如何在Ubuntu16.04中安装pylab？

Question

(GWAVA) wangshx@wangshx-KVM:~/GWAVA_v1.0/src$ python gwava_paper.py Traceback (most recent call last): File "gwava_paper.py", line 19, in <module> from gwava import * File "/home/wangshx/GWAVA_v1.0/src/gwava.py", line 21, in <module> import pylab as pl ImportError: No module named pylab How can I install pylab module, I search it and find that it is a part of matplotlib , but I don't know which version of matplotlib I should install. I try to install the newest version, it reminds me to update many module version. But I need to control the version of modules.

When I run a python scripts written by others, I controlled module version by creating a new environment using Anaconda .

This is the scripts documentation.

The software requires the following python libraries (and their 
associated dependencies) to be installed. The version numbers used
are identified, other versions may also work, but results may be 
slightly different.

- numpy (1.7.0)
- scipy (0.11.0)
- pandas (0.12.0)
- scikit-learn (0.14.1)
- pybedtools (0.6.4)
- tabix (0.2.5)

I installed all module in the README .

(GWAVA) wangshx@wangshx-KVM:~/GWAVA_v1.0/src$ conda list
dateutil                  2.4.1                    py27_0    https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free
libgfortran               1.0                           0    https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free
mkl                       2017.0.1                      0    https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free
nose                      1.3.7                    py27_1    https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free
numpy                     1.7.0                    py27_0    https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free
openssl                   1.0.2l                        0    defaults
pandas                    0.12.0               np17py27_0    https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free
pip                       9.0.1                    py27_1    defaults
pybedtools                0.6.4                     <pip>
python                    2.7.13                        0    defaults
python-dateutil           2.6.0                    py27_0    https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free
pytz                      2017.2                   py27_0    https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free
readline                  6.2                           2    defaults
scikit-learn              0.14.1               np17py27_1    https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free
scipy                     0.11.0               np17py27_3    https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free
setuptools                27.2.0                   py27_0    defaults
six                       1.10.0                   py27_0    https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free
sqlite                    3.13.0                        0    defaults
tabix                     1.0                       <pip>
tk                        8.5.18                        0    defaults
wheel                     0.29.0                   py27_0    defaults
zlib                      1.2.8                         3    defaults

Any help?

Answer 1

virtualenv is the usual way to avoid the library versioning problem with Python.

From the documentation:

virtualenv is a tool to create isolated Python environments.

The basic problem being addressed is one of dependencies and versions, and indirectly permissions. Imagine you have an application that needs version 1 of LibFoo, but another application requires version 2. How can you use both these applications? If you install everything into /usr/lib/python2.7/site-packages (or whatever your platform's standard location is), it's easy to end up in a situation where you unintentionally upgrade an application that shouldn't be upgraded.

Or more generally, what if you want to install an application and leave it be? If an application works, any change in its libraries or the versions of those libraries can break the application.

Answer 2

I use conda search matplotlib to find all the version of matplotlib .

          1.2.1                np17py33_0  defaults        
                         1.2.1                np16py26_1  defaults        
                         1.2.1                np16py27_1  defaults        
                         1.2.1                np17py26_1  defaults        
                         1.2.1                np17py27_1  defaults        
                         1.2.1                np17py33_1  defaults        
                         1.3.0                np16py26_0  defaults        
                         1.3.0                np16py27_0  defaults        
                         1.3.0                np17py26_0  defaults        
                         1.3.0                np17py27_0  defaults        
                         1.3.0                np17py33_0  defaults        
                         1.3.1                np16py26_0  defaults        
                         1.3.1                np16py27_0  defaults        
                         1.3.1                np17py26_0  defaults        
                         1.3.1                np17py27_0  defaults        
                         1.3.1                np17py33_0  defaults 

And choose one version (such as 1.3.0) that seems support the numpy17 . It works after installing 1.3.0 version of matplotlib !