Reputation: 1209
I have some experience with C++
and Fortran
, and I want to start using python
for my post-processing as I am starting to realise how inefficient MATLAB
is for what I need to do (mostly involves plots with millions of points).
I already had a few versions of python
installed, from every time I wanted to start using. It has now become a mess. In /usr/local/bin/
, here is what the command ls python*
returns:
python python2.7 python3 python3.5 python3.5m pythonw-32
python-32 python2.7-32 python3-32 python3.5-32 python3.5m-config pythonw2.7
python-config python2.7-config python3-config python3.5-config pythonw pythonw2.7-32
I now want a clean slate. I want a safe way to remove all the previous versions of python
, including all of their packages, so I can just install the latest version and import all the libraries I want like numpy
and matplotlib
smoothly (I had some issues with that).
EDIT:
I am running on OSX Yosemite 10.10.
Upvotes: 11
Views: 62271
Reputation: 14801
Do not uninstall your system's Python interpreter (Python 2.7 most probably). You might consider uninstalling the other version (Python 3.5 most probably), but I do not think you really need to do that (it may not be a bad idea to keep a system-wide Python 3 interpreter... who knows!).
If you want a clean state I would recommend you to use virtual environments for now on. You have two options:
virtualenv
and pip
to setup your virtual environments and packages. However, using pip
means you will have to compile the packages that need compilation (numpy
, matplotlib
and many other scientific Python packages that you may use for your "post-processing").Also, you say you are feeling MATLAB is inefficient for plotting millions of points. I do not know your actual needs/constraints, but I find Matplotlib to be very inefficient for plotting large data and/or real-time data.
Just as a suggestion, consider using PyQtGraph. If you still feel that is not fast enough, consider using VisPy (probably less functional/convenient at the moment, but more efficient).
Upvotes: 9