Async Techniques and Examples in Python Transcripts
Chapter: Course conclusion and review
Lecture: Review: Threads
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In contrast to the cooperative nature
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of asyncio type of concurrency on a single thread
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thread based parallelism lets the operating system
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decide when our code gets to run.
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We have a single process and that process
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has a main thread which may kick off additional threads
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spawn a couple additional pieces of work and then
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wait for them to complete and keep on running.
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And the important thing is it's up to the OS to figure out
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when a thread runs, not up to our particular process.
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Although the GIL does have something to say about
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it doesn't it, so here's the mental picture for threads.
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Here's the programming model, so we're going to start
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with the built in threading library.
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There's no external things to install here.
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We're going to have some function we want to run asynchronously
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but this is just normal Python code.
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It doesn't do any sort of async await or stuff like
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that, it's just code and instead of running on the main
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thread, we're going to run somewhere else.
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So given this, we'd like to create a bit of work
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that's going to run it so we set up the targets
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the arguments and if we want it not keep the
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process alive or be canceled more easily
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we can say it's a daemon thread.
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And then we just start it, potentially do some
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other work while it's running, or start other
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threads, things like that and then we're
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going to just wait for it to complete so we say work.join.
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Of course we can give it a timeout.
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We were just saying wait forever until it finishes.
