Support debugging of indirect child processes.

首先检查提到的入口点 debugpy.server.cli.options、debugpy.server.api 和 debugpy.connect，然后将它们与现有的直接子进程多进程支持进行比较。定义通过间接的非 Python 进程传递会话上下文的官方 API 边界；当所示的多级 worker 树能够在不依赖实现细节的情况下连接时，即表示完成。

While debugpy natively supports multiprocess debugging, this works only for directly launched child processes.
Sometimes, though, there may be several levels on non-Python processes between the main process and the child one needs to debug. I am hitting this limitation while trying to debug a user-defined function, that runs in the context of a PySpark worker process. The process tree looks like this:

<python process hosting my main program>
 └ <pyspark process>
    └ <yet another pyspark process>
       ├ <python worker process hosting the UDFs>
       ├ <python worker process hosting the UDFs>
       ├ ...
       └ <python worker process hosting the UDFs>

After spelunking the innards of debugpy for a few hours, I've managed to come up with this code:

import pickle
import os
import debugpy

def capture_session_context():
    """To be called in the main process to capture context of the current debugpy session."""
    options = debugpy.server.cli.options
    context = pickle.dumps((options.address, options.adapter_access_token, os.getpid()), 0)
    os.environ["DEBUGPY_CONTEXT"] = context.decode('ascii')

def connect_to_session():
    """To be called in a worker process to connect to the parent session."""
    context = os.environ['DEBUGPY_CONTEXT'].encode('ascii')
    address, token, ppid = pickle.loads(context)
    from debugpy.server import api
    api.pydevd.SetupHolder.setup = {"ppid": ppid}
    debugpy.connect(address, access_token=token)

Obviously, this hack uses a bunch of implementation details. It would be nice if this scenario was officially supported.
(I mean exposing official APIs similar to the above, not that debugpy should support PySperk specifically.