This is somewhat a duplicate of easy_install/pip or apt-get.
For global Python packages, use either the Ubuntu Software Center, apt-get or synaptic
Ubuntu uses Python for many important functions, therefore interfering with Python can corrupt your OS. This is the main reason I never using pip on my Ubuntu system, but instead I use either Ubuntu Software Center, synaptic or apt-get, which all by default install packages from the Ubuntu repository. These packages are tested, usually pre-compiled so they install faster and ultimately designed for Ubuntu. In addition all required dependencies are also installed and a log of installs is maintained so they can be rolled back. I think most packages have corresponding Launchpad repos so you can file issues.
Another reason to use either Ubuntu packages is that sometimes these Python packages have different names depending on where you downloaded them from. Python-chardet is an example of a package which at one time was named one thing on PyPI and another thing in the Ubuntu repository. Therefore doing something like
pip install requests will not realize that chardet is already installed in your system because the Ubuntu version has a different name, and consequently install a new version which will corrupt your system in a minor insignificant way but still why would you do that.
In general you only want to install trusted code into your OS. So you should be nervous about typing
$ sudo pip <anything>.
Lastly some things are just easier to install using either Ubuntu packages. For example if you try
pip install numpy to install numpy & scipy unless you have already installed gfortran, atlas-dev, blas-dev and lapack-dev, you will see an endless stream of compile errors. However, installing numpy & scipy through the Ubuntu repository is as easy as...
$ sudo apt-get install python-numpy python-scipy
You are in luck, because you are using Ubuntu, one of the most widely supported and oft updated distributions existing. Most likely every Python package you will need is in the Ubuntu repository, and probably already installed on your machine. And every 6 months, a new cycle of packages will be released with the latest distribution of Ubuntu.
If you are 100% confident that the package will not interfere with your Ubuntu system in any way, then you can install it using pip and Ubuntu is nice enough to keep these packages separate from the distro packages by placing the distro packages in a folder called
dist-packages/. Ubuntu repository has both pip, virtualenv and setuptools. However, I second Wojciech's suggestion to use virtualenv.
For personal Python projects use pip and wheel in a virtualenv
If you need the latest version, or the module is not in the Ubuntu repository then start a virtualenv and use pip to install the package. Although pip and setuptools have merged, IMO pip is preferred over easy-install or distutils, because it will always wait until the package is completely downloaded and built before it copies it into your file system, and it makes upgrading or uninstalling a breeze. In a lot of ways it is similar to apt-get, in that it generally handles dependencies well. However you will have to handle some dependencies yourself, for example as mentioned above for NumPy and SciPy make sure you have installed gfortran, atlas-dev, blas-dev and lapack-dev from the Ubuntu repository.
~$ sudo apt-get install gfortran libblas-dev liblapack-dev libatlas-dev python-virtualenv
~$ mkdir ~/.venvs
~$ virtualenv ~/.venvs/my_py_proj
~$ source ~/.venvs/my_py_proj/bin/activate
~(my_py_proj)$ pip install wheel numpy scipy
Since you may end up installing these many times, consider using wheel with pip to create a wheelhouse
~(my_py_proj)$ pip wheel numpy scipy
This will create binary wheel files in
-d to specify a different directory. Now if you start another virtualenv and you need the same packages you've already built them and you can install them form your wheelhouse using
pip install --find-links=<fullpath>/wheelhouse
Read Installing Python Modules in the Python documentation and Get Packages on the Python Package Index main page. Also pip, virtualenv and wheel.