anaconda是否为每个新环境创建单独的PYTHONPATH变量?

I am starting to work with the Anaconda package from Continuum.io to do scipy work. I have been able to get anaconda up and running, but I cannot tell whether anaconda creates a new PYTHONPATH environment variable for each new environment it creates, or whether it relies on the common system PYTHONPATH? I could not find any information on this in the documentation. Further, when I did a printenv, I did not see a PYTHONPATH variable in the newly created environment--though I did find a few new anaconda created environment variables. The best I can find is that anaconda added some anaconda directories and the new environment directory to the head of PATH variable--but this does not necessarily isolate the new package from the system environment but it is close. Does anyone know the answer to this question or found a way to deal with this concern.

我开始使用连续体的Anaconda包。做scipy工作。我已经能够启动和运行anaconda，但是我无法判断anaconda是否为它创建的每个新环境创建了一个新的PYTHONPATH环境变量，或者它是否依赖于公共系统PYTHONPATH?我在文件中找不到有关这方面的任何资料。此外，当我执行printenv时，我在新创建的环境中没有看到PYTHONPATH变量——尽管我确实发现了一些新的anaconda创建的环境变量。我能找到的最好的方法是，anaconda将一些anaconda目录和新的环境目录添加到PATH变量的头部，但这并不一定会将新包与系统环境隔离开来，但它是关闭的。有人知道这个问题的答案吗?或者找到了解决这个问题的方法。

2 个解决方案

#1

No, the only thing that needs to be modified for an Anaconda environment is the PATH (so that it gets the right Python from the environment bin/ directory, or Scripts\ on Windows).

不，对于Anaconda环境，惟一需要修改的是路径(以便它从环境bin/目录中获得正确的Python，或者在Windows上获得脚本)。

The way Anaconda environments work is that they hard link everything that is installed into the environment. For all intents and purposes, this means that each environment is a completely separate installation of Python and all the packages. By using hard links, this is done efficiently. Thus, there's no need to mess with PYTHONPATH because the Python binary in the environment already searches the site-packages in the environment, and the lib of the environment, and so on.

Anaconda环境的工作方式是将安装到环境中的所有东西都硬链接起来。对于所有意图和目的，这意味着每个环境都是一个完全独立的Python和所有包的安装。通过使用硬链接，这是有效的。因此，没有必要对PYTHONPATH进行混乱，因为环境中的Python二进制文件已经在环境中搜索了站点包，以及环境的lib，等等。

#2

Anaconda does not use the PYTHONPATH. One should however note that if the PYTHONPATH is set it could be used to load a library that is not in the anaconda environment. That is why before activating an environment it might be good to do a

蟒蛇不使用蟒蛇之路。但是，我们应该注意到，如果设置了PYTHONPATH，它可以用来加载一个不在anaconda环境中的库。这就是为什么在激活一个环境之前最好做一个。

unset PYTHONPATH

For instance this PYTHONPATH points to an incorrect pandas lib:

例如，这个PYTHONPATH指向一个不正确的熊猫库:

export PYTHONPATH=/home/john/share/usr/anaconda/lib/python
source activate anaconda-2.7
python
>>>> import pandas as pd
/home/john/share/usr/lib/python/pandas-0.12.0-py2.7-linux-x86_64.egg/pandas/hashtable.so: undefined symbol: PyUnicodeUCS2_DecodeUTF8
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/home/john/share/usr/lib/python/pandas-0.12.0-py2.7-linux-x86_64.egg/pandas/__init__.py", line 6, in <module>
    from . import hashtable, tslib, lib
ImportError: /home/john/share/usr/lib/python/pandas-0.12.0-py2.7-linux-x86_64.egg/pandas/hashtable.so: undefined symbol: PyUnicodeUCS2_DecodeUTF8

unsetting the PYTHONPATH prevents the wrong pandas lib from being loaded:

打开PYTHONPATH可以防止错误的熊猫库被加载:

unset PYTHONPATH
source activate anaconda-2.7
python
>>>> import pandas as pd
>>>>

#1