Python Threading Beginners Tutorial [video]

https://www.youtube.com/playlist?list=PLGKQkV4guDKEv1DoK4LYdo2ZPLo6cyLbm

by happy-go-lucky • 9 years ago

90 15 9 years ago

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tolgahanuzun2• 9 years ago

Nice video series. Why don't you work in a Linux environment?

nickyjaspers• 9 years ago

Should it make a difference then?

tolgahanuzun2• 9 years ago

I just wondered. Everyone recommends linux to me. I asked to get the idea. Not a criticism.

MikkoFinell• 9 years ago

Isn't multiprocessing almost syntactically equivalent to--but much more efficient than--threading in python?

chrisseaton2• 9 years ago

Syntactically equivalent? The syntax is the same - both multiprocessing and threading are achieved through libraries and VM primitives, not by additional syntax.

But if you meant semantically equivalent, no they aren't - threading is shared memory and multiprocessing is message passing. If you were to draw a tree of approaches to concurrency and parallelism, you would probably make this division the root node bisecting the domain into two - it's the two fundamental approaches to doing concurrency.

pvg• 9 years ago

It's an implementation difference with big practical implications. 'Fundamental divide at the root of all concurrency' seems more than a little overstated.

vitus• 9 years ago

threading is shared memory and multiprocessing is message passing

In most cases, yes. You can use shared memory buffers for IPC, though, although it typically requires more effort.

wdroz• 9 years ago

The problem is the GIL : https://wiki.python.org/moin/GlobalInterpreterLock

Multiprocessing allows you to use all cores, but you can't share memory like in threads. So you have to Serialize/Deserialize a lot for exchange data.

If your serializations cost are low and need computation power, you should use multiprocessing. If you are just waiting I/O you can use threads.

BTW, modern python "ProcessPoolExecutor" is not designed for compute heavy batch like "Pool" from "multiprocessing".

alanfranzoni2• 9 years ago

Interesting, but mostly pointless IMHO.

Python can't do proper multithreading because of the GIL (excluding Jython and IronPython, of course), hence using threads in Python doesn't benefit anyone.

If you want to learn how to do multithreaded programming, pick a language where multithreading actually works - Java would be a good example. Or just take a look at a POSIX threads tutorial.

If you want to handle concurrency in Python, ignore multithreading. Take a look at the multiprocessing module, or, for a different paradigm, at asyncio or Twisted.

js2• 9 years ago

Well this isn't the full story. If you have an I/O bound work-load, say you want to parallelize HTTP requests, threads work just fine.

alanfranzoni2• 9 years ago

If you have an I/O bound workload, a reactor or proactor approach are way better. No dealing with locks, race conditions, etc.

I never said it's wrong, it's just pointless. In Python, there's always a better alternative to multithreading which has no shortcomings.

vsajip• 9 years ago

If your threads are doing I/O rather than computation, then the GIL is less of an issue because it will be released until an I/O operation completes. It's only for threads which contend for the CPU that the GIL is a problem.

Python Threading Beginners Tutorial [video]

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