setting the MacPorts python as default. However, I think we have to change the 'Python Launcher' application by hand, this seems to still default to the system python.
Even though he has a working system now, I'm tempted to ask him to try one of the other solutions. I'm not sure all of my code's potential users will tolerate a multi-hour, multi-gigabyte installation.

I use brew to install all my libraries/compilers/interpreters.
To install python try this:
brew install python
Then add Python's binaries directory to your $PATH in your ~/.profile:
export PATH=`brew --prefix python`/bin:$PATH
I'd recommend you to install pip, virtualenv and virtualenvwrapper to have better control over your environment too.

Have you tried ActivePython?
It includes a package manager (PyPM) that, by default, installs into your home directory (eg: ~/Library/Python/2.7). Main scripts get symlinked in /usr/local/bin; use the included pythonselect to set the active Python version.
You don't have to bother installing .dmg packages, as PyPM is a binary package manager ... therefore you can install non-pure Python packages like NumPy without having to compile things yourself.
ActivePython can use Apple's Tcl/Tk or, if installed, ActiveTcl.
A "simplest, most general approach" in your documentation could be:
Install ActivePython 2.7
Open Terminal and type pypm-2.7 install matplotlib ipython

Using MacPorts, you can install python 2.6, 2.7, 3.1 and 3.2 at the same time, with their own packages, without ever touching the built-in python.
numpy, scipy, matplotlib, and ipython are also available as ports for most of those python versions.
Moreover, if you install the python_select port, you'll be able:
to choose which one of those (plus the built-in python) is the "default" python;
to install python packages through easy_install/pip for the "selected" python, if they're not available as ports.
Add virtualenv to the mix, and you'll have a very, very flexible Python development environment.
As for your questions:
Q1: with MacPorts, no. while not a frequent user, I've installed and used matplotlib in 2.6 and 2.7, switching between the two using python_select.
Q2: easy_install, pip, ipython will be "linked" to the python they were installed by. (but see tip 1)
Q3: it's easier to install one of the py{26,27,xx}-numpy ports, or pip install numpy under your python_select'ed python.
Q4: well, MacPorts is the best thing I know after APT on Debian/Ubuntu... :-)
Now, two tips if you try MacPorts:
MacPorts cleanly installs ports separately from the OS X installation, in an /opt/local directory, and each python version is installed in a /opt/local/Library/Frameworks/Python.framework/Versions/{2.5,2.6,2.7,...} directory. Using python_select cleanly switch the "python" command using links. BUT... the Versions/{2.5,2.6,2.7,...}/bin directory, where python scripts are installed, is not added to the PATH. Just adding: export PATH=/opt/local/Library/Frameworks/Python.framework/Versions/Current/bin:$PATH to your ~/.profile will always give you direct access to the scripts installed for the selected python.
to avoid bad surprises, I've added a echo Selected python is \"$(python_select -s)\" line to my ~/.profile, so I always know which is my currently selected python when opening a session... :-)
Regards,
Georges

In almost all cases, the best python to use is the one from http://python.org/. It sets up the paths correctly and doesn't overwrite anything. DMG package installs usually work automatically, as does python setup.py install, and it's not too hard to get setuptools to work. If you want per-user installs, it is easy to set up .pydistutils.cfg and python automatically recognizes the path install_lib = ~/Library/Python/$py_version_short/site-packages

An addendum regarding the usage of brew:
Since some time, brew install python will install python3.
If you intend to install python2, you want to use
brew install python#2
It is perfectly fine to install both python and python3 using brew!

Here is an old post that answers your questions too.
In general it is not a problem at all to have more than one python installation on your machine. You just have to watch out which one you are calling on the command line.
>> which python
... helps to identify where your python binary is located. The original Mac OS X python is usually at "/usr/bin/python"
I personally use the MacPorts python installation. It also supports you with the installation of modules. (see link above)

I have 4 versions of python on my MacBook Pro. 2 from the original install of OS X 10.6 and a subsequent update, then self installed copies of python 2.7 and 3.2. You can update the python command to point at any of the versions. They all install in separate directories and cause no problems with each other.
I'm not sure what will happen when you install from a .dmg file. I believe it will simply use whatever version python points to.
This post on superuser.com answers your questions on changing default paths.

What is the most compatible way to install python modules on a Mac?

