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    <p>Since you're new to threading, there's something else worth bearing in mind - which I prefer to view as parallel scoping of values.</p> <p>With traditional linear/sequential programming for any given object you only have one thread accessing and changing a piece of data. This is generally made safe due to having lexical scope. Specifically one function can operate on a variable's value without affect a global value. If you don't have lexical scope, or poor lexical scoping, then changing the value of a variable named "foo" in one function affects another called "foo". It's less commonly a problem these days, but still common enough to be alluding to.</p> <p>With threading, you have the same issue, in more subtle ways. Whilst you still have lexical scoping helping you - in that a local value "X" inside one function is independent of another local value called "X" in another, the fact that data structures are mutable is a major source of bugs in threading.</p> <p>Specifically, if a function is passed a mutable value, then in a threaded environment unless you have taken care, that function cannot guarantee that the value is not being changed by anything else.</p> <p>This shared state is the source of probably 90-99% of bugs in threaded systems, and can be very hard to debug. As a result, if you're going to write a threaded system you should try to bear in mind the distance that your shared values will travel - ie the scope of parallel access.</p> <p>In order to limit bugs you have a handful of options which are known to work:</p> <ol> <li>Use no shared state - pass shared data using thread safe queues</li> <li>Place locks around all shared data, and ensure this is used religiously throughout your code. This can be far harder sometimes than people think. The problem comes from when you "forget" to lock an object - something which is remarkably easy for people to do.</li> <li>Have a single object - an owner - in charge of shared state. Allow client threads to ask it for copies of values in the shared state, which are accompanied by a token. When they want to update the shared state, they pass back messages to the single object, along with the token they had. The owner can then determine whether an update clash has occured.</li> </ol> <p>1 is most equivalent to unix pipelines. 3 is logically equivalent to version control, and is normally referred to as software transactional memory.</p> <p>1 &amp; 3 are modes of concurrency supported in Kamaelia which aims to eliminate bugs caused by class 2. (disclosure, I run the Kamaelia project) 2 isn't supported because it relies on "always getting everything right".</p> <p>No matter which approach you use to solve your problem though, bearing in mind this issue, and the ways of dealing with it, and planning upfront how you intend to deal with it will save you no end of headaches later on.</p>
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    1. COGreat. I'd add that threads are not very useful in python, and should be avoided for the extra complexibility and no benefit. They should be used only when the API you want to call is blocking and there's no non-blocking version of it (very rarely).
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