This necessarily makes this section of code linear -- only one thread at a time. But if your entire program is sequential you shouldn't be using threads anyway. The idea is that you gain speed up based on the percentage of code you have that can execute outside locks and run in parallel.
This is one reason why using threads on a 2 core system doesn't double performance for everything. Once it is released, the first thread to move forward and acquire the lock will block all other waiting threads. Stack Overflow for Teams — Collaborate and share knowledge with a private group. Create a free Team What is Teams? Collectives on Stack Overflow. Learn more.
Why should you lock threads? Ask Question. Asked 10 years, 5 months ago. Active 2 years, 6 months ago. Viewed 6k times. Does locking ensure that threads DON'T execute simultaneously? I'm referring to using the lock functions like lock and acquire in the threading module btw Improve this question.
MistahX MistahX 2 2 gold badges 9 9 silver badges 21 21 bronze badges. No I'm not asking about the GIL, I know the limitations of it in python and am happy with it, the question is about locking threads with acquire and release non related to the GIL other than it has lock in the name — MistahX. Retagged, as not exclusive to python at all. You say "lock functions like lock and acquire in the threading module", but there are no such functions.
There is a Lock factory that returns a Lock object , which has acquire and release methods. This has nothing to do with "locking a thread", it's just a basic mutex. Add a comment.
Active Oldest Votes. Improve this answer. Okay this makes sense, but the locks i'm talking about lock threads, not files? So what do they do? MistahX: No, they lock whatever you decide they lock. You use them as you see fit to prevent multiple threads from doing the same thing at the same time. They're primitives, you build from them what you need. Why not? What would be better to use for lock ordering than the name? Although lock ordering is useful particularly in code like operating system kernels , it has a number of drawbacks in practice.
A more common approach than lock ordering, particularly for application programming as opposed to operating system or device driver programming , is to use coarser locking — use a single lock to guard many object instances, or even a whole subsystem of a program. For example, we might have a single lock for an entire social network, and have all the operations on any of its constituent parts synchronize on that lock.
Coarse-grained locks can have a significant performance penalty. In the worst case, having a single lock protecting everything, your program might be essentially sequential — only one thread is allowed to make progress at a time. In the code below three threads 1, 2, and 3 are trying to acquire locks on objects alpha , beta , and gamma. For each of the scenarios below, determine whether the system is in deadlock if the threads are currently on the indicated lines of code.
Thread 1 inside using alpha Thread 2 blocked on synchronized alpha Thread 3 finished. Thread 1 finished Thread 2 blocked on synchronized beta Thread 3 blocked on 2nd synchronized gamma. Thread 1 running synchronized beta Thread 2 blocked on synchronized gamma Thread 3 blocked on 1st synchronized gamma. Thread 1 blocked on synchronized beta Thread 2 finished Thread 3 blocked on 2nd synchronized gamma.
Recall that our primary goals are to create software that is safe from bugs , easy to understand , and ready for change. Building concurrent software is clearly a challenge for all three of these goals. We can break the issues into two general classes. When we ask whether a concurrent program is safe from bugs , we care about two properties:. Does the concurrent program satisfy its invariants and its specifications? Races in accessing mutable data threaten safety. Safety asks the question: can you prove that some bad thing never happens?
Does the program keep running and eventually do what you want, or does it get stuck somewhere waiting forever for events that will never happen? Can you prove that some good thing eventually happens?
Deadlocks threaten liveness. Liveness may also require fairness , which means that concurrent modules are given processing capacity to make progress on their computations. Library data structures either use no synchronization to offer high performance to single-threaded clients, while leaving it to multithreaded clients to add locking on top or the monitor pattern.
Mutable data structures with many parts typically use either coarse-grained locking or thread confinement. Most graphical user interface toolkits follow one of these approaches, because a graphical user interface is basically a big mutable tree of mutable objects.
Java Swing, the graphical user interface toolkit, uses thread confinement. Other threads have to pass messages to that dedicated thread in order to access the tree. Search often uses immutable datatypes. Our Boolean formula satisfiability search would be easy to make multithreaded, because all the datatypes involved were immutable.
There would be no risk of either races or deadlocks. Operating systems often use fine-grained locks in order to get high performance, and use lock ordering to deal with deadlock problems.
Databases can also manage locks, and handle locking order automatically. For more about how to use databases in system design, 6.
Producing a concurrent program that is safe from bugs, easy to understand, and ready for change requires careful thinking. And threads can interleave their operations in so many different ways that you will never be able to test even a small fraction of all possible executions. Acquiring a lock allows a thread to have exclusive access to the data guarded by that lock, forcing other threads to block — as long as those threads are also trying to acquire that same lock.
The monitor pattern guards the rep of a datatype with a single lock that is acquired by every method. Software in 6. Communicating clearly with future programmers, including future you. Designed to accommodate change without rewriting. Objectives Understand how a lock is used to protect shared mutable data Be able to recognize deadlock and know strategies to prevent it Know the monitor pattern and be able to apply it to a data type Introduction Earlier, we defined thread safety for a data type or a function as behaving correctly when used from multiple threads, regardless of how those threads are executed, without additional coordination.
Immutability : make the shared data immutable. Use existing threadsafe data types : use a data type that does the coordination for you. Synchronization : prevent threads from accessing the shared data at the same time.
Bank account example. In the Java Tutorials, read: Deadlock 1 page. We chose two of them for EditBuffer , and this is often a good idea: Implement a simple, brute-force rep first.
Locks are so commonly-used that Java provides them as a built-in language feature. Locks guard access to data Locks are used to guard a shared data variable, like the account balance shown here. Reading exercises Synchronizing with locks. If thread B tries to acquire a lock currently held by thread A: What happens to thread A? This list is mine, all mine. OK fine but this synchronized List is totally mine. I heard you like locks so I acquired your lock so you can lock while you acquire.
If text were public: public String text; then clients outside SimpleBuffer would be able to read and write it without knowing that they should first acquire the lock, and SimpleBuffer would no longer be threadsafe. Locking discipline A locking discipline is a strategy for ensuring that synchronized code is threadsafe. We must satisfy two conditions: Every shared mutable variable must be guarded by some lock.
Thread A acquires the lock on harry because the friend method is synchronized. Then thread B acquires the lock on snape for the same reason. They both update their individual reps independently, and then try to call friend on the other object — which requires them to acquire the lock on the other object.
Deadlock solution 1: lock ordering One way to prevent deadlock is to put an ordering on the locks that need to be acquired simultaneously, and ensuring that all code acquires the locks in that order. Second, it may be difficult or impossible for the code to know exactly which of those locks it will need before it even acquires the first one.
It may need to do some computation to figure it out. Reading exercises Deadlock. Scenario A Thread 1 inside using alpha Thread 2 blocked on synchronized alpha Thread 3 finished deadlock missing answer.
Locked out. Examine the code again. Calling the release method on a lock, in an unlocked state, results in an error. Code Example The following code shows how locks can be used in Python with a simple example: Suppose that there are dollars in a bank account. Race Condition The final answer might be incorrect due to the race condition. You may have to run the code several times to re-create the error.
Using a lock to solve the problem The code between the acquire and release methods are executed atomically so that there is no chance that a thread will read a non-updated version after another thread has already made a change. Keep Exploring. Related Courses. Learn in-demand tech skills in half the time. Early Access Courses. Assessments New. Free Trial New. For Business.
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