在anaconda的"conda列表"中，针对环境多次列出了软件包. [英] Packages listed multiple times for an environment in anaconda's "conda list"

问题描述

当我在conda环境中列出包裹时，我得到了结果如下:

When I list packages in a conda environment, I get e.g. the following result:

$ conda list
# packages in environment at /Users/tkb/anaconda3/envs/xxx:
#
_nb_ext_conf              0.4.0                    py35_1  
anaconda-client           1.6.3                    py35_0  
appnope                   0.1.0                    py35_0  
backports.weakref         1.0rc1                    <pip>
bleach                    1.5.0                     <pip>
bleach                    1.5.0                    py35_0  
clyent                    1.2.2                    py35_0  
decorator                 4.0.11                   py35_0  
entrypoints               0.2.3                    py35_0  
html5lib                  0.999                    py35_0  
html5lib                  0.9999999                 <pip>
ipykernel                 4.6.1                    py35_0 
....

其中一些软件包以不同的版本多次出现，并且在第三列中有所不同.这有什么作用，第三列是什么意思?

Some of the packages are present multiple times with different versions and differ in the third column. What effect does this have, and what does the third column mean?

推荐答案

第三列告诉您如何安装软件包.如果它具有pyXX_Y，则由conda安装，并且XX指示Python主版本和次版本(即35为Python 3.5)，以及软件包的内部版本号，该内部版本号用于当软件包中的软件版本相同时，使用conda来帮助判断软件包的哪个版本是较新的.如果第三列显示<pip>，则说明该软件包是通过pip安装的.有时，conda安装软件包时会有第四列.此列指示软件包的安装渠道(由install或create命令中的-c或--channel指定).

The third column tells you how the package was installed. If it has pyXX_Y, it was installed by conda, and the XX indicate the Python major and minor version (i.e., 35 is Python 3.5), and the build number of the package, which is an internal number used by conda to help judge which versions of a package are newer when the version of the software in the package is the same. If the third column says <pip>, the package was installed by pip. Sometimes, there's a fourth column when the package was installed by conda; this column indicates the channel the package was installed from (specified by -c or --channel in the install or create command).

关于它的作用，可能取决于包装.通常，建议是尽可能使用conda将软件包安装到conda环境中，因为conda无法管理(卸载，升级等)pip安装的软件包.

As for what effect this has, it probably depends on the package. In general, the advice is to install packages into conda environments using conda whenever possible, because conda can't manage (uninstall, upgrade, etc.) packages that were installed by pip.

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