How to install numpy and matplotlib in the right python version?

Question

I'm trying to install numpy, matplotlib, and scipy in the right python version.

Initially I was testing with different python versions (3.2, 2.7, 2.6).

I removed all these versions using: How to uninstall Python 2.7 on a Mac OS X 10.6.4?

Afterwards, I reinstalled Python 2.7.11. when I try to install numpy, matplotlib and scipy, using pip, I get the following message: Requirement already satisfied (use --upgrade to upgrade) ...

In my terminal, I tried the following:

$ which python
/Library/Frameworks/Python.framework/Versions/2.7/bin/python

$ python
Python 2.7.11 (v2.7.11:.....)
.....
>>> import numpy
ImportError: No module named numpy

$ /System/Library/Frameworks/Python.framework/Versions/2.7/bin/python
Python 2.7.10 (default, ......
.....
>>> import numpy
>>> numpy.__version__
'1.8.0rc1'

for some reason these packages got installed in 2.7.10 and not 2.7.11, which is the version I downloaded from python.org. Also, I don't even know how I got the 2.7.10 version.

How can I fix this issue?

Answer 1

You can also use macports (https://www.macports.org/) to install different versions of python, numpy, and matplotlib. It's really quite simple.

Alternatively, you can perhaps use anaconda (https://www.continuum.io/downloads), which uses conda, to achieve your goal.

Answer 2

I recommend using virtualenv (with virtualenvwrapper: https://virtualenvwrapper.readthedocs.org). It is very easy to setup and you'll have absolutely no problems in future when you deal with multiple Python installations.

I work with virtualenv for years now and create for each project a separate virtual environment, which is always clean and I never have to deal with PATH, PYTHONPATH or whatever.

If you followed the virtualenvwrapper installation guide, you can simply create for example one virtualenv for everyday work via:

mkvirtualenv common -p /Library/Frameworks/Python.framework/Versions/2.7/bin/python

this will create the virtualenv and automatically activate it, so you can instantly install the packages you want:

pip install matplotlib numpy scipy

and every time you want to use it you type:

workon common

As you see above, you can specify the python executable via the -p flag. Each virtualenv will be a completely fresh and independent Python installation where you can use pip to install whatever you want (without root access of course).