As we saw earlier, when scripts spawn threads—tasks that run in parallel within the program—they can naturally communicate by changing and inspecting shared global memory. As we also saw, some care must be taken to use locks to synchronize access to shared objects that can’t be updated concurrently, but it’s a fairly straightforward communication model.
Things aren’t quite as simple when scripts start processes and programs. If we limit the kinds of communications that can happen between programs, many options are available, most of which we’ve already seen in this and the prior chapters. For example, the following can all be interpreted as cross-program communication devices:
For instance, sending command-line options and writing to input
streams lets us pass in program execution parameters; reading program
output streams and exit codes gives us a way to grab a result. Because
shell variable settings are inherited by spawned programs, they
provide another way to pass context in. Pipes made by os.popen
and simple files allow even more
dynamic communication. Data can be sent between programs at arbitrary
times, not only at program start and exit.
Beyond this set, there are other tools in the Python library for
performing Inter-Process Communication (IPC). Some vary in
portability, and all vary in complexity. For instance, in the Internet
scripting part of this text we will meet the Python socket
module, which lets us transfer data
between programs running on the same computer as well as programs
located on remote networked machines.
In this section, we introduce pipes—both
anonymous and named—as well as signals, or
cross-program event triggers. Other IPC tools are available to Python
programmers (e.g., shared memory; see the mmap
module) but are not covered here for
lack of space; search the Python manuals and web site for more details
on other IPC schemes if you’re looking for something more
specific.
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