I'm starting to learn python and loving it. I work on a Mac mainly as well as Linux. I'm finding that on Linux (Ubuntu 9.04 mostly) when I install a python module using apt-get it works fine. I can import it with no trouble.
On the Mac, I'm used to using Macports to install all the Unixy stuff. However, I'm finding that most of the python modules I install with it are not being seen by python. I've spent some time playing around with PATH settings and using python_select . Nothing has really worked and at this point I'm not really understanding, instead I'm just poking around.
I get the impression that Macports isn't universally loved for managing python modules. I'd like to start fresh using a more "accepted" (if that's the right word) approach.
So, I was wondering, what is the method that Mac python developers use to manage their modules?
Bonus questions:
Do you use Apple's python, or some other version?
Do you compile everything from source or is there a package manger that works well (Fink?).

The most popular way to manage python packages (if you're not using your system package manager) is to use setuptools and easy_install. It is probably already installed on your system. Use it like this:
easy_install django
easy_install uses the Python Package Index which is an amazing resource for python developers. Have a look around to see what packages are available.
A better option is pip, which is gaining traction, as it attempts to fix a lot of the problems associated with easy_install. Pip uses the same package repository as easy_install, it just works better. Really the only time use need to use easy_install is for this command:
easy_install pip
After that, use:
pip install django
At some point you will probably want to learn a bit about virtualenv. If you do a lot of python development on projects with conflicting package requirements, virtualenv is a godsend. It will allow you to have completely different versions of various packages, and switch between them easily depending your needs.
Regarding which python to use, sticking with Apple's python will give you the least headaches, but If you need a newer version (Leopard is 2.5.1 I believe), I would go with the macports python 2.6.

Your question is already three years old and there are some details not covered in other answers:
Most people I know use HomeBrew or MacPorts, I prefer MacPorts because of its clean cut of what is a default Mac OS X environment and my development setup. Just move out your /opt folder and test your packages with a normal user Python environment
MacPorts is only portable within Mac, but with easy_install or pip you will learn how to setup your environment in any platform (Win/Mac/Linux/Bsd...). Furthermore it will always be more up to date and with more packages
I personally let MacPorts handle my Python modules to keep everything updated. Like any other high level package manager (ie: apt-get) it is much better for the heavy lifting of modules with lots of binary dependencies. There is no way I would build my Qt bindings (PySide) with easy_install or pip. Qt is huge and takes a lot to compile. As soon as you want a Python package that needs a library used by non Python programs, try to avoid easy_install or pip
At some point you will find that there are some packages missing within MacPorts. I do not believe that MacPorts will ever give you the whole CheeseShop. For example, recently I needed the Elixir module, but MacPorts only offers py25-elixir and py26-elixir, no py27 version. In cases like these you have:
pip-2.7 install --user elixir
( make sure you always type pip-(version) )
That will build an extra Python library in your home dir. Yes, Python will work with more than one library location: one controlled by MacPorts and a user local one for everything missing within MacPorts.
Now notice that I favor pip over easy_install. There is a good reason you should avoid setuptools and easy_install. Here is a good explanation and I try to keep away from them. One very useful feature of pip is giving you a list of all the modules (along their versions) that you installed with MacPorts, easy_install and pip itself:
pip-2.7 freeze
If you already started using easy_install, don't worry, pip can recognize everything done already by easy_install and even upgrade the packages installed with it.
If you are a developer keep an eye on virtualenv for controlling different setups and combinations of module versions. Other answers mention it already, what is not mentioned so far is the Tox module, a tool for testing that your package installs correctly with different Python versions.
Although I usually do not have version conflicts, I like to have virtualenv to set up a clean environment and get a clear view of my packages dependencies. That way I never forget any dependencies in my setup.py
If you go for MacPorts be aware that multiple versions of the same package are not selected anymore like the old Debian style with an extra python_select package (it is still there for compatibility). Now you have the select command to choose which Python version will be used (you can even select the Apple installed ones):
$ port select python
Available versions for python:
none
python25-apple
python26-apple
python27 (active)
python27-apple
python32
$ port select python python32
Add tox on top of it and your programs should be really portable

Please see Python OS X development environment. The best way is to use MacPorts. Download and install MacPorts, then install Python via MacPorts by typing the following commands in the Terminal:
sudo port install python26 python_select
sudo port select --set python python26
OR
sudo port install python30 python_select
sudo port select --set python python30
Use the first set of commands to install Python 2.6 and the second set to install Python 3.0. Then use:
sudo port install py26-packagename
OR
sudo port install py30-packagename
In the above commands, replace packagename with the name of the package, for example:
sudo port install py26-setuptools
These commands will automatically install the package (and its dependencies) for the given Python version.
For a full list of available packages for Python, type:
port list | grep py26-
OR
port list | grep py30-
Which command you use depends on which version of Python you chose to install.

