我已经构建了半长的shell脚本(300-500行)和Python代码，它们具有类似的功能。当执行许多外部命令时，我发现shell更容易使用。当有大量文本操作时，Perl也是一个很好的选择。

如果你的文本文件操作通常是一次性的，可能在shell提示符下完成，你从python中不会得到更好的东西。

另一方面，如果你经常不得不一遍又一遍地做同样的(或类似的)任务，并且你必须为此编写脚本，那么python是很棒的——你可以很容易地创建自己的库(你也可以用shell脚本来做，但它更麻烦)。

这是一个很简单的例子。

import popen2
stdout_text, stdin_text=popen2.popen2("your-shell-command-here")
for line in stdout_text:
  if line.startswith("#"):
    pass
  else
    jobID=int(line.split(",")[0].split()[1].lstrip("<").rstrip(">"))
    # do something with jobID

还要检查sys和getopt模块，它们是您首先需要的。

我已经构建了半长的shell脚本(300-500行)和Python代码，它们具有类似的功能。当执行许多外部命令时，我发现shell更容易使用。当有大量文本操作时，Perl也是一个很好的选择。

In the beginning there was sh, sed, and awk (and find, and grep, and...). It was good. But awk can be an odd little beast and hard to remember if you don't use it often. Then the great camel created Perl. Perl was a system administrator's dream. It was like shell scripting on steroids. Text processing, including regular expressions were just part of the language. Then it got ugly... People tried to make big applications with Perl. Now, don't get me wrong, Perl can be an application, but it can (can!) look like a mess if you're not really careful. Then there is all this flat data business. It's enough to drive a programmer nuts.

进入Python、Ruby等。这些都是非常好的通用语言。它们支持文本处理，并且做得很好(尽管可能与语言的基本核心没有那么紧密地交织在一起)。但它们也可以很好地扩展，并且在一天结束时仍然有漂亮的代码。他们还发展了相当庞大的社区，有大量的图书馆，几乎可以提供任何东西。

Now, much of the negativeness towards Perl is a matter of opinion, and certainly some people can write very clean Perl, but with this many people complaining about it being too easy to create obfuscated code, you know some grain of truth is there. The question really becomes then, are you ever going to use this language for more than simple bash script replacements. If not, learn some more Perl.. it is absolutely fantastic for that. If, on the other hand, you want a language that will grow with you as you want to do more, may I suggest Python or Ruby.

不管怎样，祝你好运!

在ShellPy库中可以使用python而不是bash。

下面是一个从Github下载Python用户头像的例子:

import json
import os
import tempfile

# get the api answer with curl
answer = `curl https://api.github.com/users/python
# syntactic sugar for checking returncode of executed process for zero
if answer:
    answer_json = json.loads(answer.stdout)
    avatar_url = answer_json['avatar_url']

    destination = os.path.join(tempfile.gettempdir(), 'python.png')

    # execute curl once again, this time to get the image
    result = `curl {avatar_url} > {destination}
    if result:
        # if there were no problems show the file
        p`ls -l {destination}
    else:
        print('Failed to download avatar')

    print('Avatar downloaded')
else:
    print('Failed to access github api')

如您所见，所有在grave重音(')符号内的表达式都在shell中执行。在Python代码中，您可以捕获此执行的结果并对其执行操作。例如:

log = `git log --pretty=oneline --grep='Create'

这一行首先在shell中执行git log——pretty=oneline——grep='Create'，然后将结果赋值给log变量。结果具有以下属性:

从已执行进程的Stdout中Stdout整个文本

Stderr从已执行进程的Stderr得到的整个文本

Returncode执行的返回码

这是该库的总体概述，更详细的描述和示例可以在这里找到。

任何shell都有几组特性。

The Essential Linux/Unix commands. All of these are available through the subprocess library. This isn't always the best first choice for doing all external commands. Look also at shutil for some commands that are separate Linux commands, but you could probably implement directly in your Python scripts. Another huge batch of Linux commands are in the os library; you can do these more simply in Python. And -- bonus! -- more quickly. Each separate Linux command in the shell (with a few exceptions) forks a subprocess. By using Python shutil and os modules, you don't fork a subprocess. The shell environment features. This includes stuff that sets a command's environment (current directory and environment variables and what-not). You can easily manage this from Python directly. The shell programming features. This is all the process status code checking, the various logic commands (if, while, for, etc.) the test command and all of it's relatives. The function definition stuff. This is all much, much easier in Python. This is one of the huge victories in getting rid of bash and doing it in Python. Interaction features. This includes command history and what-not. You don't need this for writing shell scripts. This is only for human interaction, and not for script-writing. The shell file management features. This includes redirection and pipelines. This is trickier. Much of this can be done with subprocess. But some things that are easy in the shell are unpleasant in Python. Specifically stuff like (a | b; c ) | something >result. This runs two processes in parallel (with output of a as input to b), followed by a third process. The output from that sequence is run in parallel with something and the output is collected into a file named result. That's just complex to express in any other language.

特定的程序(awk、sed、grep等)通常可以被重写为Python模块。不要走极端。替换您需要的内容并改进“grep”模块。不要一开始就编写一个替换“grep”的Python模块。

最好的事情是你可以一步一步来做。

用Python替换AWK和PERL。不要管其他的事情。 看看用Python替换GREP。这可能有点复杂，但是您的GREP版本可以根据您的处理需求进行定制。 看看用使用os.walk的Python循环替换FIND。这是一个巨大的胜利，因为您不需要生成那么多的进程。 看看用Python脚本替换常见的shell逻辑(循环、决策等)。