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Python thread pool and its principles and uses
In object-oriented programming, creating and destroying objects is very time-consuming, because creating an object requires obtaining memory resources or other resources. This is especially true in Java, where the virtual machine will try to track every object so that it can be garbage collected after the object is destroyed. Therefore, one way to improve the efficiency of service programs is to reduce the number of object creation and destruction as much as possible, especially the creation and destruction of some resource-intensive objects. PHP Chinese website brings you a variety of Python thread pool related download resources, related courses, related articles and other content for everyone to download and use for free.
Python thread pool and its principles and usesThe cost of the system starting a new thread is relatively high because it involves interaction with the operating system. In this case, using a thread pool can greatly improve performance, especially when the program needs to create a large number of threads with short lifetimes, you should consider using the thread pool. The thread pool creates a large number of idle threads when the system starts. As long as the program submits a function to the thread pool, the thread pool will start an idle thread to execute it. When the function is executed, the thread will not die, but will return to the thread pool again and become idle waiting to execute the next function.
The difference between python thread pool and multi-threadingThe difference between python thread pool and multi-threading: 1. Threads travel under the process; 2. Threads travel under the process; 3. A process can contain multiple threads; 4. Data is difficult to share between different processes; 5. Processes are smaller than Threads consume more computer resources.
How to pass single parameter and multiple parameters to python thread pool ThreadPoolExecutorPython thread pool ThreadPoolExecutor, passing a single parameter and multiple parameters This is the thread pool passing a single parameter fromconcurrent.futuresimportThreadPoolExecutor, as_completeddeftest(a):print(a)qq={"a":"1","b":"2 ","c":"3"}withThreadPoolExecutor()aspool:forj
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