I use MacPorts to install Python and any third-party modules tracked by MacPorts into /opt/local, and I install any manually installed modules (those not in the MacPorts repository) into /usr/local, and this has never caused any problems. I think you may be confused as to the use of certain MacPorts scripts and environment variables.
MacPorts python_select is used to select the "current" version of Python, but it has nothing to do with modules. This allows you to, e.g., install both Python 2.5 and Python 2.6 using MacPorts, and switch between installs.
The $PATH environment variables does not affect what Python modules are loaded. $PYTHONPATH is what you are looking for. $PYTHONPATH should point to directories containing Python modules you want to load. In my case, my $PYTHONPATH variable contains /usr/local/lib/python26/site-packages. If you use MacPorts' Python, it sets up the other proper directories for you, so you only need to add additional paths to $PYTHONPATH. But again, $PATH isn't used at all when Python searches for modules you have installed.
$PATH is used to find executables, so if you install MacPorts' Python, make sure /opt/local/bin is in your $PATH.

There's nothing wrong with using a MacPorts Python installation. If you are installing python modules from MacPorts but then not seeing them, that likely means you are not invoking the MacPorts python you installed to. In a terminal shell, you can use absolute paths to invoke the various Pythons that may be installed. For example:
$ /usr/bin/python2.5 # Apple-supplied 2.5 (Leopard)
$ /opt/local/bin/python2.5 # MacPorts 2.5
$ /opt/local/bin/python2.6 # MacPorts 2.6
$ /usr/local/bin/python2.6 # python.org (MacPython) 2.6
$ /usr/local/bin/python3.1 # python.org (MacPython) 3.1
To get the right python by default requires ensuring your shell $PATH is set properly to ensure that the right executable is found first. Another solution is to define shell aliases to the various pythons.
A python.org (MacPython) installation is fine, too, as others have suggested. easy_install can help but, again, because each Python instance may have its own easy_install command, make sure you are invoking the right easy_install.

If you use Python from MacPorts, it has it's own easy_install located at: /opt/local/bin/easy_install-2.6 (for py26, that is). It's not the same one as simply calling easy_install directly, even if you used python_select to change your default python command.

Have you looked into easy_install at all? It won't synchronize your macports or anything like that, but it will automatically download the latest package and all necessary dependencies, i.e.
easy_install nose
for the nose unit testing package, or
easy_install trac
for the trac bug tracker.
There's a bit more information on their EasyInstall page too.

For MacPython installations, I found an effective solution to fixing the problem with setuptools (easy_install) in this blog post:
http://droidism.com/getting-running-with-django-and-macpython-26-on-leopard
One handy tip includes finding out which version of python is active in the terminal:
which python

When you install modules with MacPorts, it does not go into Apple's version of Python. Instead those modules are installed onto the MacPorts version of Python selected.
You can change which version of Python is used by default using a mac port called python_select. instructions here.
Also, there's easy_install. Which will use python to install python modules.

You may already have pip3 pre-installed, so just try it!

Regarding which python version to use, Mac OS usually ships an old version of python. It's a good idea to upgrade to a newer version. You can download a .dmg from http://www.python.org/download/ . If you do that, remember to update the path. You can find the exact commands here http://farmdev.com/thoughts/66/python-3-0-on-mac-os-x-alongside-2-6-2-5-etc-/

I use easy_install with Apple's Python, and it works like a charm.

Directly install one of the fink packages (Django 1.6 as of 2013-Nov)
fink install django-py27
fink install django-py33
Or create yourself a virtualenv:
fink install virtualenv-py27
virtualenv django-env
source django-env/bin/activate
pip install django
deactivate # when you are done
Or use fink django plus any other pip installed packages in a virtualenv
fink install django-py27
fink install virtualenv-py27
virtualenv django-env --system-site-packages
source django-env/bin/activate
# django already installed
pip install django-analytical # or anything else you might want
deactivate # back to your normally scheduled programming