Google App Engine 如何限制 Python？
有谁知道GAE如何限制Python解释器？例如，它们如何阻止 IO 操作或 URL 操作。
共享主机也以某种方式做到这一点吗？
Does anybody know, how GAE limit Python interpreter? For example, how they block IO operations, or URL operations.
Shared hosting also do it in some way?
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沙箱通过具有特殊版本的 Python 解释器“在内部工作”。您运行的不是标准的 Python 可执行文件，而是经过专门修改以在 Google App 引擎上运行的可执行文件。
更新：
不，它不是普通意义上的虚拟机。每个应用程序都没有完整的虚拟PC。可能会有一些虚拟化正在进行，但谷歌并没有具体说明虚拟化的程度或内容。
操作系统中的进程通常已经限制了对操作系统其余部分和硬件的访问。谷歌对此进行了更多限制，您得到的环境中只允许读取文件系统的特定部分，而根本不能写入它，不允许打开套接字，也不允许进行系统调用等 不过，
我不知道操作系统/文件系统/解释器的每个限制是在哪个级别实现的。
The sandbox "internally works" by them having a special version of the Python interpreter. You aren't running the standard Python executable, but one especially modified to run on Google App engine.
Update:
And no it's not a virtual machine in the ordinary sense. Each application does not have a complete virtual PC. There may be some virtualization going on, but Google isn't saying exactly how much or what.
A process has normally in an operating system already limited access to the rest of the OS and the hardware. Google have limited this even more and you get an environment where you are only allowed to read the very specific parts of the file system, and not write to it at all, you are not allowed to open sockets and not allowed to make system calls etc.
I don't know at which level OS/Filesystem/Interpreter each limitation is implemented, though.
来自 Google 的网站：
应用程序只能访问其他应用程序
通过互联网连接的计算机
提供 URL 获取和电子邮件
服务。其他电脑只能
通过以下方式连接到应用程序
HTTP（或 HTTPS）请求
标准端口。
应用程序无法写入
文件系统。应用程序可以读取文件，
但仅限使用以下方式上传的文件
应用程序代码。该应用程序必须使用
App Engine 数据存储、memcache 或
所有数据的其他服务
在请求之间持续存在。
应用程序代码仅运行在
对网络请求的响应，排队
任务或计划任务，并且必须
30以内返回响应数据
无论如何，秒。一个请求
处理程序无法生成子进程或
响应后执行代码
已发送。
除此之外，您只能使用 Python 2.5，无法使用任何基于 C 的扩展，更新版本的 Web 框架在某些情况下将无法工作（再次是 Python 2.5）。
您可以阅读整篇文章什么是 Google App Engine？。
From Google's site:
An application can only access other
computers on the Internet through the
provided URL fetch and email
services. Other computers can only
connect to the application by making
HTTP (or HTTPS) requests on the
standard ports.
An application cannot write to the
file system. An app can read files,
but only files uploaded with the
application code. The app must use
the App Engine datastore, memcache or
other services for all data that
persists between requests.
Application code only runs in
response to a web request, a queued
task, or a scheduled task, and must
return response data within 30
seconds in any case. A request
handler cannot spawn a sub-process or
execute code after the response has
been sent.
Beyond that, you're stuck with Python 2.5, you can't use any C-based extensions, more up-to-date versions of web frameworks won't work in some cases (Python 2.5 again).
You can read the whole article What is Google App Engine?.
我发现这个网站
有一些相当不错的信息。你到底想做什么？
此处
新鲜！
请查看此处：http://code.google.com/appengine/docs/python /runtime.html
您的 IO 操作受到如下限制（超出禁用的模块）：
资源|免费默认配额|启用计费的默认配额
Blobstore |存储的数据| 1GB| 1 GB 可用空间；无上限
资源|计费已启用|默认配额
每日限额|最大速率
Blobstore API 调用 |140,000,000 次调用| 72,000 次调用/分钟
嗯，我的表格不太好，但希望仍然可读。
编辑：好的，我明白了。但是先生，您不必使用“f”这个词。 :) 你知道，这有点像整个“授人以鱼”的场景。我总是问 Google，这就是为什么我在这里回答问题只是为了好玩。
再次编辑：好的，在发表评论之前这更有意义。所以我又去回答了这个问题。我希望它有帮助。
I found this site
that has some pretty decent information. What exactly are you trying to do?
Here
FRESH!
Look here: http://code.google.com/appengine/docs/python/runtime.html
Your IO Operations are limited as follows (beyond disabled modules):
Resource| Free Default Quota| Billing Enabled Default Quota
Blobstore |Stored Data| 1 GB| 1 GB free; no maximum
Resource |Billing Enabled| Default Quota
Daily Limit| Maximum Rate
Blobstore API Calls |140,000,000 calls| 72,000 calls/minute
Hmm my table isn't that good, but hopefully still readable.
EDIT: OK, I understand. But sir, you did not have to use the "f" word. :) And you know, it's kinda like the whole 'teach a man to fish' scenario. Google is who I always ask and that's why I'm answering questions here for fun.
EDIT AGAIN: OK that made more sense before the comment was tooked. So I went and answered the question a little more. I hope it helps.
IMO 它不是标准的 python，而是专门为应用程序引擎修补的版本。换句话说，你可以或多或少地思考一个“更高级别”的虚拟机，但它不是模拟 x86 指令，而是模拟 python 操作码（如果你不知道它们是什么，请尝试编写一个名为“foo”的小函数，然后执行“import” dis; dis.dis(foo)”，您将看到编译器生成的 python 操作码）。
通过修补 python，您可以对其施加任何您喜欢的限制。当然，您必须禁止使用用户提供的 C/C++ 扩展模块，因为 C/C++ 模块将有权访问进程可以访问的所有内容。
使用这样的虚拟环境，您可以安全地运行 python 代码，而无需为每个实例使用单独的 x86 VM。
IMO it's not a standard python, but a version specifically patched for app engine. In other words you can think more or less like an "higher level" VM that however is not emulating x86 instructions but python opcodes (if you don't know what they are try writing a small function named "foo" and the doing "import dis; dis.dis(foo)" you will see the python opcodes that the compiler produced).
By patching python you can impose to it whatever limitations you like. Of course you've however to forbid the use of user supplied C/C++ extension modules as a C/C++ module will have access to everything the process can access.
Using such a virtual environment you're able to run safely python code without the need to use a separate x86 VM for every instance.